gogol-ml-0.4.0: Google Cloud Machine Learning Engine SDK.

Copyright(c) 2015-2016 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay <brendan.g.hay@gmail.com>
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellNone
LanguageHaskell2010

Network.Google.MachineLearning.Types

Contents

Description

 
Synopsis

Service Configuration

machineLearningService :: ServiceConfig Source #

Default request referring to version v1 of the Cloud Machine Learning Engine. This contains the host and root path used as a starting point for constructing service requests.

OAuth Scopes

cloudPlatformScope :: Proxy '["https://www.googleapis.com/auth/cloud-platform"] Source #

View and manage your data across Google Cloud Platform services

GoogleIAMV1__AuditConfig

data GoogleIAMV1__AuditConfig Source #

Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices" "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:foo'gmail.com" ] }, { "log_type": "DATA_WRITE", }, { "log_type": "ADMIN_READ", } ] }, { "service": "fooservice.googleapis.com" "audit_log_configs": [ { "log_type": "DATA_READ", }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:bar'gmail.com" ] } ] } ] } For fooservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts foo'gmail.com from DATA_READ logging, and bar'gmail.com from DATA_WRITE logging.

See: googleIAMV1__AuditConfig smart constructor.

Instances
Eq GoogleIAMV1__AuditConfig Source # 
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Data GoogleIAMV1__AuditConfig Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleIAMV1__AuditConfig -> c GoogleIAMV1__AuditConfig #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleIAMV1__AuditConfig #

toConstr :: GoogleIAMV1__AuditConfig -> Constr #

dataTypeOf :: GoogleIAMV1__AuditConfig -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleIAMV1__AuditConfig) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleIAMV1__AuditConfig) #

gmapT :: (forall b. Data b => b -> b) -> GoogleIAMV1__AuditConfig -> GoogleIAMV1__AuditConfig #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__AuditConfig -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__AuditConfig -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleIAMV1__AuditConfig -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleIAMV1__AuditConfig -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditConfig -> m GoogleIAMV1__AuditConfig #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditConfig -> m GoogleIAMV1__AuditConfig #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditConfig -> m GoogleIAMV1__AuditConfig #

Show GoogleIAMV1__AuditConfig Source # 
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Generic GoogleIAMV1__AuditConfig Source # 
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Associated Types

type Rep GoogleIAMV1__AuditConfig :: Type -> Type #

ToJSON GoogleIAMV1__AuditConfig Source # 
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FromJSON GoogleIAMV1__AuditConfig Source # 
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type Rep GoogleIAMV1__AuditConfig Source # 
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type Rep GoogleIAMV1__AuditConfig = D1 (MetaData "GoogleIAMV1__AuditConfig" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleIAMV1__AuditConfig'" PrefixI True) (S1 (MetaSel (Just "_givacService") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_givacAuditLogConfigs") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleIAMV1__AuditLogConfig]))))

googleIAMV1__AuditConfig :: GoogleIAMV1__AuditConfig Source #

Creates a value of GoogleIAMV1__AuditConfig with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

givacService :: Lens' GoogleIAMV1__AuditConfig (Maybe Text) Source #

Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.

givacAuditLogConfigs :: Lens' GoogleIAMV1__AuditConfig [GoogleIAMV1__AuditLogConfig] Source #

The configuration for logging of each type of permission.

GoogleCloudMlV1__Version

data GoogleCloudMlV1__Version Source #

Represents a version of the model. Each version is a trained model deployed in the cloud, ready to handle prediction requests. A model can have multiple versions. You can get information about all of the versions of a given model by calling projects.models.versions.list.

See: googleCloudMlV1__Version smart constructor.

Instances
Eq GoogleCloudMlV1__Version Source # 
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Data GoogleCloudMlV1__Version Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__Version -> c GoogleCloudMlV1__Version #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__Version #

toConstr :: GoogleCloudMlV1__Version -> Constr #

dataTypeOf :: GoogleCloudMlV1__Version -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__Version) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__Version) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__Version -> GoogleCloudMlV1__Version #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Version -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Version -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__Version -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__Version -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Version -> m GoogleCloudMlV1__Version #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Version -> m GoogleCloudMlV1__Version #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Version -> m GoogleCloudMlV1__Version #

Show GoogleCloudMlV1__Version Source # 
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Generic GoogleCloudMlV1__Version Source # 
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Associated Types

type Rep GoogleCloudMlV1__Version :: Type -> Type #

ToJSON GoogleCloudMlV1__Version Source # 
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FromJSON GoogleCloudMlV1__Version Source # 
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type Rep GoogleCloudMlV1__Version Source # 
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type Rep GoogleCloudMlV1__Version = D1 (MetaData "GoogleCloudMlV1__Version" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__Version'" PrefixI True) ((((S1 (MetaSel (Just "_gcmvvFramework") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__VersionFramework)) :*: S1 (MetaSel (Just "_gcmvvEtag") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bytes))) :*: (S1 (MetaSel (Just "_gcmvvState") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__VersionState)) :*: S1 (MetaSel (Just "_gcmvvAutoScaling") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__AutoScaling)))) :*: ((S1 (MetaSel (Just "_gcmvvPythonVersion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvvRuntimeVersion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) :*: (S1 (MetaSel (Just "_gcmvvLastUseTime") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe DateTime')) :*: S1 (MetaSel (Just "_gcmvvName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))))) :*: (((S1 (MetaSel (Just "_gcmvvDeploymentURI") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvvManualScaling") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__ManualScaling))) :*: (S1 (MetaSel (Just "_gcmvvMachineType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvvLabels") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__VersionLabels)))) :*: ((S1 (MetaSel (Just "_gcmvvErrorMessage") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvvDescription") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) :*: (S1 (MetaSel (Just "_gcmvvCreateTime") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe DateTime')) :*: S1 (MetaSel (Just "_gcmvvIsDefault") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)))))))

gcmvvFramework :: Lens' GoogleCloudMlV1__Version (Maybe GoogleCloudMlV1__VersionFramework) Source #

Optional. The machine learning framework Cloud ML Engine uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, Cloud ML Engine will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater.

gcmvvEtag :: Lens' GoogleCloudMlV1__Version (Maybe ByteString) Source #

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetVersion`, and systems are expected to put that etag in the request to `UpdateVersion` to ensure that their change will be applied to the model as intended.

gcmvvAutoScaling :: Lens' GoogleCloudMlV1__Version (Maybe GoogleCloudMlV1__AutoScaling) Source #

Automatically scale the number of nodes used to serve the model in response to increases and decreases in traffic. Care should be taken to ramp up traffic according to the model's ability to scale or you will start seeing increases in latency and 429 response codes.

gcmvvPythonVersion :: Lens' GoogleCloudMlV1__Version (Maybe Text) Source #

Optional. The version of Python used in prediction. If not set, the default version is '2.7'. Python '3.5' is available when `runtime_version` is set to '1.4' and above. Python '2.7' works with all supported runtime versions.

gcmvvRuntimeVersion :: Lens' GoogleCloudMlV1__Version (Maybe Text) Source #

Optional. The Cloud ML Engine runtime version to use for this deployment. If not set, Cloud ML Engine uses the default stable version, 1.0. For more information, see the runtime version list and how to manage runtime versions.

gcmvvLastUseTime :: Lens' GoogleCloudMlV1__Version (Maybe UTCTime) Source #

Output only. The time the version was last used for prediction.

gcmvvName :: Lens' GoogleCloudMlV1__Version (Maybe Text) Source #

Required.The name specified for the version when it was created. The version name must be unique within the model it is created in.

gcmvvDeploymentURI :: Lens' GoogleCloudMlV1__Version (Maybe Text) Source #

Required. The Google Cloud Storage location of the trained model used to create the version. See the guide to model deployment for more information. When passing Version to projects.models.versions.create the model service uses the specified location as the source of the model. Once deployed, the model version is hosted by the prediction service, so this location is useful only as a historical record. The total number of model files can't exceed 1000.

gcmvvManualScaling :: Lens' GoogleCloudMlV1__Version (Maybe GoogleCloudMlV1__ManualScaling) Source #

Manually select the number of nodes to use for serving the model. You should generally use `auto_scaling` with an appropriate `min_nodes` instead, but this option is available if you want more predictable billing. Beware that latency and error rates will increase if the traffic exceeds that capability of the system to serve it based on the selected number of nodes.

gcmvvMachineType :: Lens' GoogleCloudMlV1__Version (Maybe Text) Source #

Optional. The type of machine on which to serve the model. Currently only applies to online prediction service. The following are currently supported and will be deprecated in Beta release. mls1-highmem-1 1 core 2 Gb RAM mls1-highcpu-4 4 core 2 Gb RAM The following are available in Beta: mls1-c1-m2 1 core 2 Gb RAM Default mls1-c4-m2 4 core 2 Gb RAM

gcmvvLabels :: Lens' GoogleCloudMlV1__Version (Maybe GoogleCloudMlV1__VersionLabels) Source #

Optional. One or more labels that you can add, to organize your model versions. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

gcmvvErrorMessage :: Lens' GoogleCloudMlV1__Version (Maybe Text) Source #

Output only. The details of a failure or a cancellation.

gcmvvDescription :: Lens' GoogleCloudMlV1__Version (Maybe Text) Source #

Optional. The description specified for the version when it was created.

gcmvvCreateTime :: Lens' GoogleCloudMlV1__Version (Maybe UTCTime) Source #

Output only. The time the version was created.

gcmvvIsDefault :: Lens' GoogleCloudMlV1__Version (Maybe Bool) Source #

Output only. If true, this version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.methods.versions.setDefault.

GoogleCloudMlV1__PredictionOutput

data GoogleCloudMlV1__PredictionOutput Source #

Represents results of a prediction job.

See: googleCloudMlV1__PredictionOutput smart constructor.

Instances
Eq GoogleCloudMlV1__PredictionOutput Source # 
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Data GoogleCloudMlV1__PredictionOutput Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__PredictionOutput -> c GoogleCloudMlV1__PredictionOutput #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__PredictionOutput #

toConstr :: GoogleCloudMlV1__PredictionOutput -> Constr #

dataTypeOf :: GoogleCloudMlV1__PredictionOutput -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__PredictionOutput) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__PredictionOutput) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__PredictionOutput -> GoogleCloudMlV1__PredictionOutput #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictionOutput -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictionOutput -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictionOutput -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictionOutput -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionOutput -> m GoogleCloudMlV1__PredictionOutput #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionOutput -> m GoogleCloudMlV1__PredictionOutput #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionOutput -> m GoogleCloudMlV1__PredictionOutput #

Show GoogleCloudMlV1__PredictionOutput Source # 
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Generic GoogleCloudMlV1__PredictionOutput Source # 
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type Rep GoogleCloudMlV1__PredictionOutput :: Type -> Type #

ToJSON GoogleCloudMlV1__PredictionOutput Source # 
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FromJSON GoogleCloudMlV1__PredictionOutput Source # 
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type Rep GoogleCloudMlV1__PredictionOutput Source # 
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type Rep GoogleCloudMlV1__PredictionOutput = D1 (MetaData "GoogleCloudMlV1__PredictionOutput" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__PredictionOutput'" PrefixI True) ((S1 (MetaSel (Just "_gcmvpoNodeHours") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Double))) :*: S1 (MetaSel (Just "_gcmvpoErrorCount") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64)))) :*: (S1 (MetaSel (Just "_gcmvpoPredictionCount") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64))) :*: S1 (MetaSel (Just "_gcmvpoOutputPath") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))))

googleCloudMlV1__PredictionOutput :: GoogleCloudMlV1__PredictionOutput Source #

Creates a value of GoogleCloudMlV1__PredictionOutput with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvpoNodeHours :: Lens' GoogleCloudMlV1__PredictionOutput (Maybe Double) Source #

Node hours used by the batch prediction job.

gcmvpoErrorCount :: Lens' GoogleCloudMlV1__PredictionOutput (Maybe Int64) Source #

The number of data instances which resulted in errors.

gcmvpoOutputPath :: Lens' GoogleCloudMlV1__PredictionOutput (Maybe Text) Source #

The output Google Cloud Storage location provided at the job creation time.

GoogleCloudMlV1__HyperparameterOutputHyperparameters

data GoogleCloudMlV1__HyperparameterOutputHyperparameters Source #

The hyperparameters given to this trial.

See: googleCloudMlV1__HyperparameterOutputHyperparameters smart constructor.

Instances
Eq GoogleCloudMlV1__HyperparameterOutputHyperparameters Source # 
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Data GoogleCloudMlV1__HyperparameterOutputHyperparameters Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> c GoogleCloudMlV1__HyperparameterOutputHyperparameters #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__HyperparameterOutputHyperparameters #

toConstr :: GoogleCloudMlV1__HyperparameterOutputHyperparameters -> Constr #

dataTypeOf :: GoogleCloudMlV1__HyperparameterOutputHyperparameters -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__HyperparameterOutputHyperparameters) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__HyperparameterOutputHyperparameters) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> GoogleCloudMlV1__HyperparameterOutputHyperparameters #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> m GoogleCloudMlV1__HyperparameterOutputHyperparameters #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> m GoogleCloudMlV1__HyperparameterOutputHyperparameters #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterOutputHyperparameters -> m GoogleCloudMlV1__HyperparameterOutputHyperparameters #

Show GoogleCloudMlV1__HyperparameterOutputHyperparameters Source # 
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Generic GoogleCloudMlV1__HyperparameterOutputHyperparameters Source # 
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ToJSON GoogleCloudMlV1__HyperparameterOutputHyperparameters Source # 
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FromJSON GoogleCloudMlV1__HyperparameterOutputHyperparameters Source # 
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type Rep GoogleCloudMlV1__HyperparameterOutputHyperparameters Source # 
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type Rep GoogleCloudMlV1__HyperparameterOutputHyperparameters = D1 (MetaData "GoogleCloudMlV1__HyperparameterOutputHyperparameters" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__HyperparameterOutputHyperparameters'" PrefixI True) (S1 (MetaSel (Just "_gcmvhohAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text Text))))

googleCloudMlV1__HyperparameterOutputHyperparameters Source #

Creates a value of GoogleCloudMlV1__HyperparameterOutputHyperparameters with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

GoogleCloudMlV1__PredictRequest

data GoogleCloudMlV1__PredictRequest Source #

Request for predictions to be issued against a trained model.

See: googleCloudMlV1__PredictRequest smart constructor.

Instances
Eq GoogleCloudMlV1__PredictRequest Source # 
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Data GoogleCloudMlV1__PredictRequest Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__PredictRequest -> c GoogleCloudMlV1__PredictRequest #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__PredictRequest #

toConstr :: GoogleCloudMlV1__PredictRequest -> Constr #

dataTypeOf :: GoogleCloudMlV1__PredictRequest -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__PredictRequest) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__PredictRequest) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__PredictRequest -> GoogleCloudMlV1__PredictRequest #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictRequest -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictRequest -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictRequest -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictRequest -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictRequest -> m GoogleCloudMlV1__PredictRequest #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictRequest -> m GoogleCloudMlV1__PredictRequest #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictRequest -> m GoogleCloudMlV1__PredictRequest #

Show GoogleCloudMlV1__PredictRequest Source # 
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Generic GoogleCloudMlV1__PredictRequest Source # 
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type Rep GoogleCloudMlV1__PredictRequest :: Type -> Type #

ToJSON GoogleCloudMlV1__PredictRequest Source # 
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FromJSON GoogleCloudMlV1__PredictRequest Source # 
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type Rep GoogleCloudMlV1__PredictRequest Source # 
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type Rep GoogleCloudMlV1__PredictRequest = D1 (MetaData "GoogleCloudMlV1__PredictRequest" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__PredictRequest'" PrefixI True) (S1 (MetaSel (Just "_gcmvprHTTPBody") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (Maybe GoogleAPI__HTTPBody))))

googleCloudMlV1__PredictRequest :: GoogleCloudMlV1__PredictRequest Source #

Creates a value of GoogleCloudMlV1__PredictRequest with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

GoogleCloudMlV1__ParameterSpecType

data GoogleCloudMlV1__ParameterSpecType Source #

Required. The type of the parameter.

Constructors

ParameterTypeUnspecified

PARAMETER_TYPE_UNSPECIFIED You must specify a valid type. Using this unspecified type will result in an error.

Double

DOUBLE Type for real-valued parameters.

Integer

INTEGER Type for integral parameters.

Categorical

CATEGORICAL The parameter is categorical, with a value chosen from the categories field.

Discrete

DISCRETE The parameter is real valued, with a fixed set of feasible points. If `type==DISCRETE`, feasible_points must be provided, and {`min_value`, `max_value`} will be ignored.

Instances
Enum GoogleCloudMlV1__ParameterSpecType Source # 
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Eq GoogleCloudMlV1__ParameterSpecType Source # 
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Data GoogleCloudMlV1__ParameterSpecType Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ParameterSpecType -> c GoogleCloudMlV1__ParameterSpecType #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ParameterSpecType #

toConstr :: GoogleCloudMlV1__ParameterSpecType -> Constr #

dataTypeOf :: GoogleCloudMlV1__ParameterSpecType -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ParameterSpecType) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ParameterSpecType) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ParameterSpecType -> GoogleCloudMlV1__ParameterSpecType #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ParameterSpecType -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ParameterSpecType -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ParameterSpecType -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ParameterSpecType -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpecType -> m GoogleCloudMlV1__ParameterSpecType #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpecType -> m GoogleCloudMlV1__ParameterSpecType #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpecType -> m GoogleCloudMlV1__ParameterSpecType #

Ord GoogleCloudMlV1__ParameterSpecType Source # 
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Read GoogleCloudMlV1__ParameterSpecType Source # 
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Show GoogleCloudMlV1__ParameterSpecType Source # 
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Generic GoogleCloudMlV1__ParameterSpecType Source # 
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Associated Types

type Rep GoogleCloudMlV1__ParameterSpecType :: Type -> Type #

Hashable GoogleCloudMlV1__ParameterSpecType Source # 
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ToJSON GoogleCloudMlV1__ParameterSpecType Source # 
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FromJSON GoogleCloudMlV1__ParameterSpecType Source # 
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FromHttpApiData GoogleCloudMlV1__ParameterSpecType Source # 
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ToHttpApiData GoogleCloudMlV1__ParameterSpecType Source # 
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type Rep GoogleCloudMlV1__ParameterSpecType Source # 
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type Rep GoogleCloudMlV1__ParameterSpecType = D1 (MetaData "GoogleCloudMlV1__ParameterSpecType" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "ParameterTypeUnspecified" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Double" PrefixI False) (U1 :: Type -> Type)) :+: (C1 (MetaCons "Integer" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "Categorical" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Discrete" PrefixI False) (U1 :: Type -> Type))))

GoogleCloudMlV1__TrainingInputScaleTier

data GoogleCloudMlV1__TrainingInputScaleTier Source #

Required. Specifies the machine types, the number of replicas for workers and parameter servers.

Constructors

Basic

BASIC A single worker instance. This tier is suitable for learning how to use Cloud ML, and for experimenting with new models using small datasets.

Standard1

STANDARD_1 Many workers and a few parameter servers.

Premium1

PREMIUM_1 A large number of workers with many parameter servers.

BasicGpu

BASIC_GPU A single worker instance with a GPU.

BasicTpu

BASIC_TPU A single worker instance with a Cloud TPU.

Custom

CUSTOM The CUSTOM tier is not a set tier, but rather enables you to use your own cluster specification. When you use this tier, set values to configure your processing cluster according to these guidelines: * You _must_ set `TrainingInput.masterType` to specify the type of machine to use for your master node. This is the only required setting. * You _may_ set `TrainingInput.workerCount` to specify the number of workers to use. If you specify one or more workers, you _must_ also set `TrainingInput.workerType` to specify the type of machine to use for your worker nodes. * You _may_ set `TrainingInput.parameterServerCount` to specify the number of parameter servers to use. If you specify one or more parameter servers, you _must_ also set `TrainingInput.parameterServerType` to specify the type of machine to use for your parameter servers. Note that all of your workers must use the same machine type, which can be different from your parameter server type and master type. Your parameter servers must likewise use the same machine type, which can be different from your worker type and master type.

Instances
Enum GoogleCloudMlV1__TrainingInputScaleTier Source # 
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Eq GoogleCloudMlV1__TrainingInputScaleTier Source # 
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Data GoogleCloudMlV1__TrainingInputScaleTier Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__TrainingInputScaleTier -> c GoogleCloudMlV1__TrainingInputScaleTier #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__TrainingInputScaleTier #

toConstr :: GoogleCloudMlV1__TrainingInputScaleTier -> Constr #

dataTypeOf :: GoogleCloudMlV1__TrainingInputScaleTier -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__TrainingInputScaleTier) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__TrainingInputScaleTier) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__TrainingInputScaleTier -> GoogleCloudMlV1__TrainingInputScaleTier #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__TrainingInputScaleTier -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__TrainingInputScaleTier -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__TrainingInputScaleTier -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__TrainingInputScaleTier -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingInputScaleTier -> m GoogleCloudMlV1__TrainingInputScaleTier #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingInputScaleTier -> m GoogleCloudMlV1__TrainingInputScaleTier #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingInputScaleTier -> m GoogleCloudMlV1__TrainingInputScaleTier #

Ord GoogleCloudMlV1__TrainingInputScaleTier Source # 
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Read GoogleCloudMlV1__TrainingInputScaleTier Source # 
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Show GoogleCloudMlV1__TrainingInputScaleTier Source # 
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Generic GoogleCloudMlV1__TrainingInputScaleTier Source # 
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Hashable GoogleCloudMlV1__TrainingInputScaleTier Source # 
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ToJSON GoogleCloudMlV1__TrainingInputScaleTier Source # 
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FromJSON GoogleCloudMlV1__TrainingInputScaleTier Source # 
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FromHttpApiData GoogleCloudMlV1__TrainingInputScaleTier Source # 
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ToHttpApiData GoogleCloudMlV1__TrainingInputScaleTier Source # 
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type Rep GoogleCloudMlV1__TrainingInputScaleTier Source # 
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type Rep GoogleCloudMlV1__TrainingInputScaleTier = D1 (MetaData "GoogleCloudMlV1__TrainingInputScaleTier" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "Basic" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "Standard1" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Premium1" PrefixI False) (U1 :: Type -> Type))) :+: (C1 (MetaCons "BasicGpu" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "BasicTpu" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Custom" PrefixI False) (U1 :: Type -> Type))))

GoogleLongrunning__OperationResponse

data GoogleLongrunning__OperationResponse Source #

The normal response of the operation in case of success. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.

See: googleLongrunning__OperationResponse smart constructor.

Instances
Eq GoogleLongrunning__OperationResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Data GoogleLongrunning__OperationResponse Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleLongrunning__OperationResponse -> c GoogleLongrunning__OperationResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleLongrunning__OperationResponse #

toConstr :: GoogleLongrunning__OperationResponse -> Constr #

dataTypeOf :: GoogleLongrunning__OperationResponse -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleLongrunning__OperationResponse) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleLongrunning__OperationResponse) #

gmapT :: (forall b. Data b => b -> b) -> GoogleLongrunning__OperationResponse -> GoogleLongrunning__OperationResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleLongrunning__OperationResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleLongrunning__OperationResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleLongrunning__OperationResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleLongrunning__OperationResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleLongrunning__OperationResponse -> m GoogleLongrunning__OperationResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleLongrunning__OperationResponse -> m GoogleLongrunning__OperationResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleLongrunning__OperationResponse -> m GoogleLongrunning__OperationResponse #

Show GoogleLongrunning__OperationResponse Source # 
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Generic GoogleLongrunning__OperationResponse Source # 
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ToJSON GoogleLongrunning__OperationResponse Source # 
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FromJSON GoogleLongrunning__OperationResponse Source # 
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type Rep GoogleLongrunning__OperationResponse Source # 
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type Rep GoogleLongrunning__OperationResponse = D1 (MetaData "GoogleLongrunning__OperationResponse" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleLongrunning__OperationResponse'" PrefixI True) (S1 (MetaSel (Just "_glorAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text JSONValue))))

googleLongrunning__OperationResponse Source #

Creates a value of GoogleLongrunning__OperationResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

glorAddtional :: Lens' GoogleLongrunning__OperationResponse (HashMap Text JSONValue) Source #

Properties of the object. Contains field 'type with type URL.

GoogleCloudMlV1__ParameterSpecScaleType

data GoogleCloudMlV1__ParameterSpecScaleType Source #

Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`).

Constructors

None

NONE By default, no scaling is applied.

UnitLinearScale

UNIT_LINEAR_SCALE Scales the feasible space to (0, 1) linearly.

UnitLogScale

UNIT_LOG_SCALE Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.

UnitReverseLogScale

UNIT_REVERSE_LOG_SCALE Scales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.

Instances
Enum GoogleCloudMlV1__ParameterSpecScaleType Source # 
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Eq GoogleCloudMlV1__ParameterSpecScaleType Source # 
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Data GoogleCloudMlV1__ParameterSpecScaleType Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ParameterSpecScaleType -> c GoogleCloudMlV1__ParameterSpecScaleType #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ParameterSpecScaleType #

toConstr :: GoogleCloudMlV1__ParameterSpecScaleType -> Constr #

dataTypeOf :: GoogleCloudMlV1__ParameterSpecScaleType -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ParameterSpecScaleType) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ParameterSpecScaleType) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ParameterSpecScaleType -> GoogleCloudMlV1__ParameterSpecScaleType #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ParameterSpecScaleType -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ParameterSpecScaleType -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ParameterSpecScaleType -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ParameterSpecScaleType -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpecScaleType -> m GoogleCloudMlV1__ParameterSpecScaleType #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpecScaleType -> m GoogleCloudMlV1__ParameterSpecScaleType #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpecScaleType -> m GoogleCloudMlV1__ParameterSpecScaleType #

Ord GoogleCloudMlV1__ParameterSpecScaleType Source # 
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Read GoogleCloudMlV1__ParameterSpecScaleType Source # 
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Show GoogleCloudMlV1__ParameterSpecScaleType Source # 
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Generic GoogleCloudMlV1__ParameterSpecScaleType Source # 
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Hashable GoogleCloudMlV1__ParameterSpecScaleType Source # 
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ToJSON GoogleCloudMlV1__ParameterSpecScaleType Source # 
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FromJSON GoogleCloudMlV1__ParameterSpecScaleType Source # 
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FromHttpApiData GoogleCloudMlV1__ParameterSpecScaleType Source # 
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ToHttpApiData GoogleCloudMlV1__ParameterSpecScaleType Source # 
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type Rep GoogleCloudMlV1__ParameterSpecScaleType Source # 
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type Rep GoogleCloudMlV1__ParameterSpecScaleType = D1 (MetaData "GoogleCloudMlV1__ParameterSpecScaleType" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "None" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "UnitLinearScale" PrefixI False) (U1 :: Type -> Type)) :+: (C1 (MetaCons "UnitLogScale" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "UnitReverseLogScale" PrefixI False) (U1 :: Type -> Type)))

GoogleIAMV1__AuditLogConfig

data GoogleIAMV1__AuditLogConfig Source #

Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:foo'gmail.com" ] }, { "log_type": "DATA_WRITE", } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting foo'gmail.com from DATA_READ logging.

See: googleIAMV1__AuditLogConfig smart constructor.

Instances
Eq GoogleIAMV1__AuditLogConfig Source # 
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Data GoogleIAMV1__AuditLogConfig Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleIAMV1__AuditLogConfig -> c GoogleIAMV1__AuditLogConfig #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleIAMV1__AuditLogConfig #

toConstr :: GoogleIAMV1__AuditLogConfig -> Constr #

dataTypeOf :: GoogleIAMV1__AuditLogConfig -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleIAMV1__AuditLogConfig) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleIAMV1__AuditLogConfig) #

gmapT :: (forall b. Data b => b -> b) -> GoogleIAMV1__AuditLogConfig -> GoogleIAMV1__AuditLogConfig #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__AuditLogConfig -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__AuditLogConfig -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleIAMV1__AuditLogConfig -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleIAMV1__AuditLogConfig -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditLogConfig -> m GoogleIAMV1__AuditLogConfig #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditLogConfig -> m GoogleIAMV1__AuditLogConfig #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditLogConfig -> m GoogleIAMV1__AuditLogConfig #

Show GoogleIAMV1__AuditLogConfig Source # 
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Generic GoogleIAMV1__AuditLogConfig Source # 
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Associated Types

type Rep GoogleIAMV1__AuditLogConfig :: Type -> Type #

ToJSON GoogleIAMV1__AuditLogConfig Source # 
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FromJSON GoogleIAMV1__AuditLogConfig Source # 
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type Rep GoogleIAMV1__AuditLogConfig Source # 
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type Rep GoogleIAMV1__AuditLogConfig = D1 (MetaData "GoogleIAMV1__AuditLogConfig" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleIAMV1__AuditLogConfig'" PrefixI True) (S1 (MetaSel (Just "_givalcLogType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleIAMV1__AuditLogConfigLogType)) :*: S1 (MetaSel (Just "_givalcExemptedMembers") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Text]))))

googleIAMV1__AuditLogConfig :: GoogleIAMV1__AuditLogConfig Source #

Creates a value of GoogleIAMV1__AuditLogConfig with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

givalcExemptedMembers :: Lens' GoogleIAMV1__AuditLogConfig [Text] Source #

Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.

GoogleCloudMlV1__VersionFramework

data GoogleCloudMlV1__VersionFramework Source #

Optional. The machine learning framework Cloud ML Engine uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, Cloud ML Engine will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater.

Constructors

FrameworkUnspecified

FRAMEWORK_UNSPECIFIED Unspecified framework. Defaults to TensorFlow.

Tensorflow

TENSORFLOW Tensorflow framework.

ScikitLearn

SCIKIT_LEARN Scikit-learn framework.

Xgboost

XGBOOST XGBoost framework.

Instances
Enum GoogleCloudMlV1__VersionFramework Source # 
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Eq GoogleCloudMlV1__VersionFramework Source # 
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Data GoogleCloudMlV1__VersionFramework Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__VersionFramework -> c GoogleCloudMlV1__VersionFramework #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__VersionFramework #

toConstr :: GoogleCloudMlV1__VersionFramework -> Constr #

dataTypeOf :: GoogleCloudMlV1__VersionFramework -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__VersionFramework) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__VersionFramework) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__VersionFramework -> GoogleCloudMlV1__VersionFramework #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__VersionFramework -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__VersionFramework -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__VersionFramework -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__VersionFramework -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionFramework -> m GoogleCloudMlV1__VersionFramework #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionFramework -> m GoogleCloudMlV1__VersionFramework #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionFramework -> m GoogleCloudMlV1__VersionFramework #

Ord GoogleCloudMlV1__VersionFramework Source # 
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Read GoogleCloudMlV1__VersionFramework Source # 
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Show GoogleCloudMlV1__VersionFramework Source # 
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Generic GoogleCloudMlV1__VersionFramework Source # 
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Associated Types

type Rep GoogleCloudMlV1__VersionFramework :: Type -> Type #

Hashable GoogleCloudMlV1__VersionFramework Source # 
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ToJSON GoogleCloudMlV1__VersionFramework Source # 
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FromJSON GoogleCloudMlV1__VersionFramework Source # 
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FromHttpApiData GoogleCloudMlV1__VersionFramework Source # 
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ToHttpApiData GoogleCloudMlV1__VersionFramework Source # 
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type Rep GoogleCloudMlV1__VersionFramework Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__VersionFramework = D1 (MetaData "GoogleCloudMlV1__VersionFramework" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "FrameworkUnspecified" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Tensorflow" PrefixI False) (U1 :: Type -> Type)) :+: (C1 (MetaCons "ScikitLearn" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Xgboost" PrefixI False) (U1 :: Type -> Type)))

GoogleCloudMlV1__ListModelsResponse

data GoogleCloudMlV1__ListModelsResponse Source #

Response message for the ListModels method.

See: googleCloudMlV1__ListModelsResponse smart constructor.

Instances
Eq GoogleCloudMlV1__ListModelsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__ListModelsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ListModelsResponse -> c GoogleCloudMlV1__ListModelsResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ListModelsResponse #

toConstr :: GoogleCloudMlV1__ListModelsResponse -> Constr #

dataTypeOf :: GoogleCloudMlV1__ListModelsResponse -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ListModelsResponse) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ListModelsResponse) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ListModelsResponse -> GoogleCloudMlV1__ListModelsResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ListModelsResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ListModelsResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ListModelsResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ListModelsResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListModelsResponse -> m GoogleCloudMlV1__ListModelsResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListModelsResponse -> m GoogleCloudMlV1__ListModelsResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListModelsResponse -> m GoogleCloudMlV1__ListModelsResponse #

Show GoogleCloudMlV1__ListModelsResponse Source # 
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Generic GoogleCloudMlV1__ListModelsResponse Source # 
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ToJSON GoogleCloudMlV1__ListModelsResponse Source # 
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FromJSON GoogleCloudMlV1__ListModelsResponse Source # 
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type Rep GoogleCloudMlV1__ListModelsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__ListModelsResponse = D1 (MetaData "GoogleCloudMlV1__ListModelsResponse" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__ListModelsResponse'" PrefixI True) (S1 (MetaSel (Just "_gcmvlmrNextPageToken") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvlmrModels") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleCloudMlV1__Model]))))

googleCloudMlV1__ListModelsResponse :: GoogleCloudMlV1__ListModelsResponse Source #

Creates a value of GoogleCloudMlV1__ListModelsResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvlmrNextPageToken :: Lens' GoogleCloudMlV1__ListModelsResponse (Maybe Text) Source #

Optional. Pass this token as the `page_token` field of the request for a subsequent call.

GoogleCloudMlV1__VersionState

data GoogleCloudMlV1__VersionState Source #

Output only. The state of a version.

Constructors

Unknown

UNKNOWN The version state is unspecified.

Ready

READY The version is ready for prediction.

Creating

CREATING The version is being created. New UpdateVersion and DeleteVersion requests will fail if a version is in the CREATING state.

Failed

FAILED The version failed to be created, possibly cancelled. `error_message` should contain the details of the failure.

Deleting

DELETING The version is being deleted. New UpdateVersion and DeleteVersion requests will fail if a version is in the DELETING state.

Updating

UPDATING The version is being updated. New UpdateVersion and DeleteVersion requests will fail if a version is in the UPDATING state.

Instances
Enum GoogleCloudMlV1__VersionState Source # 
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Eq GoogleCloudMlV1__VersionState Source # 
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Data GoogleCloudMlV1__VersionState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__VersionState -> c GoogleCloudMlV1__VersionState #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__VersionState #

toConstr :: GoogleCloudMlV1__VersionState -> Constr #

dataTypeOf :: GoogleCloudMlV1__VersionState -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__VersionState) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__VersionState) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__VersionState -> GoogleCloudMlV1__VersionState #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__VersionState -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__VersionState -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__VersionState -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__VersionState -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionState -> m GoogleCloudMlV1__VersionState #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionState -> m GoogleCloudMlV1__VersionState #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionState -> m GoogleCloudMlV1__VersionState #

Ord GoogleCloudMlV1__VersionState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Read GoogleCloudMlV1__VersionState Source # 
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Show GoogleCloudMlV1__VersionState Source # 
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Generic GoogleCloudMlV1__VersionState Source # 
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Associated Types

type Rep GoogleCloudMlV1__VersionState :: Type -> Type #

Hashable GoogleCloudMlV1__VersionState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

ToJSON GoogleCloudMlV1__VersionState Source # 
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FromJSON GoogleCloudMlV1__VersionState Source # 
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FromHttpApiData GoogleCloudMlV1__VersionState Source # 
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ToHttpApiData GoogleCloudMlV1__VersionState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__VersionState Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__VersionState = D1 (MetaData "GoogleCloudMlV1__VersionState" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "Unknown" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "Ready" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Creating" PrefixI False) (U1 :: Type -> Type))) :+: (C1 (MetaCons "Failed" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "Deleting" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Updating" PrefixI False) (U1 :: Type -> Type))))

GoogleLongrunning__ListOperationsResponse

data GoogleLongrunning__ListOperationsResponse Source #

The response message for Operations.ListOperations.

See: googleLongrunning__ListOperationsResponse smart constructor.

Instances
Eq GoogleLongrunning__ListOperationsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleLongrunning__ListOperationsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleLongrunning__ListOperationsResponse -> c GoogleLongrunning__ListOperationsResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleLongrunning__ListOperationsResponse #

toConstr :: GoogleLongrunning__ListOperationsResponse -> Constr #

dataTypeOf :: GoogleLongrunning__ListOperationsResponse -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleLongrunning__ListOperationsResponse) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleLongrunning__ListOperationsResponse) #

gmapT :: (forall b. Data b => b -> b) -> GoogleLongrunning__ListOperationsResponse -> GoogleLongrunning__ListOperationsResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleLongrunning__ListOperationsResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleLongrunning__ListOperationsResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleLongrunning__ListOperationsResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleLongrunning__ListOperationsResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleLongrunning__ListOperationsResponse -> m GoogleLongrunning__ListOperationsResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleLongrunning__ListOperationsResponse -> m GoogleLongrunning__ListOperationsResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleLongrunning__ListOperationsResponse -> m GoogleLongrunning__ListOperationsResponse #

Show GoogleLongrunning__ListOperationsResponse Source # 
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Generic GoogleLongrunning__ListOperationsResponse Source # 
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ToJSON GoogleLongrunning__ListOperationsResponse Source # 
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FromJSON GoogleLongrunning__ListOperationsResponse Source # 
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type Rep GoogleLongrunning__ListOperationsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleLongrunning__ListOperationsResponse = D1 (MetaData "GoogleLongrunning__ListOperationsResponse" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleLongrunning__ListOperationsResponse'" PrefixI True) (S1 (MetaSel (Just "_gllorNextPageToken") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gllorOperations") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleLongrunning__Operation]))))

googleLongrunning__ListOperationsResponse :: GoogleLongrunning__ListOperationsResponse Source #

Creates a value of GoogleLongrunning__ListOperationsResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gllorOperations :: Lens' GoogleLongrunning__ListOperationsResponse [GoogleLongrunning__Operation] Source #

A list of operations that matches the specified filter in the request.

GoogleCloudMlV1__AcceleratorConfig

data GoogleCloudMlV1__AcceleratorConfig Source #

Represents a hardware accelerator request config.

See: googleCloudMlV1__AcceleratorConfig smart constructor.

Instances
Eq GoogleCloudMlV1__AcceleratorConfig Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__AcceleratorConfig Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__AcceleratorConfig -> c GoogleCloudMlV1__AcceleratorConfig #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__AcceleratorConfig #

toConstr :: GoogleCloudMlV1__AcceleratorConfig -> Constr #

dataTypeOf :: GoogleCloudMlV1__AcceleratorConfig -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__AcceleratorConfig) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__AcceleratorConfig) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__AcceleratorConfig -> GoogleCloudMlV1__AcceleratorConfig #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__AcceleratorConfig -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__AcceleratorConfig -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__AcceleratorConfig -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__AcceleratorConfig -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AcceleratorConfig -> m GoogleCloudMlV1__AcceleratorConfig #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AcceleratorConfig -> m GoogleCloudMlV1__AcceleratorConfig #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AcceleratorConfig -> m GoogleCloudMlV1__AcceleratorConfig #

Show GoogleCloudMlV1__AcceleratorConfig Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__AcceleratorConfig Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__AcceleratorConfig :: Type -> Type #

ToJSON GoogleCloudMlV1__AcceleratorConfig Source # 
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FromJSON GoogleCloudMlV1__AcceleratorConfig Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__AcceleratorConfig Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__AcceleratorConfig = D1 (MetaData "GoogleCloudMlV1__AcceleratorConfig" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__AcceleratorConfig'" PrefixI True) (S1 (MetaSel (Just "_gcmvacCount") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64))) :*: S1 (MetaSel (Just "_gcmvacType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__AcceleratorConfigType))))

googleCloudMlV1__AcceleratorConfig :: GoogleCloudMlV1__AcceleratorConfig Source #

Creates a value of GoogleCloudMlV1__AcceleratorConfig with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvacCount :: Lens' GoogleCloudMlV1__AcceleratorConfig (Maybe Int64) Source #

The number of accelerators to attach to each machine running the job.

GoogleIAMV1__Policy

data GoogleIAMV1__Policy Source #

Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A `Policy` consists of a list of `bindings`. A `binding` binds a list of `members` to a `role`, where the members can be user accounts, Google groups, Google domains, and service accounts. A `role` is a named list of permissions defined by IAM. **JSON Example** { "bindings": [ { "role": "roles/owner", "members": [ "user:mike'example.com", "group:admins'example.com", "domain:google.com", "serviceAccount:my-other-app'appspot.gserviceaccount.com" ] }, { "role": "roles/viewer", "members": ["user:sean'example.com"] } ] } **YAML Example** bindings: - members: - user:mike'example.com - group:admins'example.com - domain:google.com - serviceAccount:my-other-app'appspot.gserviceaccount.com role: roles/owner - members: - user:sean'example.com role: roles/viewer For a description of IAM and its features, see the IAM developer's guide.

See: googleIAMV1__Policy smart constructor.

Instances
Eq GoogleIAMV1__Policy Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleIAMV1__Policy Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleIAMV1__Policy -> c GoogleIAMV1__Policy #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleIAMV1__Policy #

toConstr :: GoogleIAMV1__Policy -> Constr #

dataTypeOf :: GoogleIAMV1__Policy -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleIAMV1__Policy) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleIAMV1__Policy) #

gmapT :: (forall b. Data b => b -> b) -> GoogleIAMV1__Policy -> GoogleIAMV1__Policy #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__Policy -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__Policy -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleIAMV1__Policy -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleIAMV1__Policy -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleIAMV1__Policy -> m GoogleIAMV1__Policy #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__Policy -> m GoogleIAMV1__Policy #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__Policy -> m GoogleIAMV1__Policy #

Show GoogleIAMV1__Policy Source # 
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Generic GoogleIAMV1__Policy Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleIAMV1__Policy :: Type -> Type #

ToJSON GoogleIAMV1__Policy Source # 
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FromJSON GoogleIAMV1__Policy Source # 
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type Rep GoogleIAMV1__Policy Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleIAMV1__Policy = D1 (MetaData "GoogleIAMV1__Policy" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleIAMV1__Policy'" PrefixI True) ((S1 (MetaSel (Just "_givpAuditConfigs") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleIAMV1__AuditConfig])) :*: S1 (MetaSel (Just "_givpEtag") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bytes))) :*: (S1 (MetaSel (Just "_givpVersion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int32))) :*: S1 (MetaSel (Just "_givpBindings") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleIAMV1__Binding])))))

googleIAMV1__Policy :: GoogleIAMV1__Policy Source #

Creates a value of GoogleIAMV1__Policy with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

givpAuditConfigs :: Lens' GoogleIAMV1__Policy [GoogleIAMV1__AuditConfig] Source #

Specifies cloud audit logging configuration for this policy.

givpEtag :: Lens' GoogleIAMV1__Policy (Maybe ByteString) Source #

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. If no `etag` is provided in the call to `setIamPolicy`, then the existing policy is overwritten blindly.

givpBindings :: Lens' GoogleIAMV1__Policy [GoogleIAMV1__Binding] Source #

Associates a list of `members` to a `role`. `bindings` with no members will result in an error.

GoogleIAMV1__TestIAMPermissionsResponse

data GoogleIAMV1__TestIAMPermissionsResponse Source #

Response message for `TestIamPermissions` method.

See: googleIAMV1__TestIAMPermissionsResponse smart constructor.

Instances
Eq GoogleIAMV1__TestIAMPermissionsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleIAMV1__TestIAMPermissionsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleIAMV1__TestIAMPermissionsResponse -> c GoogleIAMV1__TestIAMPermissionsResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleIAMV1__TestIAMPermissionsResponse #

toConstr :: GoogleIAMV1__TestIAMPermissionsResponse -> Constr #

dataTypeOf :: GoogleIAMV1__TestIAMPermissionsResponse -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleIAMV1__TestIAMPermissionsResponse) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleIAMV1__TestIAMPermissionsResponse) #

gmapT :: (forall b. Data b => b -> b) -> GoogleIAMV1__TestIAMPermissionsResponse -> GoogleIAMV1__TestIAMPermissionsResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__TestIAMPermissionsResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__TestIAMPermissionsResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleIAMV1__TestIAMPermissionsResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleIAMV1__TestIAMPermissionsResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleIAMV1__TestIAMPermissionsResponse -> m GoogleIAMV1__TestIAMPermissionsResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__TestIAMPermissionsResponse -> m GoogleIAMV1__TestIAMPermissionsResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__TestIAMPermissionsResponse -> m GoogleIAMV1__TestIAMPermissionsResponse #

Show GoogleIAMV1__TestIAMPermissionsResponse Source # 
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Generic GoogleIAMV1__TestIAMPermissionsResponse Source # 
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ToJSON GoogleIAMV1__TestIAMPermissionsResponse Source # 
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FromJSON GoogleIAMV1__TestIAMPermissionsResponse Source # 
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type Rep GoogleIAMV1__TestIAMPermissionsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleIAMV1__TestIAMPermissionsResponse = D1 (MetaData "GoogleIAMV1__TestIAMPermissionsResponse" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleIAMV1__TestIAMPermissionsResponse'" PrefixI True) (S1 (MetaSel (Just "_givtiprPermissions") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (Maybe [Text]))))

googleIAMV1__TestIAMPermissionsResponse :: GoogleIAMV1__TestIAMPermissionsResponse Source #

Creates a value of GoogleIAMV1__TestIAMPermissionsResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

givtiprPermissions :: Lens' GoogleIAMV1__TestIAMPermissionsResponse [Text] Source #

A subset of `TestPermissionsRequest.permissions` that the caller is allowed.

GoogleCloudMlV1__HyperparameterSpecAlgorithm

data GoogleCloudMlV1__HyperparameterSpecAlgorithm Source #

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default CloudML Engine hyperparameter tuning algorithm if unspecified.

Constructors

AlgorithmUnspecified

ALGORITHM_UNSPECIFIED The default algorithm used by hyperparameter tuning service.

GridSearch

GRID_SEARCH Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.

RandomSearch

RANDOM_SEARCH Simple random search within the feasible space.

Instances
Enum GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Eq GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Data GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> c GoogleCloudMlV1__HyperparameterSpecAlgorithm #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__HyperparameterSpecAlgorithm #

toConstr :: GoogleCloudMlV1__HyperparameterSpecAlgorithm -> Constr #

dataTypeOf :: GoogleCloudMlV1__HyperparameterSpecAlgorithm -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__HyperparameterSpecAlgorithm) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__HyperparameterSpecAlgorithm) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> GoogleCloudMlV1__HyperparameterSpecAlgorithm #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> m GoogleCloudMlV1__HyperparameterSpecAlgorithm #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> m GoogleCloudMlV1__HyperparameterSpecAlgorithm #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpecAlgorithm -> m GoogleCloudMlV1__HyperparameterSpecAlgorithm #

Ord GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Read GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Show GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Generic GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Hashable GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

ToJSON GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

FromJSON GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

FromHttpApiData GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

ToHttpApiData GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__HyperparameterSpecAlgorithm Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__HyperparameterSpecAlgorithm = D1 (MetaData "GoogleCloudMlV1__HyperparameterSpecAlgorithm" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "AlgorithmUnspecified" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "GridSearch" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "RandomSearch" PrefixI False) (U1 :: Type -> Type)))

GoogleCloudMlV1__ListJobsResponse

data GoogleCloudMlV1__ListJobsResponse Source #

Response message for the ListJobs method.

See: googleCloudMlV1__ListJobsResponse smart constructor.

Instances
Eq GoogleCloudMlV1__ListJobsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__ListJobsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ListJobsResponse -> c GoogleCloudMlV1__ListJobsResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ListJobsResponse #

toConstr :: GoogleCloudMlV1__ListJobsResponse -> Constr #

dataTypeOf :: GoogleCloudMlV1__ListJobsResponse -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ListJobsResponse) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ListJobsResponse) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ListJobsResponse -> GoogleCloudMlV1__ListJobsResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ListJobsResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ListJobsResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ListJobsResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ListJobsResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListJobsResponse -> m GoogleCloudMlV1__ListJobsResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListJobsResponse -> m GoogleCloudMlV1__ListJobsResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListJobsResponse -> m GoogleCloudMlV1__ListJobsResponse #

Show GoogleCloudMlV1__ListJobsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__ListJobsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__ListJobsResponse :: Type -> Type #

ToJSON GoogleCloudMlV1__ListJobsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__ListJobsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__ListJobsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__ListJobsResponse = D1 (MetaData "GoogleCloudMlV1__ListJobsResponse" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__ListJobsResponse'" PrefixI True) (S1 (MetaSel (Just "_gcmvljrNextPageToken") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvljrJobs") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleCloudMlV1__Job]))))

googleCloudMlV1__ListJobsResponse :: GoogleCloudMlV1__ListJobsResponse Source #

Creates a value of GoogleCloudMlV1__ListJobsResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvljrNextPageToken :: Lens' GoogleCloudMlV1__ListJobsResponse (Maybe Text) Source #

Optional. Pass this token as the `page_token` field of the request for a subsequent call.

GoogleCloudMlV1__ListVersionsResponse

data GoogleCloudMlV1__ListVersionsResponse Source #

Response message for the ListVersions method.

See: googleCloudMlV1__ListVersionsResponse smart constructor.

Instances
Eq GoogleCloudMlV1__ListVersionsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__ListVersionsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ListVersionsResponse -> c GoogleCloudMlV1__ListVersionsResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ListVersionsResponse #

toConstr :: GoogleCloudMlV1__ListVersionsResponse -> Constr #

dataTypeOf :: GoogleCloudMlV1__ListVersionsResponse -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ListVersionsResponse) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ListVersionsResponse) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ListVersionsResponse -> GoogleCloudMlV1__ListVersionsResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ListVersionsResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ListVersionsResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ListVersionsResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ListVersionsResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListVersionsResponse -> m GoogleCloudMlV1__ListVersionsResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListVersionsResponse -> m GoogleCloudMlV1__ListVersionsResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListVersionsResponse -> m GoogleCloudMlV1__ListVersionsResponse #

Show GoogleCloudMlV1__ListVersionsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__ListVersionsResponse Source # 
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ToJSON GoogleCloudMlV1__ListVersionsResponse Source # 
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FromJSON GoogleCloudMlV1__ListVersionsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__ListVersionsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__ListVersionsResponse = D1 (MetaData "GoogleCloudMlV1__ListVersionsResponse" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__ListVersionsResponse'" PrefixI True) (S1 (MetaSel (Just "_gcmvlvrNextPageToken") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvlvrVersions") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleCloudMlV1__Version]))))

googleCloudMlV1__ListVersionsResponse :: GoogleCloudMlV1__ListVersionsResponse Source #

Creates a value of GoogleCloudMlV1__ListVersionsResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvlvrNextPageToken :: Lens' GoogleCloudMlV1__ListVersionsResponse (Maybe Text) Source #

Optional. Pass this token as the `page_token` field of the request for a subsequent call.

GoogleType__Expr

data GoogleType__Expr Source #

Represents an expression text. Example: title: "User account presence" description: "Determines whether the request has a user account" expression: "size(request.user) > 0"

See: googleType__Expr smart constructor.

Instances
Eq GoogleType__Expr Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleType__Expr Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleType__Expr -> c GoogleType__Expr #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleType__Expr #

toConstr :: GoogleType__Expr -> Constr #

dataTypeOf :: GoogleType__Expr -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleType__Expr) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleType__Expr) #

gmapT :: (forall b. Data b => b -> b) -> GoogleType__Expr -> GoogleType__Expr #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleType__Expr -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleType__Expr -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleType__Expr -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleType__Expr -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleType__Expr -> m GoogleType__Expr #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleType__Expr -> m GoogleType__Expr #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleType__Expr -> m GoogleType__Expr #

Show GoogleType__Expr Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleType__Expr Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleType__Expr :: Type -> Type #

ToJSON GoogleType__Expr Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleType__Expr Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleType__Expr Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleType__Expr = D1 (MetaData "GoogleType__Expr" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleType__Expr'" PrefixI True) ((S1 (MetaSel (Just "_gteLocation") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gteExpression") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) :*: (S1 (MetaSel (Just "_gteTitle") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gteDescription") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))))

googleType__Expr :: GoogleType__Expr Source #

Creates a value of GoogleType__Expr with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gteLocation :: Lens' GoogleType__Expr (Maybe Text) Source #

An optional string indicating the location of the expression for error reporting, e.g. a file name and a position in the file.

gteExpression :: Lens' GoogleType__Expr (Maybe Text) Source #

Textual representation of an expression in Common Expression Language syntax. The application context of the containing message determines which well-known feature set of CEL is supported.

gteTitle :: Lens' GoogleType__Expr (Maybe Text) Source #

An optional title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.

gteDescription :: Lens' GoogleType__Expr (Maybe Text) Source #

An optional description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.

GoogleCloudMlV1__JobState

data GoogleCloudMlV1__JobState Source #

Output only. The detailed state of a job.

Constructors

GCMVJSStateUnspecified

STATE_UNSPECIFIED The job state is unspecified.

GCMVJSQueued

QUEUED The job has been just created and processing has not yet begun.

GCMVJSPreparing

PREPARING The service is preparing to run the job.

GCMVJSRunning

RUNNING The job is in progress.

GCMVJSSucceeded

SUCCEEDED The job completed successfully.

GCMVJSFailed

FAILED The job failed. `error_message` should contain the details of the failure.

GCMVJSCancelling

CANCELLING The job is being cancelled. `error_message` should describe the reason for the cancellation.

GCMVJSCancelled

CANCELLED The job has been cancelled. `error_message` should describe the reason for the cancellation.

Instances
Enum GoogleCloudMlV1__JobState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Eq GoogleCloudMlV1__JobState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Data GoogleCloudMlV1__JobState Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__JobState -> c GoogleCloudMlV1__JobState #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__JobState #

toConstr :: GoogleCloudMlV1__JobState -> Constr #

dataTypeOf :: GoogleCloudMlV1__JobState -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__JobState) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__JobState) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__JobState -> GoogleCloudMlV1__JobState #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__JobState -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__JobState -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__JobState -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__JobState -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__JobState -> m GoogleCloudMlV1__JobState #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__JobState -> m GoogleCloudMlV1__JobState #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__JobState -> m GoogleCloudMlV1__JobState #

Ord GoogleCloudMlV1__JobState Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Read GoogleCloudMlV1__JobState Source # 
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Show GoogleCloudMlV1__JobState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Generic GoogleCloudMlV1__JobState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Associated Types

type Rep GoogleCloudMlV1__JobState :: Type -> Type #

Hashable GoogleCloudMlV1__JobState Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

ToJSON GoogleCloudMlV1__JobState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

FromJSON GoogleCloudMlV1__JobState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

FromHttpApiData GoogleCloudMlV1__JobState Source # 
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ToHttpApiData GoogleCloudMlV1__JobState Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__JobState Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__JobState = D1 (MetaData "GoogleCloudMlV1__JobState" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (((C1 (MetaCons "GCMVJSStateUnspecified" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "GCMVJSQueued" PrefixI False) (U1 :: Type -> Type)) :+: (C1 (MetaCons "GCMVJSPreparing" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "GCMVJSRunning" PrefixI False) (U1 :: Type -> Type))) :+: ((C1 (MetaCons "GCMVJSSucceeded" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "GCMVJSFailed" PrefixI False) (U1 :: Type -> Type)) :+: (C1 (MetaCons "GCMVJSCancelling" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "GCMVJSCancelled" PrefixI False) (U1 :: Type -> Type))))

GoogleCloudMlV1__PredictionInputDataFormat

data GoogleCloudMlV1__PredictionInputDataFormat Source #

Required. The format of the input data files.

Constructors

DataFormatUnspecified

DATA_FORMAT_UNSPECIFIED Unspecified format.

JSON

JSON Each line of the file is a JSON dictionary representing one record.

Text

TEXT Deprecated. Use JSON instead.

TfRecord

TF_RECORD INPUT ONLY. The source file is a TFRecord file.

TfRecordGzip

TF_RECORD_GZIP INPUT ONLY. The source file is a GZIP-compressed TFRecord file.

CSV

CSV OUTPUT ONLY. Output values will be in comma-separated rows, with keys in a separate file.

Instances
Enum GoogleCloudMlV1__PredictionInputDataFormat Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Eq GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Data GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__PredictionInputDataFormat -> c GoogleCloudMlV1__PredictionInputDataFormat #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__PredictionInputDataFormat #

toConstr :: GoogleCloudMlV1__PredictionInputDataFormat -> Constr #

dataTypeOf :: GoogleCloudMlV1__PredictionInputDataFormat -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__PredictionInputDataFormat) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__PredictionInputDataFormat) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__PredictionInputDataFormat -> GoogleCloudMlV1__PredictionInputDataFormat #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictionInputDataFormat -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictionInputDataFormat -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictionInputDataFormat -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictionInputDataFormat -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInputDataFormat -> m GoogleCloudMlV1__PredictionInputDataFormat #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInputDataFormat -> m GoogleCloudMlV1__PredictionInputDataFormat #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInputDataFormat -> m GoogleCloudMlV1__PredictionInputDataFormat #

Ord GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Read GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Show GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Generic GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Hashable GoogleCloudMlV1__PredictionInputDataFormat Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

ToJSON GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

FromJSON GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

FromHttpApiData GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

ToHttpApiData GoogleCloudMlV1__PredictionInputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__PredictionInputDataFormat Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__PredictionInputDataFormat = D1 (MetaData "GoogleCloudMlV1__PredictionInputDataFormat" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "DataFormatUnspecified" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "JSON" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Text" PrefixI False) (U1 :: Type -> Type))) :+: (C1 (MetaCons "TfRecord" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "TfRecordGzip" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "CSV" PrefixI False) (U1 :: Type -> Type))))

GoogleCloudMlV1__CapabilityType

data GoogleCloudMlV1__CapabilityType Source #

Constructors

TypeUnspecified
TYPE_UNSPECIFIED
Training
TRAINING
BatchPrediction
BATCH_PREDICTION
OnlinePrediction
ONLINE_PREDICTION
Instances
Enum GoogleCloudMlV1__CapabilityType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Eq GoogleCloudMlV1__CapabilityType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Data GoogleCloudMlV1__CapabilityType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__CapabilityType -> c GoogleCloudMlV1__CapabilityType #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__CapabilityType #

toConstr :: GoogleCloudMlV1__CapabilityType -> Constr #

dataTypeOf :: GoogleCloudMlV1__CapabilityType -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__CapabilityType) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__CapabilityType) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__CapabilityType -> GoogleCloudMlV1__CapabilityType #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__CapabilityType -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__CapabilityType -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__CapabilityType -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__CapabilityType -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__CapabilityType -> m GoogleCloudMlV1__CapabilityType #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__CapabilityType -> m GoogleCloudMlV1__CapabilityType #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__CapabilityType -> m GoogleCloudMlV1__CapabilityType #

Ord GoogleCloudMlV1__CapabilityType Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Read GoogleCloudMlV1__CapabilityType Source # 
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Show GoogleCloudMlV1__CapabilityType Source # 
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Generic GoogleCloudMlV1__CapabilityType Source # 
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Associated Types

type Rep GoogleCloudMlV1__CapabilityType :: Type -> Type #

Hashable GoogleCloudMlV1__CapabilityType Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

ToJSON GoogleCloudMlV1__CapabilityType Source # 
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FromJSON GoogleCloudMlV1__CapabilityType Source # 
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FromHttpApiData GoogleCloudMlV1__CapabilityType Source # 
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ToHttpApiData GoogleCloudMlV1__CapabilityType Source # 
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type Rep GoogleCloudMlV1__CapabilityType Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__CapabilityType = D1 (MetaData "GoogleCloudMlV1__CapabilityType" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "TypeUnspecified" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Training" PrefixI False) (U1 :: Type -> Type)) :+: (C1 (MetaCons "BatchPrediction" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "OnlinePrediction" PrefixI False) (U1 :: Type -> Type)))

GoogleCloudMlV1__HyperparameterOutput

data GoogleCloudMlV1__HyperparameterOutput Source #

Represents the result of a single hyperparameter tuning trial from a training job. The TrainingOutput object that is returned on successful completion of a training job with hyperparameter tuning includes a list of HyperparameterOutput objects, one for each successful trial.

See: googleCloudMlV1__HyperparameterOutput smart constructor.

Instances
Eq GoogleCloudMlV1__HyperparameterOutput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__HyperparameterOutput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__HyperparameterOutput -> c GoogleCloudMlV1__HyperparameterOutput #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__HyperparameterOutput #

toConstr :: GoogleCloudMlV1__HyperparameterOutput -> Constr #

dataTypeOf :: GoogleCloudMlV1__HyperparameterOutput -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__HyperparameterOutput) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__HyperparameterOutput) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__HyperparameterOutput -> GoogleCloudMlV1__HyperparameterOutput #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterOutput -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterOutput -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterOutput -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterOutput -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterOutput -> m GoogleCloudMlV1__HyperparameterOutput #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterOutput -> m GoogleCloudMlV1__HyperparameterOutput #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterOutput -> m GoogleCloudMlV1__HyperparameterOutput #

Show GoogleCloudMlV1__HyperparameterOutput Source # 
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Generic GoogleCloudMlV1__HyperparameterOutput Source # 
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ToJSON GoogleCloudMlV1__HyperparameterOutput Source # 
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FromJSON GoogleCloudMlV1__HyperparameterOutput Source # 
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type Rep GoogleCloudMlV1__HyperparameterOutput Source # 
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type Rep GoogleCloudMlV1__HyperparameterOutput = D1 (MetaData "GoogleCloudMlV1__HyperparameterOutput" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__HyperparameterOutput'" PrefixI True) ((S1 (MetaSel (Just "_gcmvhoIsTrialStoppedEarly") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)) :*: S1 (MetaSel (Just "_gcmvhoAllMetrics") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric]))) :*: (S1 (MetaSel (Just "_gcmvhoHyperparameters") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__HyperparameterOutputHyperparameters)) :*: (S1 (MetaSel (Just "_gcmvhoTrialId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvhoFinalMetric") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric))))))

googleCloudMlV1__HyperparameterOutput :: GoogleCloudMlV1__HyperparameterOutput Source #

Creates a value of GoogleCloudMlV1__HyperparameterOutput with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvhoAllMetrics :: Lens' GoogleCloudMlV1__HyperparameterOutput [GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric] Source #

All recorded object metrics for this trial. This field is not currently populated.

GoogleCloudMlV1__GetConfigResponse

data GoogleCloudMlV1__GetConfigResponse Source #

Returns service account information associated with a project.

See: googleCloudMlV1__GetConfigResponse smart constructor.

Instances
Eq GoogleCloudMlV1__GetConfigResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__GetConfigResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__GetConfigResponse -> c GoogleCloudMlV1__GetConfigResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__GetConfigResponse #

toConstr :: GoogleCloudMlV1__GetConfigResponse -> Constr #

dataTypeOf :: GoogleCloudMlV1__GetConfigResponse -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__GetConfigResponse) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__GetConfigResponse) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__GetConfigResponse -> GoogleCloudMlV1__GetConfigResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__GetConfigResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__GetConfigResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__GetConfigResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__GetConfigResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__GetConfigResponse -> m GoogleCloudMlV1__GetConfigResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__GetConfigResponse -> m GoogleCloudMlV1__GetConfigResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__GetConfigResponse -> m GoogleCloudMlV1__GetConfigResponse #

Show GoogleCloudMlV1__GetConfigResponse Source # 
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Generic GoogleCloudMlV1__GetConfigResponse Source # 
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Associated Types

type Rep GoogleCloudMlV1__GetConfigResponse :: Type -> Type #

ToJSON GoogleCloudMlV1__GetConfigResponse Source # 
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FromJSON GoogleCloudMlV1__GetConfigResponse Source # 
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type Rep GoogleCloudMlV1__GetConfigResponse Source # 
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type Rep GoogleCloudMlV1__GetConfigResponse = D1 (MetaData "GoogleCloudMlV1__GetConfigResponse" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__GetConfigResponse'" PrefixI True) (S1 (MetaSel (Just "_gcmvgcrConfig") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__Config)) :*: (S1 (MetaSel (Just "_gcmvgcrServiceAccount") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvgcrServiceAccountProject") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64))))))

googleCloudMlV1__GetConfigResponse :: GoogleCloudMlV1__GetConfigResponse Source #

Creates a value of GoogleCloudMlV1__GetConfigResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvgcrServiceAccount :: Lens' GoogleCloudMlV1__GetConfigResponse (Maybe Text) Source #

The service account Cloud ML uses to access resources in the project.

GoogleCloudMlV1__PredictionInputOutputDataFormat

data GoogleCloudMlV1__PredictionInputOutputDataFormat Source #

Optional. Format of the output data files, defaults to JSON.

Constructors

GCMVPIODFDataFormatUnspecified

DATA_FORMAT_UNSPECIFIED Unspecified format.

GCMVPIODFJSON

JSON Each line of the file is a JSON dictionary representing one record.

GCMVPIODFText

TEXT Deprecated. Use JSON instead.

GCMVPIODFTfRecord

TF_RECORD INPUT ONLY. The source file is a TFRecord file.

GCMVPIODFTfRecordGzip

TF_RECORD_GZIP INPUT ONLY. The source file is a GZIP-compressed TFRecord file.

GCMVPIODFCSV

CSV OUTPUT ONLY. Output values will be in comma-separated rows, with keys in a separate file.

Instances
Enum GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Eq GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Data GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> c GoogleCloudMlV1__PredictionInputOutputDataFormat #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__PredictionInputOutputDataFormat #

toConstr :: GoogleCloudMlV1__PredictionInputOutputDataFormat -> Constr #

dataTypeOf :: GoogleCloudMlV1__PredictionInputOutputDataFormat -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__PredictionInputOutputDataFormat) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__PredictionInputOutputDataFormat) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> GoogleCloudMlV1__PredictionInputOutputDataFormat #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> m GoogleCloudMlV1__PredictionInputOutputDataFormat #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> m GoogleCloudMlV1__PredictionInputOutputDataFormat #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInputOutputDataFormat -> m GoogleCloudMlV1__PredictionInputOutputDataFormat #

Ord GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Read GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Show GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Generic GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Hashable GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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ToJSON GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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FromJSON GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

FromHttpApiData GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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ToHttpApiData GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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type Rep GoogleCloudMlV1__PredictionInputOutputDataFormat Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__PredictionInputOutputDataFormat = D1 (MetaData "GoogleCloudMlV1__PredictionInputOutputDataFormat" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "GCMVPIODFDataFormatUnspecified" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "GCMVPIODFJSON" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "GCMVPIODFText" PrefixI False) (U1 :: Type -> Type))) :+: (C1 (MetaCons "GCMVPIODFTfRecord" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "GCMVPIODFTfRecordGzip" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "GCMVPIODFCSV" PrefixI False) (U1 :: Type -> Type))))

GoogleCloudMlV1__ManualScaling

data GoogleCloudMlV1__ManualScaling Source #

Options for manually scaling a model.

See: googleCloudMlV1__ManualScaling smart constructor.

Instances
Eq GoogleCloudMlV1__ManualScaling Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__ManualScaling Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ManualScaling -> c GoogleCloudMlV1__ManualScaling #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ManualScaling #

toConstr :: GoogleCloudMlV1__ManualScaling -> Constr #

dataTypeOf :: GoogleCloudMlV1__ManualScaling -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ManualScaling) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ManualScaling) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ManualScaling -> GoogleCloudMlV1__ManualScaling #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ManualScaling -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ManualScaling -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ManualScaling -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ManualScaling -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ManualScaling -> m GoogleCloudMlV1__ManualScaling #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ManualScaling -> m GoogleCloudMlV1__ManualScaling #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ManualScaling -> m GoogleCloudMlV1__ManualScaling #

Show GoogleCloudMlV1__ManualScaling Source # 
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Generic GoogleCloudMlV1__ManualScaling Source # 
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type Rep GoogleCloudMlV1__ManualScaling :: Type -> Type #

ToJSON GoogleCloudMlV1__ManualScaling Source # 
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FromJSON GoogleCloudMlV1__ManualScaling Source # 
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type Rep GoogleCloudMlV1__ManualScaling Source # 
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type Rep GoogleCloudMlV1__ManualScaling = D1 (MetaData "GoogleCloudMlV1__ManualScaling" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__ManualScaling'" PrefixI True) (S1 (MetaSel (Just "_gcmvmsNodes") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (Maybe (Textual Int32)))))

googleCloudMlV1__ManualScaling :: GoogleCloudMlV1__ManualScaling Source #

Creates a value of GoogleCloudMlV1__ManualScaling with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvmsNodes :: Lens' GoogleCloudMlV1__ManualScaling (Maybe Int32) Source #

The number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed, so the cost of operating this model will be proportional to `nodes` * number of hours since last billing cycle plus the cost for each prediction performed.

GoogleLongrunning__Operation

data GoogleLongrunning__Operation Source #

This resource represents a long-running operation that is the result of a network API call.

See: googleLongrunning__Operation smart constructor.

Instances
Eq GoogleLongrunning__Operation Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleLongrunning__Operation Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleLongrunning__Operation -> c GoogleLongrunning__Operation #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleLongrunning__Operation #

toConstr :: GoogleLongrunning__Operation -> Constr #

dataTypeOf :: GoogleLongrunning__Operation -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleLongrunning__Operation) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleLongrunning__Operation) #

gmapT :: (forall b. Data b => b -> b) -> GoogleLongrunning__Operation -> GoogleLongrunning__Operation #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleLongrunning__Operation -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleLongrunning__Operation -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleLongrunning__Operation -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleLongrunning__Operation -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleLongrunning__Operation -> m GoogleLongrunning__Operation #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleLongrunning__Operation -> m GoogleLongrunning__Operation #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleLongrunning__Operation -> m GoogleLongrunning__Operation #

Show GoogleLongrunning__Operation Source # 
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Generic GoogleLongrunning__Operation Source # 
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Associated Types

type Rep GoogleLongrunning__Operation :: Type -> Type #

ToJSON GoogleLongrunning__Operation Source # 
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FromJSON GoogleLongrunning__Operation Source # 
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type Rep GoogleLongrunning__Operation Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

googleLongrunning__Operation :: GoogleLongrunning__Operation Source #

Creates a value of GoogleLongrunning__Operation with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gloDone :: Lens' GoogleLongrunning__Operation (Maybe Bool) Source #

If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.

gloError :: Lens' GoogleLongrunning__Operation (Maybe GoogleRpc__Status) Source #

The error result of the operation in case of failure or cancellation.

gloResponse :: Lens' GoogleLongrunning__Operation (Maybe GoogleLongrunning__OperationResponse) Source #

The normal response of the operation in case of success. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.

gloName :: Lens' GoogleLongrunning__Operation (Maybe Text) Source #

The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should have the format of `operations/some/unique/name`.

gloMetadata :: Lens' GoogleLongrunning__Operation (Maybe GoogleLongrunning__OperationMetadata) Source #

Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.

GoogleCloudMlV1__Model

data GoogleCloudMlV1__Model Source #

Represents a machine learning solution. A model can have multiple versions, each of which is a deployed, trained model ready to receive prediction requests. The model itself is just a container.

See: googleCloudMlV1__Model smart constructor.

Instances
Eq GoogleCloudMlV1__Model Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__Model Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__Model -> c GoogleCloudMlV1__Model #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__Model #

toConstr :: GoogleCloudMlV1__Model -> Constr #

dataTypeOf :: GoogleCloudMlV1__Model -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__Model) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__Model) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__Model -> GoogleCloudMlV1__Model #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Model -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Model -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__Model -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__Model -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Model -> m GoogleCloudMlV1__Model #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Model -> m GoogleCloudMlV1__Model #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Model -> m GoogleCloudMlV1__Model #

Show GoogleCloudMlV1__Model Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__Model Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__Model :: Type -> Type #

ToJSON GoogleCloudMlV1__Model Source # 
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FromJSON GoogleCloudMlV1__Model Source # 
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type Rep GoogleCloudMlV1__Model Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__Model = D1 (MetaData "GoogleCloudMlV1__Model" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__Model'" PrefixI True) ((S1 (MetaSel (Just "_gcmvmEtag") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bytes)) :*: (S1 (MetaSel (Just "_gcmvmRegions") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Text])) :*: S1 (MetaSel (Just "_gcmvmDefaultVersion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__Version)))) :*: ((S1 (MetaSel (Just "_gcmvmName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvmLabels") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__ModelLabels))) :*: (S1 (MetaSel (Just "_gcmvmDescription") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvmOnlinePredictionLogging") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool))))))

googleCloudMlV1__Model :: GoogleCloudMlV1__Model Source #

Creates a value of GoogleCloudMlV1__Model with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvmEtag :: Lens' GoogleCloudMlV1__Model (Maybe ByteString) Source #

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.

gcmvmRegions :: Lens' GoogleCloudMlV1__Model [Text] Source #

Optional. The list of regions where the model is going to be deployed. Currently only one region per model is supported. Defaults to 'us-central1' if nothing is set. See the available regions for ML Engine services. Note: * No matter where a model is deployed, it can always be accessed by users from anywhere, both for online and batch prediction. * The region for a batch prediction job is set by the region field when submitting the batch prediction job and does not take its value from this field.

gcmvmDefaultVersion :: Lens' GoogleCloudMlV1__Model (Maybe GoogleCloudMlV1__Version) Source #

Output only. The default version of the model. This version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.methods.versions.setDefault.

gcmvmName :: Lens' GoogleCloudMlV1__Model (Maybe Text) Source #

Required. The name specified for the model when it was created. The model name must be unique within the project it is created in.

gcmvmLabels :: Lens' GoogleCloudMlV1__Model (Maybe GoogleCloudMlV1__ModelLabels) Source #

Optional. One or more labels that you can add, to organize your models. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

gcmvmDescription :: Lens' GoogleCloudMlV1__Model (Maybe Text) Source #

Optional. The description specified for the model when it was created.

gcmvmOnlinePredictionLogging :: Lens' GoogleCloudMlV1__Model (Maybe Bool) Source #

Optional. If true, enables StackDriver Logging for online prediction. Default is false.

GoogleCloudMlV1__Job

data GoogleCloudMlV1__Job Source #

Represents a training or prediction job.

See: googleCloudMlV1__Job smart constructor.

Instances
Eq GoogleCloudMlV1__Job Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__Job Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__Job -> c GoogleCloudMlV1__Job #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__Job #

toConstr :: GoogleCloudMlV1__Job -> Constr #

dataTypeOf :: GoogleCloudMlV1__Job -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__Job) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__Job) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__Job -> GoogleCloudMlV1__Job #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Job -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Job -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__Job -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__Job -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Job -> m GoogleCloudMlV1__Job #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Job -> m GoogleCloudMlV1__Job #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Job -> m GoogleCloudMlV1__Job #

Show GoogleCloudMlV1__Job Source # 
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Generic GoogleCloudMlV1__Job Source # 
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Associated Types

type Rep GoogleCloudMlV1__Job :: Type -> Type #

ToJSON GoogleCloudMlV1__Job Source # 
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FromJSON GoogleCloudMlV1__Job Source # 
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type Rep GoogleCloudMlV1__Job Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__Job = D1 (MetaData "GoogleCloudMlV1__Job" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__Job'" PrefixI True) (((S1 (MetaSel (Just "_gcmvjEtag") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bytes)) :*: (S1 (MetaSel (Just "_gcmvjState") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__JobState)) :*: S1 (MetaSel (Just "_gcmvjTrainingOutput") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__TrainingOutput)))) :*: (S1 (MetaSel (Just "_gcmvjJobId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 (MetaSel (Just "_gcmvjStartTime") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe DateTime')) :*: S1 (MetaSel (Just "_gcmvjPredictionInput") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__PredictionInput))))) :*: ((S1 (MetaSel (Just "_gcmvjEndTime") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe DateTime')) :*: (S1 (MetaSel (Just "_gcmvjPredictionOutput") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__PredictionOutput)) :*: S1 (MetaSel (Just "_gcmvjLabels") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__JobLabels)))) :*: (S1 (MetaSel (Just "_gcmvjErrorMessage") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 (MetaSel (Just "_gcmvjTrainingInput") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__TrainingInput)) :*: S1 (MetaSel (Just "_gcmvjCreateTime") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe DateTime')))))))

gcmvjEtag :: Lens' GoogleCloudMlV1__Job (Maybe ByteString) Source #

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a job from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform job updates in order to avoid race conditions: An `etag` is returned in the response to `GetJob`, and systems are expected to put that etag in the request to `UpdateJob` to ensure that their change will be applied to the same version of the job.

gcmvjState :: Lens' GoogleCloudMlV1__Job (Maybe GoogleCloudMlV1__JobState) Source #

Output only. The detailed state of a job.

gcmvjJobId :: Lens' GoogleCloudMlV1__Job (Maybe Text) Source #

Required. The user-specified id of the job.

gcmvjStartTime :: Lens' GoogleCloudMlV1__Job (Maybe UTCTime) Source #

Output only. When the job processing was started.

gcmvjEndTime :: Lens' GoogleCloudMlV1__Job (Maybe UTCTime) Source #

Output only. When the job processing was completed.

gcmvjLabels :: Lens' GoogleCloudMlV1__Job (Maybe GoogleCloudMlV1__JobLabels) Source #

Optional. One or more labels that you can add, to organize your jobs. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

gcmvjErrorMessage :: Lens' GoogleCloudMlV1__Job (Maybe Text) Source #

Output only. The details of a failure or a cancellation.

gcmvjCreateTime :: Lens' GoogleCloudMlV1__Job (Maybe UTCTime) Source #

Output only. When the job was created.

GoogleCloudMlV1__HyperparameterSpecGoal

data GoogleCloudMlV1__HyperparameterSpecGoal Source #

Required. The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.

Constructors

GoalTypeUnspecified

GOAL_TYPE_UNSPECIFIED Goal Type will default to maximize.

Maximize

MAXIMIZE Maximize the goal metric.

Minimize

MINIMIZE Minimize the goal metric.

Instances
Enum GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Eq GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Data GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__HyperparameterSpecGoal -> c GoogleCloudMlV1__HyperparameterSpecGoal #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__HyperparameterSpecGoal #

toConstr :: GoogleCloudMlV1__HyperparameterSpecGoal -> Constr #

dataTypeOf :: GoogleCloudMlV1__HyperparameterSpecGoal -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__HyperparameterSpecGoal) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__HyperparameterSpecGoal) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__HyperparameterSpecGoal -> GoogleCloudMlV1__HyperparameterSpecGoal #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterSpecGoal -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterSpecGoal -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterSpecGoal -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterSpecGoal -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpecGoal -> m GoogleCloudMlV1__HyperparameterSpecGoal #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpecGoal -> m GoogleCloudMlV1__HyperparameterSpecGoal #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpecGoal -> m GoogleCloudMlV1__HyperparameterSpecGoal #

Ord GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Read GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Show GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Generic GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Hashable GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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ToJSON GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

FromJSON GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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FromHttpApiData GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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ToHttpApiData GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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type Rep GoogleCloudMlV1__HyperparameterSpecGoal Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__HyperparameterSpecGoal = D1 (MetaData "GoogleCloudMlV1__HyperparameterSpecGoal" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoalTypeUnspecified" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "Maximize" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "Minimize" PrefixI False) (U1 :: Type -> Type)))

GoogleCloudMlV1__SetDefaultVersionRequest

data GoogleCloudMlV1__SetDefaultVersionRequest Source #

Request message for the SetDefaultVersion request.

See: googleCloudMlV1__SetDefaultVersionRequest smart constructor.

Instances
Eq GoogleCloudMlV1__SetDefaultVersionRequest Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__SetDefaultVersionRequest Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__SetDefaultVersionRequest -> c GoogleCloudMlV1__SetDefaultVersionRequest #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__SetDefaultVersionRequest #

toConstr :: GoogleCloudMlV1__SetDefaultVersionRequest -> Constr #

dataTypeOf :: GoogleCloudMlV1__SetDefaultVersionRequest -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__SetDefaultVersionRequest) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__SetDefaultVersionRequest) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__SetDefaultVersionRequest -> GoogleCloudMlV1__SetDefaultVersionRequest #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__SetDefaultVersionRequest -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__SetDefaultVersionRequest -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__SetDefaultVersionRequest -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__SetDefaultVersionRequest -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__SetDefaultVersionRequest -> m GoogleCloudMlV1__SetDefaultVersionRequest #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__SetDefaultVersionRequest -> m GoogleCloudMlV1__SetDefaultVersionRequest #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__SetDefaultVersionRequest -> m GoogleCloudMlV1__SetDefaultVersionRequest #

Show GoogleCloudMlV1__SetDefaultVersionRequest Source # 
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Generic GoogleCloudMlV1__SetDefaultVersionRequest Source # 
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ToJSON GoogleCloudMlV1__SetDefaultVersionRequest Source # 
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FromJSON GoogleCloudMlV1__SetDefaultVersionRequest Source # 
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type Rep GoogleCloudMlV1__SetDefaultVersionRequest Source # 
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type Rep GoogleCloudMlV1__SetDefaultVersionRequest = D1 (MetaData "GoogleCloudMlV1__SetDefaultVersionRequest" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__SetDefaultVersionRequest'" PrefixI False) (U1 :: Type -> Type))

GoogleCloudMlV1__ModelLabels

data GoogleCloudMlV1__ModelLabels Source #

Optional. One or more labels that you can add, to organize your models. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

See: googleCloudMlV1__ModelLabels smart constructor.

Instances
Eq GoogleCloudMlV1__ModelLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__ModelLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ModelLabels -> c GoogleCloudMlV1__ModelLabels #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ModelLabels #

toConstr :: GoogleCloudMlV1__ModelLabels -> Constr #

dataTypeOf :: GoogleCloudMlV1__ModelLabels -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ModelLabels) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ModelLabels) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ModelLabels -> GoogleCloudMlV1__ModelLabels #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ModelLabels -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ModelLabels -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ModelLabels -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ModelLabels -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ModelLabels -> m GoogleCloudMlV1__ModelLabels #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ModelLabels -> m GoogleCloudMlV1__ModelLabels #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ModelLabels -> m GoogleCloudMlV1__ModelLabels #

Show GoogleCloudMlV1__ModelLabels Source # 
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Generic GoogleCloudMlV1__ModelLabels Source # 
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Associated Types

type Rep GoogleCloudMlV1__ModelLabels :: Type -> Type #

ToJSON GoogleCloudMlV1__ModelLabels Source # 
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FromJSON GoogleCloudMlV1__ModelLabels Source # 
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type Rep GoogleCloudMlV1__ModelLabels Source # 
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type Rep GoogleCloudMlV1__ModelLabels = D1 (MetaData "GoogleCloudMlV1__ModelLabels" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__ModelLabels'" PrefixI True) (S1 (MetaSel (Just "_gcmvmlAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text Text))))

googleCloudMlV1__ModelLabels Source #

Creates a value of GoogleCloudMlV1__ModelLabels with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

GoogleIAMV1__AuditLogConfigLogType

data GoogleIAMV1__AuditLogConfigLogType Source #

The log type that this config enables.

Constructors

LogTypeUnspecified

LOG_TYPE_UNSPECIFIED Default case. Should never be this.

AdminRead

ADMIN_READ Admin reads. Example: CloudIAM getIamPolicy

DataWrite

DATA_WRITE Data writes. Example: CloudSQL Users create

DataRead

DATA_READ Data reads. Example: CloudSQL Users list

Instances
Enum GoogleIAMV1__AuditLogConfigLogType Source # 
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Eq GoogleIAMV1__AuditLogConfigLogType Source # 
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Data GoogleIAMV1__AuditLogConfigLogType Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleIAMV1__AuditLogConfigLogType -> c GoogleIAMV1__AuditLogConfigLogType #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleIAMV1__AuditLogConfigLogType #

toConstr :: GoogleIAMV1__AuditLogConfigLogType -> Constr #

dataTypeOf :: GoogleIAMV1__AuditLogConfigLogType -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleIAMV1__AuditLogConfigLogType) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleIAMV1__AuditLogConfigLogType) #

gmapT :: (forall b. Data b => b -> b) -> GoogleIAMV1__AuditLogConfigLogType -> GoogleIAMV1__AuditLogConfigLogType #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__AuditLogConfigLogType -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__AuditLogConfigLogType -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleIAMV1__AuditLogConfigLogType -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleIAMV1__AuditLogConfigLogType -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditLogConfigLogType -> m GoogleIAMV1__AuditLogConfigLogType #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditLogConfigLogType -> m GoogleIAMV1__AuditLogConfigLogType #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__AuditLogConfigLogType -> m GoogleIAMV1__AuditLogConfigLogType #

Ord GoogleIAMV1__AuditLogConfigLogType Source # 
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Read GoogleIAMV1__AuditLogConfigLogType Source # 
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Show GoogleIAMV1__AuditLogConfigLogType Source # 
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Generic GoogleIAMV1__AuditLogConfigLogType Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Associated Types

type Rep GoogleIAMV1__AuditLogConfigLogType :: Type -> Type #

Hashable GoogleIAMV1__AuditLogConfigLogType Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

ToJSON GoogleIAMV1__AuditLogConfigLogType Source # 
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FromJSON GoogleIAMV1__AuditLogConfigLogType Source # 
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FromHttpApiData GoogleIAMV1__AuditLogConfigLogType Source # 
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ToHttpApiData GoogleIAMV1__AuditLogConfigLogType Source # 
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type Rep GoogleIAMV1__AuditLogConfigLogType Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleIAMV1__AuditLogConfigLogType = D1 (MetaData "GoogleIAMV1__AuditLogConfigLogType" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "LogTypeUnspecified" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "AdminRead" PrefixI False) (U1 :: Type -> Type)) :+: (C1 (MetaCons "DataWrite" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "DataRead" PrefixI False) (U1 :: Type -> Type)))

GoogleCloudMlV1__JobLabels

data GoogleCloudMlV1__JobLabels Source #

Optional. One or more labels that you can add, to organize your jobs. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

See: googleCloudMlV1__JobLabels smart constructor.

Instances
Eq GoogleCloudMlV1__JobLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__JobLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__JobLabels -> c GoogleCloudMlV1__JobLabels #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__JobLabels #

toConstr :: GoogleCloudMlV1__JobLabels -> Constr #

dataTypeOf :: GoogleCloudMlV1__JobLabels -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__JobLabels) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__JobLabels) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__JobLabels -> GoogleCloudMlV1__JobLabels #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__JobLabels -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__JobLabels -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__JobLabels -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__JobLabels -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__JobLabels -> m GoogleCloudMlV1__JobLabels #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__JobLabels -> m GoogleCloudMlV1__JobLabels #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__JobLabels -> m GoogleCloudMlV1__JobLabels #

Show GoogleCloudMlV1__JobLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__JobLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__JobLabels :: Type -> Type #

ToJSON GoogleCloudMlV1__JobLabels Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__JobLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__JobLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__JobLabels = D1 (MetaData "GoogleCloudMlV1__JobLabels" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__JobLabels'" PrefixI True) (S1 (MetaSel (Just "_gcmvjlAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text Text))))

googleCloudMlV1__JobLabels Source #

Creates a value of GoogleCloudMlV1__JobLabels with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

GoogleRpc__Status

data GoogleRpc__Status Source #

The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. The error model is designed to be: - Simple to use and understand for most users - Flexible enough to meet unexpected needs # Overview The `Status` message contains three pieces of data: error code, error message, and error details. The error code should be an enum value of google.rpc.Code, but it may accept additional error codes if needed. The error message should be a developer-facing English message that helps developers *understand* and *resolve* the error. If a localized user-facing error message is needed, put the localized message in the error details or localize it in the client. The optional error details may contain arbitrary information about the error. There is a predefined set of error detail types in the package `google.rpc` that can be used for common error conditions. # Language mapping The `Status` message is the logical representation of the error model, but it is not necessarily the actual wire format. When the `Status` message is exposed in different client libraries and different wire protocols, it can be mapped differently. For example, it will likely be mapped to some exceptions in Java, but more likely mapped to some error codes in C. # Other uses The error model and the `Status` message can be used in a variety of environments, either with or without APIs, to provide a consistent developer experience across different environments. Example uses of this error model include: - Partial errors. If a service needs to return partial errors to the client, it may embed the `Status` in the normal response to indicate the partial errors. - Workflow errors. A typical workflow has multiple steps. Each step may have a `Status` message for error reporting. - Batch operations. If a client uses batch request and batch response, the `Status` message should be used directly inside batch response, one for each error sub-response. - Asynchronous operations. If an API call embeds asynchronous operation results in its response, the status of those operations should be represented directly using the `Status` message. - Logging. If some API errors are stored in logs, the message `Status` could be used directly after any stripping needed for security/privacy reasons.

See: googleRpc__Status smart constructor.

Instances
Eq GoogleRpc__Status Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleRpc__Status Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleRpc__Status -> c GoogleRpc__Status #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleRpc__Status #

toConstr :: GoogleRpc__Status -> Constr #

dataTypeOf :: GoogleRpc__Status -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleRpc__Status) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleRpc__Status) #

gmapT :: (forall b. Data b => b -> b) -> GoogleRpc__Status -> GoogleRpc__Status #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleRpc__Status -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleRpc__Status -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleRpc__Status -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleRpc__Status -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleRpc__Status -> m GoogleRpc__Status #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleRpc__Status -> m GoogleRpc__Status #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleRpc__Status -> m GoogleRpc__Status #

Show GoogleRpc__Status Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleRpc__Status Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleRpc__Status :: Type -> Type #

ToJSON GoogleRpc__Status Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleRpc__Status Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleRpc__Status Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleRpc__Status = D1 (MetaData "GoogleRpc__Status" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleRpc__Status'" PrefixI True) (S1 (MetaSel (Just "_grsDetails") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleRpc__StatusDetailsItem])) :*: (S1 (MetaSel (Just "_grsCode") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int32))) :*: S1 (MetaSel (Just "_grsMessage") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))))

googleRpc__Status :: GoogleRpc__Status Source #

Creates a value of GoogleRpc__Status with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

grsDetails :: Lens' GoogleRpc__Status [GoogleRpc__StatusDetailsItem] Source #

A list of messages that carry the error details. There is a common set of message types for APIs to use.

grsCode :: Lens' GoogleRpc__Status (Maybe Int32) Source #

The status code, which should be an enum value of google.rpc.Code.

grsMessage :: Lens' GoogleRpc__Status (Maybe Text) Source #

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

GoogleCloudMlV1__Config

data GoogleCloudMlV1__Config Source #

Instances
Eq GoogleCloudMlV1__Config Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__Config Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__Config -> c GoogleCloudMlV1__Config #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__Config #

toConstr :: GoogleCloudMlV1__Config -> Constr #

dataTypeOf :: GoogleCloudMlV1__Config -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__Config) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__Config) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__Config -> GoogleCloudMlV1__Config #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Config -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Config -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__Config -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__Config -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Config -> m GoogleCloudMlV1__Config #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Config -> m GoogleCloudMlV1__Config #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Config -> m GoogleCloudMlV1__Config #

Show GoogleCloudMlV1__Config Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__Config Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__Config :: Type -> Type #

ToJSON GoogleCloudMlV1__Config Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__Config Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__Config Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__Config = D1 (MetaData "GoogleCloudMlV1__Config" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__Config'" PrefixI True) (S1 (MetaSel (Just "_gcmvcTpuServiceAccount") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (Maybe Text))))

googleCloudMlV1__Config :: GoogleCloudMlV1__Config Source #

Creates a value of GoogleCloudMlV1__Config with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvcTpuServiceAccount :: Lens' GoogleCloudMlV1__Config (Maybe Text) Source #

The service account Cloud ML uses to run on TPU node.

GoogleCloudMlV1__HyperparameterSpec

data GoogleCloudMlV1__HyperparameterSpec Source #

Represents a set of hyperparameters to optimize.

See: googleCloudMlV1__HyperparameterSpec smart constructor.

Instances
Eq GoogleCloudMlV1__HyperparameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__HyperparameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__HyperparameterSpec -> c GoogleCloudMlV1__HyperparameterSpec #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__HyperparameterSpec #

toConstr :: GoogleCloudMlV1__HyperparameterSpec -> Constr #

dataTypeOf :: GoogleCloudMlV1__HyperparameterSpec -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__HyperparameterSpec) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__HyperparameterSpec) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__HyperparameterSpec -> GoogleCloudMlV1__HyperparameterSpec #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterSpec -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__HyperparameterSpec -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterSpec -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__HyperparameterSpec -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpec -> m GoogleCloudMlV1__HyperparameterSpec #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpec -> m GoogleCloudMlV1__HyperparameterSpec #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__HyperparameterSpec -> m GoogleCloudMlV1__HyperparameterSpec #

Show GoogleCloudMlV1__HyperparameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__HyperparameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

ToJSON GoogleCloudMlV1__HyperparameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__HyperparameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__HyperparameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__HyperparameterSpec = D1 (MetaData "GoogleCloudMlV1__HyperparameterSpec" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__HyperparameterSpec'" PrefixI True) (((S1 (MetaSel (Just "_gcmvhsResumePreviousJobId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvhsParams") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleCloudMlV1__ParameterSpec]))) :*: (S1 (MetaSel (Just "_gcmvhsAlgorithm") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__HyperparameterSpecAlgorithm)) :*: S1 (MetaSel (Just "_gcmvhsGoal") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__HyperparameterSpecGoal)))) :*: ((S1 (MetaSel (Just "_gcmvhsMaxTrials") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int32))) :*: S1 (MetaSel (Just "_gcmvhsEnableTrialEarlyStopping") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool))) :*: (S1 (MetaSel (Just "_gcmvhsMaxParallelTrials") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int32))) :*: S1 (MetaSel (Just "_gcmvhsHyperparameterMetricTag") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))))))

gcmvhsResumePreviousJobId :: Lens' GoogleCloudMlV1__HyperparameterSpec (Maybe Text) Source #

Optional. The prior hyperparameter tuning job id that users hope to continue with. The job id will be used to find the corresponding vizier study guid and resume the study.

gcmvhsAlgorithm :: Lens' GoogleCloudMlV1__HyperparameterSpec (Maybe GoogleCloudMlV1__HyperparameterSpecAlgorithm) Source #

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default CloudML Engine hyperparameter tuning algorithm if unspecified.

gcmvhsGoal :: Lens' GoogleCloudMlV1__HyperparameterSpec (Maybe GoogleCloudMlV1__HyperparameterSpecGoal) Source #

Required. The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.

gcmvhsMaxTrials :: Lens' GoogleCloudMlV1__HyperparameterSpec (Maybe Int32) Source #

Optional. How many training trials should be attempted to optimize the specified hyperparameters. Defaults to one.

gcmvhsEnableTrialEarlyStopping :: Lens' GoogleCloudMlV1__HyperparameterSpec (Maybe Bool) Source #

Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.

gcmvhsMaxParallelTrials :: Lens' GoogleCloudMlV1__HyperparameterSpec (Maybe Int32) Source #

Optional. The number of training trials to run concurrently. You can reduce the time it takes to perform hyperparameter tuning by adding trials in parallel. However, each trail only benefits from the information gained in completed trials. That means that a trial does not get access to the results of trials running at the same time, which could reduce the quality of the overall optimization. Each trial will use the same scale tier and machine types. Defaults to one.

gcmvhsHyperparameterMetricTag :: Lens' GoogleCloudMlV1__HyperparameterSpec (Maybe Text) Source #

Optional. The Tensorflow summary tag name to use for optimizing trials. For current versions of Tensorflow, this tag name should exactly match what is shown in Tensorboard, including all scopes. For versions of Tensorflow prior to 0.12, this should be only the tag passed to tf.Summary. By default, "training/hptuning/metric" will be used.

GoogleCloudMlV1__AutoScaling

data GoogleCloudMlV1__AutoScaling Source #

Options for automatically scaling a model.

See: googleCloudMlV1__AutoScaling smart constructor.

Instances
Eq GoogleCloudMlV1__AutoScaling Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__AutoScaling Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__AutoScaling -> c GoogleCloudMlV1__AutoScaling #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__AutoScaling #

toConstr :: GoogleCloudMlV1__AutoScaling -> Constr #

dataTypeOf :: GoogleCloudMlV1__AutoScaling -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__AutoScaling) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__AutoScaling) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__AutoScaling -> GoogleCloudMlV1__AutoScaling #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__AutoScaling -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__AutoScaling -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__AutoScaling -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__AutoScaling -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AutoScaling -> m GoogleCloudMlV1__AutoScaling #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AutoScaling -> m GoogleCloudMlV1__AutoScaling #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AutoScaling -> m GoogleCloudMlV1__AutoScaling #

Show GoogleCloudMlV1__AutoScaling Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__AutoScaling Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__AutoScaling :: Type -> Type #

ToJSON GoogleCloudMlV1__AutoScaling Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__AutoScaling Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__AutoScaling Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__AutoScaling = D1 (MetaData "GoogleCloudMlV1__AutoScaling" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__AutoScaling'" PrefixI True) (S1 (MetaSel (Just "_gcmvasMinNodes") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (Maybe (Textual Int32)))))

googleCloudMlV1__AutoScaling :: GoogleCloudMlV1__AutoScaling Source #

Creates a value of GoogleCloudMlV1__AutoScaling with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvasMinNodes :: Lens' GoogleCloudMlV1__AutoScaling (Maybe Int32) Source #

Optional. The minimum number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed. Therefore, the cost of operating this model will be at least `rate` * `min_nodes` * number of hours since last billing cycle, where `rate` is the cost per node-hour as documented in the pricing guide, even if no predictions are performed. There is additional cost for each prediction performed. Unlike manual scaling, if the load gets too heavy for the nodes that are up, the service will automatically add nodes to handle the increased load as well as scale back as traffic drops, always maintaining at least `min_nodes`. You will be charged for the time in which additional nodes are used. If not specified, `min_nodes` defaults to 0, in which case, when traffic to a model stops (and after a cool-down period), nodes will be shut down and no charges will be incurred until traffic to the model resumes. You can set `min_nodes` when creating the model version, and you can also update `min_nodes` for an existing version:

update_body.json:
{
  'autoScaling': {
    'minNodes': 5
  }
}

HTTP request:

PATCH https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes -d './update_body.json

GoogleLongrunning__OperationMetadata

data GoogleLongrunning__OperationMetadata Source #

Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.

See: googleLongrunning__OperationMetadata smart constructor.

Instances
Eq GoogleLongrunning__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleLongrunning__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleLongrunning__OperationMetadata -> c GoogleLongrunning__OperationMetadata #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleLongrunning__OperationMetadata #

toConstr :: GoogleLongrunning__OperationMetadata -> Constr #

dataTypeOf :: GoogleLongrunning__OperationMetadata -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleLongrunning__OperationMetadata) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleLongrunning__OperationMetadata) #

gmapT :: (forall b. Data b => b -> b) -> GoogleLongrunning__OperationMetadata -> GoogleLongrunning__OperationMetadata #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleLongrunning__OperationMetadata -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleLongrunning__OperationMetadata -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleLongrunning__OperationMetadata -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleLongrunning__OperationMetadata -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleLongrunning__OperationMetadata -> m GoogleLongrunning__OperationMetadata #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleLongrunning__OperationMetadata -> m GoogleLongrunning__OperationMetadata #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleLongrunning__OperationMetadata -> m GoogleLongrunning__OperationMetadata #

Show GoogleLongrunning__OperationMetadata Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleLongrunning__OperationMetadata Source # 
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ToJSON GoogleLongrunning__OperationMetadata Source # 
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FromJSON GoogleLongrunning__OperationMetadata Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleLongrunning__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleLongrunning__OperationMetadata = D1 (MetaData "GoogleLongrunning__OperationMetadata" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleLongrunning__OperationMetadata'" PrefixI True) (S1 (MetaSel (Just "_glomAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text JSONValue))))

googleLongrunning__OperationMetadata Source #

Creates a value of GoogleLongrunning__OperationMetadata with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

glomAddtional :: Lens' GoogleLongrunning__OperationMetadata (HashMap Text JSONValue) Source #

Properties of the object. Contains field 'type with type URL.

GoogleCloudMlV1__ParameterSpec

data GoogleCloudMlV1__ParameterSpec Source #

Represents a single hyperparameter to optimize.

See: googleCloudMlV1__ParameterSpec smart constructor.

Instances
Eq GoogleCloudMlV1__ParameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__ParameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ParameterSpec -> c GoogleCloudMlV1__ParameterSpec #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ParameterSpec #

toConstr :: GoogleCloudMlV1__ParameterSpec -> Constr #

dataTypeOf :: GoogleCloudMlV1__ParameterSpec -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ParameterSpec) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ParameterSpec) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ParameterSpec -> GoogleCloudMlV1__ParameterSpec #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ParameterSpec -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ParameterSpec -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ParameterSpec -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ParameterSpec -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpec -> m GoogleCloudMlV1__ParameterSpec #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpec -> m GoogleCloudMlV1__ParameterSpec #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ParameterSpec -> m GoogleCloudMlV1__ParameterSpec #

Show GoogleCloudMlV1__ParameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__ParameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__ParameterSpec :: Type -> Type #

ToJSON GoogleCloudMlV1__ParameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__ParameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__ParameterSpec Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__ParameterSpec = D1 (MetaData "GoogleCloudMlV1__ParameterSpec" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__ParameterSpec'" PrefixI True) ((S1 (MetaSel (Just "_gcmvpsMaxValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Double))) :*: (S1 (MetaSel (Just "_gcmvpsScaleType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__ParameterSpecScaleType)) :*: S1 (MetaSel (Just "_gcmvpsType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__ParameterSpecType)))) :*: ((S1 (MetaSel (Just "_gcmvpsDiscreteValues") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Textual Double])) :*: S1 (MetaSel (Just "_gcmvpsParameterName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) :*: (S1 (MetaSel (Just "_gcmvpsCategoricalValues") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Text])) :*: S1 (MetaSel (Just "_gcmvpsMinValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Double)))))))

googleCloudMlV1__ParameterSpec :: GoogleCloudMlV1__ParameterSpec Source #

Creates a value of GoogleCloudMlV1__ParameterSpec with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvpsMaxValue :: Lens' GoogleCloudMlV1__ParameterSpec (Maybe Double) Source #

Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is `INTEGER`.

gcmvpsScaleType :: Lens' GoogleCloudMlV1__ParameterSpec (Maybe GoogleCloudMlV1__ParameterSpecScaleType) Source #

Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`).

gcmvpsDiscreteValues :: Lens' GoogleCloudMlV1__ParameterSpec [Double] Source #

Required if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

gcmvpsParameterName :: Lens' GoogleCloudMlV1__ParameterSpec (Maybe Text) Source #

Required. The parameter name must be unique amongst all ParameterConfigs in a HyperparameterSpec message. E.g., "learning_rate".

gcmvpsCategoricalValues :: Lens' GoogleCloudMlV1__ParameterSpec [Text] Source #

Required if type is `CATEGORICAL`. The list of possible categories.

gcmvpsMinValue :: Lens' GoogleCloudMlV1__ParameterSpec (Maybe Double) Source #

Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is INTEGER.

Xgafv

data Xgafv Source #

V1 error format.

Constructors

X1

1 v1 error format

X2

2 v2 error format

Instances
Enum Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Eq Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

(==) :: Xgafv -> Xgafv -> Bool #

(/=) :: Xgafv -> Xgafv -> Bool #

Data Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Xgafv -> c Xgafv #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Xgafv #

toConstr :: Xgafv -> Constr #

dataTypeOf :: Xgafv -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Xgafv) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Xgafv) #

gmapT :: (forall b. Data b => b -> b) -> Xgafv -> Xgafv #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Xgafv -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Xgafv -> r #

gmapQ :: (forall d. Data d => d -> u) -> Xgafv -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> Xgafv -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> Xgafv -> m Xgafv #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Xgafv -> m Xgafv #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Xgafv -> m Xgafv #

Ord Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

compare :: Xgafv -> Xgafv -> Ordering #

(<) :: Xgafv -> Xgafv -> Bool #

(<=) :: Xgafv -> Xgafv -> Bool #

(>) :: Xgafv -> Xgafv -> Bool #

(>=) :: Xgafv -> Xgafv -> Bool #

max :: Xgafv -> Xgafv -> Xgafv #

min :: Xgafv -> Xgafv -> Xgafv #

Read Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Show Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

showsPrec :: Int -> Xgafv -> ShowS #

show :: Xgafv -> String #

showList :: [Xgafv] -> ShowS #

Generic Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Associated Types

type Rep Xgafv :: Type -> Type #

Methods

from :: Xgafv -> Rep Xgafv x #

to :: Rep Xgafv x -> Xgafv #

Hashable Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

hashWithSalt :: Int -> Xgafv -> Int #

hash :: Xgafv -> Int #

ToJSON Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

FromJSON Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

FromHttpApiData Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

ToHttpApiData Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

type Rep Xgafv Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

type Rep Xgafv = D1 (MetaData "Xgafv" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "X1" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "X2" PrefixI False) (U1 :: Type -> Type))

GoogleIAMV1__Binding

data GoogleIAMV1__Binding Source #

Associates `members` with a `role`.

See: googleIAMV1__Binding smart constructor.

Instances
Eq GoogleIAMV1__Binding Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleIAMV1__Binding Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleIAMV1__Binding -> c GoogleIAMV1__Binding #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleIAMV1__Binding #

toConstr :: GoogleIAMV1__Binding -> Constr #

dataTypeOf :: GoogleIAMV1__Binding -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleIAMV1__Binding) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleIAMV1__Binding) #

gmapT :: (forall b. Data b => b -> b) -> GoogleIAMV1__Binding -> GoogleIAMV1__Binding #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__Binding -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__Binding -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleIAMV1__Binding -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleIAMV1__Binding -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleIAMV1__Binding -> m GoogleIAMV1__Binding #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__Binding -> m GoogleIAMV1__Binding #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__Binding -> m GoogleIAMV1__Binding #

Show GoogleIAMV1__Binding Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleIAMV1__Binding Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleIAMV1__Binding :: Type -> Type #

ToJSON GoogleIAMV1__Binding Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleIAMV1__Binding Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleIAMV1__Binding Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleIAMV1__Binding = D1 (MetaData "GoogleIAMV1__Binding" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleIAMV1__Binding'" PrefixI True) (S1 (MetaSel (Just "_givbMembers") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Text])) :*: (S1 (MetaSel (Just "_givbRole") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_givbCondition") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleType__Expr)))))

googleIAMV1__Binding :: GoogleIAMV1__Binding Source #

Creates a value of GoogleIAMV1__Binding with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

givbMembers :: Lens' GoogleIAMV1__Binding [Text] Source #

Specifies the identities requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice'gmail.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app'appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins'example.com`. * `domain:{domain}`: A Google Apps domain name that represents all the users of that domain. For example, `google.com` or `example.com`.

givbRole :: Lens' GoogleIAMV1__Binding (Maybe Text) Source #

Role that is assigned to `members`. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.

givbCondition :: Lens' GoogleIAMV1__Binding (Maybe GoogleType__Expr) Source #

Unimplemented. The condition that is associated with this binding. NOTE: an unsatisfied condition will not allow user access via current binding. Different bindings, including their conditions, are examined independently.

GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric

data GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric Source #

An observed value of a metric.

See: googleCloudMlV1_HyperparameterOutput_HyperparameterMetric smart constructor.

Instances
Eq GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> c GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric #

toConstr :: GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> Constr #

dataTypeOf :: GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> m GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> m GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric -> m GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric #

Show GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

ToJSON GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric = D1 (MetaData "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric'" PrefixI True) (S1 (MetaSel (Just "_gcmvhohmTrainingStep") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64))) :*: S1 (MetaSel (Just "_gcmvhohmObjectiveValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Double)))))

GoogleIAMV1__SetIAMPolicyRequest

data GoogleIAMV1__SetIAMPolicyRequest Source #

Request message for `SetIamPolicy` method.

See: googleIAMV1__SetIAMPolicyRequest smart constructor.

Instances
Eq GoogleIAMV1__SetIAMPolicyRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleIAMV1__SetIAMPolicyRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleIAMV1__SetIAMPolicyRequest -> c GoogleIAMV1__SetIAMPolicyRequest #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleIAMV1__SetIAMPolicyRequest #

toConstr :: GoogleIAMV1__SetIAMPolicyRequest -> Constr #

dataTypeOf :: GoogleIAMV1__SetIAMPolicyRequest -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleIAMV1__SetIAMPolicyRequest) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleIAMV1__SetIAMPolicyRequest) #

gmapT :: (forall b. Data b => b -> b) -> GoogleIAMV1__SetIAMPolicyRequest -> GoogleIAMV1__SetIAMPolicyRequest #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__SetIAMPolicyRequest -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__SetIAMPolicyRequest -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleIAMV1__SetIAMPolicyRequest -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleIAMV1__SetIAMPolicyRequest -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleIAMV1__SetIAMPolicyRequest -> m GoogleIAMV1__SetIAMPolicyRequest #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__SetIAMPolicyRequest -> m GoogleIAMV1__SetIAMPolicyRequest #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__SetIAMPolicyRequest -> m GoogleIAMV1__SetIAMPolicyRequest #

Show GoogleIAMV1__SetIAMPolicyRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleIAMV1__SetIAMPolicyRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleIAMV1__SetIAMPolicyRequest :: Type -> Type #

ToJSON GoogleIAMV1__SetIAMPolicyRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleIAMV1__SetIAMPolicyRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleIAMV1__SetIAMPolicyRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleIAMV1__SetIAMPolicyRequest = D1 (MetaData "GoogleIAMV1__SetIAMPolicyRequest" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleIAMV1__SetIAMPolicyRequest'" PrefixI True) (S1 (MetaSel (Just "_givsiprUpdateMask") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GFieldMask)) :*: S1 (MetaSel (Just "_givsiprPolicy") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleIAMV1__Policy))))

googleIAMV1__SetIAMPolicyRequest :: GoogleIAMV1__SetIAMPolicyRequest Source #

Creates a value of GoogleIAMV1__SetIAMPolicyRequest with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

givsiprUpdateMask :: Lens' GoogleIAMV1__SetIAMPolicyRequest (Maybe GFieldMask) Source #

OPTIONAL: A FieldMask specifying which fields of the policy to modify. Only the fields in the mask will be modified. If no mask is provided, the following default mask is used: paths: "bindings, etag" This field is only used by Cloud IAM.

givsiprPolicy :: Lens' GoogleIAMV1__SetIAMPolicyRequest (Maybe GoogleIAMV1__Policy) Source #

REQUIRED: The complete policy to be applied to the `resource`. The size of the policy is limited to a few 10s of KB. An empty policy is a valid policy but certain Cloud Platform services (such as Projects) might reject them.

GoogleCloudMlV1__PredictionInput

data GoogleCloudMlV1__PredictionInput Source #

Represents input parameters for a prediction job. Next field: 20

See: googleCloudMlV1__PredictionInput smart constructor.

Instances
Eq GoogleCloudMlV1__PredictionInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__PredictionInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__PredictionInput -> c GoogleCloudMlV1__PredictionInput #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__PredictionInput #

toConstr :: GoogleCloudMlV1__PredictionInput -> Constr #

dataTypeOf :: GoogleCloudMlV1__PredictionInput -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__PredictionInput) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__PredictionInput) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__PredictionInput -> GoogleCloudMlV1__PredictionInput #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictionInput -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__PredictionInput -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictionInput -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__PredictionInput -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInput -> m GoogleCloudMlV1__PredictionInput #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInput -> m GoogleCloudMlV1__PredictionInput #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__PredictionInput -> m GoogleCloudMlV1__PredictionInput #

Show GoogleCloudMlV1__PredictionInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__PredictionInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__PredictionInput :: Type -> Type #

ToJSON GoogleCloudMlV1__PredictionInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__PredictionInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__PredictionInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__PredictionInput = D1 (MetaData "GoogleCloudMlV1__PredictionInput" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__PredictionInput'" PrefixI True) (((S1 (MetaSel (Just "_gcmvpiVersionName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 (MetaSel (Just "_gcmvpiModelName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvpiDataFormat") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__PredictionInputDataFormat)))) :*: (S1 (MetaSel (Just "_gcmvpiURI") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 (MetaSel (Just "_gcmvpiRuntimeVersion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvpiBatchSize") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64)))))) :*: ((S1 (MetaSel (Just "_gcmvpiMaxWorkerCount") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64))) :*: (S1 (MetaSel (Just "_gcmvpiOutputDataFormat") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__PredictionInputOutputDataFormat)) :*: S1 (MetaSel (Just "_gcmvpiAccelerator") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__AcceleratorConfig)))) :*: ((S1 (MetaSel (Just "_gcmvpiOutputPath") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvpiRegion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) :*: (S1 (MetaSel (Just "_gcmvpiInputPaths") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Text])) :*: S1 (MetaSel (Just "_gcmvpiSignatureName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))))))

gcmvpiVersionName :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Text) Source #

Use this field if you want to specify a version of the model to use. The string is formatted the same way as `model_version`, with the addition of the version information: `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"`

gcmvpiModelName :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Text) Source #

Use this field if you want to use the default version for the specified model. The string must use the following format: `"projects/YOUR_PROJECT/models/YOUR_MODEL"`

gcmvpiURI :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Text) Source #

Use this field if you want to specify a Google Cloud Storage path for the model to use.

gcmvpiRuntimeVersion :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Text) Source #

Optional. The Cloud ML Engine runtime version to use for this batch prediction. If not set, Cloud ML Engine will pick the runtime version used during the CreateVersion request for this model version, or choose the latest stable version when model version information is not available such as when the model is specified by uri.

gcmvpiBatchSize :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Int64) Source #

Optional. Number of records per batch, defaults to 64. The service will buffer batch_size number of records in memory before invoking one Tensorflow prediction call internally. So take the record size and memory available into consideration when setting this parameter.

gcmvpiMaxWorkerCount :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Int64) Source #

Optional. The maximum number of workers to be used for parallel processing. Defaults to 10 if not specified.

gcmvpiAccelerator :: Lens' GoogleCloudMlV1__PredictionInput (Maybe GoogleCloudMlV1__AcceleratorConfig) Source #

Optional. The type and number of accelerators to be attached to each machine running the job.

gcmvpiOutputPath :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Text) Source #

Required. The output Google Cloud Storage location.

gcmvpiRegion :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Text) Source #

Required. The Google Compute Engine region to run the prediction job in. See the available regions for ML Engine services.

gcmvpiInputPaths :: Lens' GoogleCloudMlV1__PredictionInput [Text] Source #

Required. The Google Cloud Storage location of the input data files. May contain wildcards.

gcmvpiSignatureName :: Lens' GoogleCloudMlV1__PredictionInput (Maybe Text) Source #

Optional. The name of the signature defined in the SavedModel to use for this job. Please refer to SavedModel for information about how to use signatures. Defaults to DEFAULT_SERVING_SIGNATURE_DEF_KEY , which is "serving_default".

GoogleCloudMlV1__TrainingInput

data GoogleCloudMlV1__TrainingInput Source #

Represents input parameters for a training job. When using the gcloud command to submit your training job, you can specify the input parameters as command-line arguments and/or in a YAML configuration file referenced from the --config command-line argument. For details, see the guide to submitting a training job.

See: googleCloudMlV1__TrainingInput smart constructor.

Instances
Eq GoogleCloudMlV1__TrainingInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__TrainingInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__TrainingInput -> c GoogleCloudMlV1__TrainingInput #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__TrainingInput #

toConstr :: GoogleCloudMlV1__TrainingInput -> Constr #

dataTypeOf :: GoogleCloudMlV1__TrainingInput -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__TrainingInput) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__TrainingInput) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__TrainingInput -> GoogleCloudMlV1__TrainingInput #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__TrainingInput -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__TrainingInput -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__TrainingInput -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__TrainingInput -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingInput -> m GoogleCloudMlV1__TrainingInput #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingInput -> m GoogleCloudMlV1__TrainingInput #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingInput -> m GoogleCloudMlV1__TrainingInput #

Show GoogleCloudMlV1__TrainingInput Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__TrainingInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__TrainingInput :: Type -> Type #

ToJSON GoogleCloudMlV1__TrainingInput Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__TrainingInput Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__TrainingInput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__TrainingInput = D1 (MetaData "GoogleCloudMlV1__TrainingInput" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__TrainingInput'" PrefixI True) (((S1 (MetaSel (Just "_gcmvtiMasterType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 (MetaSel (Just "_gcmvtiParameterServerCount") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64))) :*: S1 (MetaSel (Just "_gcmvtiArgs") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Text])))) :*: ((S1 (MetaSel (Just "_gcmvtiWorkerCount") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64))) :*: S1 (MetaSel (Just "_gcmvtiJobDir") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) :*: (S1 (MetaSel (Just "_gcmvtiPythonVersion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvtiRuntimeVersion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))))) :*: ((S1 (MetaSel (Just "_gcmvtiWorkerType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 (MetaSel (Just "_gcmvtiPythonModule") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvtiParameterServerType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))) :*: ((S1 (MetaSel (Just "_gcmvtiHyperparameters") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__HyperparameterSpec)) :*: S1 (MetaSel (Just "_gcmvtiPackageURIs") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Text]))) :*: (S1 (MetaSel (Just "_gcmvtiScaleTier") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__TrainingInputScaleTier)) :*: S1 (MetaSel (Just "_gcmvtiRegion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))))))

gcmvtiMasterType :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Text) Source #

Optional. Specifies the type of virtual machine to use for your training job's master worker. The following types are supported:

standard
A basic machine configuration suitable for training simple models with small to moderate datasets.
large_model
A machine with a lot of memory, specially suited for parameter servers when your model is large (having many hidden layers or layers with very large numbers of nodes).
complex_model_s
A machine suitable for the master and workers of the cluster when your model requires more computation than the standard machine can handle satisfactorily.
complex_model_m
A machine with roughly twice the number of cores and roughly double the memory of complex_model_s.
complex_model_l
A machine with roughly twice the number of cores and roughly double the memory of complex_model_m.
standard_gpu
A machine equivalent to standard that also includes a single NVIDIA Tesla K80 GPU. See more about using GPUs to train your model.
complex_model_m_gpu
A machine equivalent to complex_model_m that also includes four NVIDIA Tesla K80 GPUs.
complex_model_l_gpu
A machine equivalent to complex_model_l that also includes eight NVIDIA Tesla K80 GPUs.
standard_p100
A machine equivalent to standard that also includes a single NVIDIA Tesla P100 GPU.
complex_model_m_p100
A machine equivalent to complex_model_m that also includes four NVIDIA Tesla P100 GPUs.
standard_v100
A machine equivalent to standard that also includes a single NVIDIA Tesla V100 GPU. The availability of these GPUs is in the Beta launch stage.
large_model_v100
A machine equivalent to large_model that also includes a single NVIDIA Tesla V100 GPU. The availability of these GPUs is in the Beta launch stage.
complex_model_m_v100
A machine equivalent to complex_model_m that also includes four NVIDIA Tesla V100 GPUs. The availability of these GPUs is in the Beta launch stage.
complex_model_l_v100
A machine equivalent to complex_model_l that also includes eight NVIDIA Tesla V100 GPUs. The availability of these GPUs is in the Beta launch stage.
cloud_tpu
A TPU VM including one Cloud TPU. See more about using TPUs to train your model.

You must set this value when `scaleTier` is set to `CUSTOM`.

gcmvtiParameterServerCount :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Int64) Source #

Optional. The number of parameter server replicas to use for the training job. Each replica in the cluster will be of the type specified in `parameter_server_type`. This value can only be used when `scale_tier` is set to `CUSTOM`.If you set this value, you must also set `parameter_server_type`.

gcmvtiArgs :: Lens' GoogleCloudMlV1__TrainingInput [Text] Source #

Optional. Command line arguments to pass to the program.

gcmvtiWorkerCount :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Int64) Source #

Optional. The number of worker replicas to use for the training job. Each replica in the cluster will be of the type specified in `worker_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `worker_type`.

gcmvtiJobDir :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Text) Source #

Optional. A Google Cloud Storage path in which to store training outputs and other data needed for training. This path is passed to your TensorFlow program as the '--job-dir' command-line argument. The benefit of specifying this field is that Cloud ML validates the path for use in training.

gcmvtiPythonVersion :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Text) Source #

Optional. The version of Python used in training. If not set, the default version is '2.7'. Python '3.5' is available when `runtime_version` is set to '1.4' and above. Python '2.7' works with all supported runtime versions.

gcmvtiRuntimeVersion :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Text) Source #

Optional. The Cloud ML Engine runtime version to use for training. If not set, Cloud ML Engine uses the default stable version, 1.0. For more information, see the runtime version list and how to manage runtime versions.

gcmvtiWorkerType :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Text) Source #

Optional. Specifies the type of virtual machine to use for your training job's worker nodes. The supported values are the same as those described in the entry for `masterType`. This value must be present when `scaleTier` is set to `CUSTOM` and `workerCount` is greater than zero.

gcmvtiPythonModule :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Text) Source #

Required. The Python module name to run after installing the packages.

gcmvtiParameterServerType :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Text) Source #

Optional. Specifies the type of virtual machine to use for your training job's parameter server. The supported values are the same as those described in the entry for `master_type`. This value must be present when `scaleTier` is set to `CUSTOM` and `parameter_server_count` is greater than zero.

gcmvtiPackageURIs :: Lens' GoogleCloudMlV1__TrainingInput [Text] Source #

Required. The Google Cloud Storage location of the packages with the training program and any additional dependencies. The maximum number of package URIs is 100.

gcmvtiScaleTier :: Lens' GoogleCloudMlV1__TrainingInput (Maybe GoogleCloudMlV1__TrainingInputScaleTier) Source #

Required. Specifies the machine types, the number of replicas for workers and parameter servers.

gcmvtiRegion :: Lens' GoogleCloudMlV1__TrainingInput (Maybe Text) Source #

Required. The Google Compute Engine region to run the training job in. See the available regions for ML Engine services.

GoogleRpc__StatusDetailsItem

data GoogleRpc__StatusDetailsItem Source #

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Eq GoogleRpc__StatusDetailsItem Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Data GoogleRpc__StatusDetailsItem Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleRpc__StatusDetailsItem -> c GoogleRpc__StatusDetailsItem #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleRpc__StatusDetailsItem #

toConstr :: GoogleRpc__StatusDetailsItem -> Constr #

dataTypeOf :: GoogleRpc__StatusDetailsItem -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleRpc__StatusDetailsItem) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleRpc__StatusDetailsItem) #

gmapT :: (forall b. Data b => b -> b) -> GoogleRpc__StatusDetailsItem -> GoogleRpc__StatusDetailsItem #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleRpc__StatusDetailsItem -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleRpc__StatusDetailsItem -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleRpc__StatusDetailsItem -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleRpc__StatusDetailsItem -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleRpc__StatusDetailsItem -> m GoogleRpc__StatusDetailsItem #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleRpc__StatusDetailsItem -> m GoogleRpc__StatusDetailsItem #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleRpc__StatusDetailsItem -> m GoogleRpc__StatusDetailsItem #

Show GoogleRpc__StatusDetailsItem Source # 
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Generic GoogleRpc__StatusDetailsItem Source # 
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type Rep GoogleRpc__StatusDetailsItem :: Type -> Type #

ToJSON GoogleRpc__StatusDetailsItem Source # 
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FromJSON GoogleRpc__StatusDetailsItem Source # 
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type Rep GoogleRpc__StatusDetailsItem Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleRpc__StatusDetailsItem = D1 (MetaData "GoogleRpc__StatusDetailsItem" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleRpc__StatusDetailsItem'" PrefixI True) (S1 (MetaSel (Just "_grsdiAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text JSONValue))))

googleRpc__StatusDetailsItem Source #

Creates a value of GoogleRpc__StatusDetailsItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

grsdiAddtional :: Lens' GoogleRpc__StatusDetailsItem (HashMap Text JSONValue) Source #

Properties of the object. Contains field 'type with type URL.

GoogleCloudMlV1__OperationMetadataOperationType

data GoogleCloudMlV1__OperationMetadataOperationType Source #

The operation type.

Constructors

OperationTypeUnspecified

OPERATION_TYPE_UNSPECIFIED Unspecified operation type.

CreateVersion

CREATE_VERSION An operation to create a new version.

DeleteVersion

DELETE_VERSION An operation to delete an existing version.

DeleteModel

DELETE_MODEL An operation to delete an existing model.

UpdateModel

UPDATE_MODEL An operation to update an existing model.

UpdateVersion

UPDATE_VERSION An operation to update an existing version.

UpdateConfig

UPDATE_CONFIG An operation to update project configuration.

Instances
Enum GoogleCloudMlV1__OperationMetadataOperationType Source # 
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Defined in Network.Google.MachineLearning.Types.Sum

Eq GoogleCloudMlV1__OperationMetadataOperationType Source # 
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Data GoogleCloudMlV1__OperationMetadataOperationType Source # 
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gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__OperationMetadataOperationType -> c GoogleCloudMlV1__OperationMetadataOperationType #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__OperationMetadataOperationType #

toConstr :: GoogleCloudMlV1__OperationMetadataOperationType -> Constr #

dataTypeOf :: GoogleCloudMlV1__OperationMetadataOperationType -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__OperationMetadataOperationType) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__OperationMetadataOperationType) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__OperationMetadataOperationType -> GoogleCloudMlV1__OperationMetadataOperationType #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__OperationMetadataOperationType -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__OperationMetadataOperationType -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__OperationMetadataOperationType -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__OperationMetadataOperationType -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadataOperationType -> m GoogleCloudMlV1__OperationMetadataOperationType #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadataOperationType -> m GoogleCloudMlV1__OperationMetadataOperationType #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadataOperationType -> m GoogleCloudMlV1__OperationMetadataOperationType #

Ord GoogleCloudMlV1__OperationMetadataOperationType Source # 
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Read GoogleCloudMlV1__OperationMetadataOperationType Source # 
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Show GoogleCloudMlV1__OperationMetadataOperationType Source # 
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Generic GoogleCloudMlV1__OperationMetadataOperationType Source # 
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Hashable GoogleCloudMlV1__OperationMetadataOperationType Source # 
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ToJSON GoogleCloudMlV1__OperationMetadataOperationType Source # 
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FromJSON GoogleCloudMlV1__OperationMetadataOperationType Source # 
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FromHttpApiData GoogleCloudMlV1__OperationMetadataOperationType Source # 
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ToHttpApiData GoogleCloudMlV1__OperationMetadataOperationType Source # 
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type Rep GoogleCloudMlV1__OperationMetadataOperationType Source # 
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type Rep GoogleCloudMlV1__OperationMetadataOperationType = D1 (MetaData "GoogleCloudMlV1__OperationMetadataOperationType" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "OperationTypeUnspecified" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "CreateVersion" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "DeleteVersion" PrefixI False) (U1 :: Type -> Type))) :+: ((C1 (MetaCons "DeleteModel" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "UpdateModel" PrefixI False) (U1 :: Type -> Type)) :+: (C1 (MetaCons "UpdateVersion" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "UpdateConfig" PrefixI False) (U1 :: Type -> Type))))

GoogleProtobuf__Empty

data GoogleProtobuf__Empty Source #

A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`.

See: googleProtobuf__Empty smart constructor.

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Eq GoogleProtobuf__Empty Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Data GoogleProtobuf__Empty Source # 
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gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleProtobuf__Empty -> c GoogleProtobuf__Empty #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleProtobuf__Empty #

toConstr :: GoogleProtobuf__Empty -> Constr #

dataTypeOf :: GoogleProtobuf__Empty -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleProtobuf__Empty) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleProtobuf__Empty) #

gmapT :: (forall b. Data b => b -> b) -> GoogleProtobuf__Empty -> GoogleProtobuf__Empty #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleProtobuf__Empty -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleProtobuf__Empty -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleProtobuf__Empty -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleProtobuf__Empty -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleProtobuf__Empty -> m GoogleProtobuf__Empty #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleProtobuf__Empty -> m GoogleProtobuf__Empty #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleProtobuf__Empty -> m GoogleProtobuf__Empty #

Show GoogleProtobuf__Empty Source # 
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Generic GoogleProtobuf__Empty Source # 
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type Rep GoogleProtobuf__Empty :: Type -> Type #

ToJSON GoogleProtobuf__Empty Source # 
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FromJSON GoogleProtobuf__Empty Source # 
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type Rep GoogleProtobuf__Empty Source # 
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type Rep GoogleProtobuf__Empty = D1 (MetaData "GoogleProtobuf__Empty" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleProtobuf__Empty'" PrefixI False) (U1 :: Type -> Type))

googleProtobuf__Empty :: GoogleProtobuf__Empty Source #

Creates a value of GoogleProtobuf__Empty with the minimum fields required to make a request.

GoogleCloudMlV1__Location

data GoogleCloudMlV1__Location Source #

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Eq GoogleCloudMlV1__Location Source # 
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Data GoogleCloudMlV1__Location Source # 
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Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__Location -> c GoogleCloudMlV1__Location #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__Location #

toConstr :: GoogleCloudMlV1__Location -> Constr #

dataTypeOf :: GoogleCloudMlV1__Location -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__Location) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__Location) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__Location -> GoogleCloudMlV1__Location #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Location -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Location -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__Location -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__Location -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Location -> m GoogleCloudMlV1__Location #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Location -> m GoogleCloudMlV1__Location #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Location -> m GoogleCloudMlV1__Location #

Show GoogleCloudMlV1__Location Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__Location Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__Location :: Type -> Type #

ToJSON GoogleCloudMlV1__Location Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__Location Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__Location Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__Location = D1 (MetaData "GoogleCloudMlV1__Location" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__Location'" PrefixI True) (S1 (MetaSel (Just "_gcmvlName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvlCapabilities") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleCloudMlV1__Capability]))))

googleCloudMlV1__Location :: GoogleCloudMlV1__Location Source #

Creates a value of GoogleCloudMlV1__Location with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

GoogleCloudMlV1__OperationMetadataLabels

data GoogleCloudMlV1__OperationMetadataLabels Source #

The user labels, inherited from the model or the model version being operated on.

See: googleCloudMlV1__OperationMetadataLabels smart constructor.

Instances
Eq GoogleCloudMlV1__OperationMetadataLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__OperationMetadataLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__OperationMetadataLabels -> c GoogleCloudMlV1__OperationMetadataLabels #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__OperationMetadataLabels #

toConstr :: GoogleCloudMlV1__OperationMetadataLabels -> Constr #

dataTypeOf :: GoogleCloudMlV1__OperationMetadataLabels -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__OperationMetadataLabels) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__OperationMetadataLabels) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__OperationMetadataLabels -> GoogleCloudMlV1__OperationMetadataLabels #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__OperationMetadataLabels -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__OperationMetadataLabels -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__OperationMetadataLabels -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__OperationMetadataLabels -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadataLabels -> m GoogleCloudMlV1__OperationMetadataLabels #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadataLabels -> m GoogleCloudMlV1__OperationMetadataLabels #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadataLabels -> m GoogleCloudMlV1__OperationMetadataLabels #

Show GoogleCloudMlV1__OperationMetadataLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__OperationMetadataLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

ToJSON GoogleCloudMlV1__OperationMetadataLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__OperationMetadataLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__OperationMetadataLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__OperationMetadataLabels = D1 (MetaData "GoogleCloudMlV1__OperationMetadataLabels" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__OperationMetadataLabels'" PrefixI True) (S1 (MetaSel (Just "_gcmvomlAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text Text))))

googleCloudMlV1__OperationMetadataLabels Source #

Creates a value of GoogleCloudMlV1__OperationMetadataLabels with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

GoogleCloudMlV1__AcceleratorConfigType

data GoogleCloudMlV1__AcceleratorConfigType Source #

The available types of accelerators.

Constructors

AcceleratorTypeUnspecified

ACCELERATOR_TYPE_UNSPECIFIED Unspecified accelerator type. Default to no GPU.

NvidiaTeslaK80

NVIDIA_TESLA_K80 Nvidia Tesla K80 GPU.

NvidiaTeslaP100

NVIDIA_TESLA_P100 Nvidia Tesla P100 GPU.

NvidiaTeslaV100

NVIDIA_TESLA_V100 Nvidia Tesla V100 GPU.

NvidiaTeslaP4

NVIDIA_TESLA_P4 Nvidia Tesla P4 GPU.

NvidiaTeslaT4

NVIDIA_TESLA_T4 Nvidia Tesla T4 GPU.

Instances
Enum GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Eq GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Data GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__AcceleratorConfigType -> c GoogleCloudMlV1__AcceleratorConfigType #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__AcceleratorConfigType #

toConstr :: GoogleCloudMlV1__AcceleratorConfigType -> Constr #

dataTypeOf :: GoogleCloudMlV1__AcceleratorConfigType -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__AcceleratorConfigType) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__AcceleratorConfigType) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__AcceleratorConfigType -> GoogleCloudMlV1__AcceleratorConfigType #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__AcceleratorConfigType -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__AcceleratorConfigType -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__AcceleratorConfigType -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__AcceleratorConfigType -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AcceleratorConfigType -> m GoogleCloudMlV1__AcceleratorConfigType #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AcceleratorConfigType -> m GoogleCloudMlV1__AcceleratorConfigType #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__AcceleratorConfigType -> m GoogleCloudMlV1__AcceleratorConfigType #

Ord GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Read GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Show GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Generic GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

Hashable GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

ToJSON GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

FromJSON GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

FromHttpApiData GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

ToHttpApiData GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__AcceleratorConfigType Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Sum

type Rep GoogleCloudMlV1__AcceleratorConfigType = D1 (MetaData "GoogleCloudMlV1__AcceleratorConfigType" "Network.Google.MachineLearning.Types.Sum" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) ((C1 (MetaCons "AcceleratorTypeUnspecified" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "NvidiaTeslaK80" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "NvidiaTeslaP100" PrefixI False) (U1 :: Type -> Type))) :+: (C1 (MetaCons "NvidiaTeslaV100" PrefixI False) (U1 :: Type -> Type) :+: (C1 (MetaCons "NvidiaTeslaP4" PrefixI False) (U1 :: Type -> Type) :+: C1 (MetaCons "NvidiaTeslaT4" PrefixI False) (U1 :: Type -> Type))))

GoogleCloudMlV1__Capability

data GoogleCloudMlV1__Capability Source #

Instances
Eq GoogleCloudMlV1__Capability Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__Capability Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__Capability -> c GoogleCloudMlV1__Capability #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__Capability #

toConstr :: GoogleCloudMlV1__Capability -> Constr #

dataTypeOf :: GoogleCloudMlV1__Capability -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__Capability) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__Capability) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__Capability -> GoogleCloudMlV1__Capability #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Capability -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__Capability -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__Capability -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__Capability -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Capability -> m GoogleCloudMlV1__Capability #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Capability -> m GoogleCloudMlV1__Capability #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__Capability -> m GoogleCloudMlV1__Capability #

Show GoogleCloudMlV1__Capability Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__Capability Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__Capability :: Type -> Type #

ToJSON GoogleCloudMlV1__Capability Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__Capability Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__Capability Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__Capability = D1 (MetaData "GoogleCloudMlV1__Capability" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__Capability'" PrefixI True) (S1 (MetaSel (Just "_gcmvcAvailableAccelerators") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Text])) :*: S1 (MetaSel (Just "_gcmvcType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GoogleCloudMlV1__CapabilityType))))

googleCloudMlV1__Capability :: GoogleCloudMlV1__Capability Source #

Creates a value of GoogleCloudMlV1__Capability with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvcAvailableAccelerators :: Lens' GoogleCloudMlV1__Capability [Text] Source #

Available accelerators for the capability.

GoogleCloudMlV1__OperationMetadata

data GoogleCloudMlV1__OperationMetadata Source #

Represents the metadata of the long-running operation.

See: googleCloudMlV1__OperationMetadata smart constructor.

Instances
Eq GoogleCloudMlV1__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__OperationMetadata -> c GoogleCloudMlV1__OperationMetadata #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__OperationMetadata #

toConstr :: GoogleCloudMlV1__OperationMetadata -> Constr #

dataTypeOf :: GoogleCloudMlV1__OperationMetadata -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__OperationMetadata) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__OperationMetadata) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__OperationMetadata -> GoogleCloudMlV1__OperationMetadata #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__OperationMetadata -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__OperationMetadata -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__OperationMetadata -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__OperationMetadata -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadata -> m GoogleCloudMlV1__OperationMetadata #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadata -> m GoogleCloudMlV1__OperationMetadata #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__OperationMetadata -> m GoogleCloudMlV1__OperationMetadata #

Show GoogleCloudMlV1__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__OperationMetadata :: Type -> Type #

ToJSON GoogleCloudMlV1__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__OperationMetadata Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

gcmvomStartTime :: Lens' GoogleCloudMlV1__OperationMetadata (Maybe UTCTime) Source #

The time operation processing started.

gcmvomModelName :: Lens' GoogleCloudMlV1__OperationMetadata (Maybe Text) Source #

Contains the name of the model associated with the operation.

gcmvomProjectNumber :: Lens' GoogleCloudMlV1__OperationMetadata (Maybe Int64) Source #

Contains the project number associated with the operation.

gcmvomVersion :: Lens' GoogleCloudMlV1__OperationMetadata (Maybe GoogleCloudMlV1__Version) Source #

Contains the version associated with the operation.

gcmvomEndTime :: Lens' GoogleCloudMlV1__OperationMetadata (Maybe UTCTime) Source #

The time operation processing completed.

gcmvomIsCancellationRequested :: Lens' GoogleCloudMlV1__OperationMetadata (Maybe Bool) Source #

Indicates whether a request to cancel this operation has been made.

gcmvomLabels :: Lens' GoogleCloudMlV1__OperationMetadata (Maybe GoogleCloudMlV1__OperationMetadataLabels) Source #

The user labels, inherited from the model or the model version being operated on.

GoogleAPI__HTTPBodyExtensionsItem

data GoogleAPI__HTTPBodyExtensionsItem Source #

Instances
Eq GoogleAPI__HTTPBodyExtensionsItem Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleAPI__HTTPBodyExtensionsItem Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleAPI__HTTPBodyExtensionsItem -> c GoogleAPI__HTTPBodyExtensionsItem #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleAPI__HTTPBodyExtensionsItem #

toConstr :: GoogleAPI__HTTPBodyExtensionsItem -> Constr #

dataTypeOf :: GoogleAPI__HTTPBodyExtensionsItem -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleAPI__HTTPBodyExtensionsItem) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleAPI__HTTPBodyExtensionsItem) #

gmapT :: (forall b. Data b => b -> b) -> GoogleAPI__HTTPBodyExtensionsItem -> GoogleAPI__HTTPBodyExtensionsItem #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleAPI__HTTPBodyExtensionsItem -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleAPI__HTTPBodyExtensionsItem -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleAPI__HTTPBodyExtensionsItem -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleAPI__HTTPBodyExtensionsItem -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleAPI__HTTPBodyExtensionsItem -> m GoogleAPI__HTTPBodyExtensionsItem #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleAPI__HTTPBodyExtensionsItem -> m GoogleAPI__HTTPBodyExtensionsItem #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleAPI__HTTPBodyExtensionsItem -> m GoogleAPI__HTTPBodyExtensionsItem #

Show GoogleAPI__HTTPBodyExtensionsItem Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleAPI__HTTPBodyExtensionsItem Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleAPI__HTTPBodyExtensionsItem :: Type -> Type #

ToJSON GoogleAPI__HTTPBodyExtensionsItem Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleAPI__HTTPBodyExtensionsItem Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleAPI__HTTPBodyExtensionsItem Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleAPI__HTTPBodyExtensionsItem = D1 (MetaData "GoogleAPI__HTTPBodyExtensionsItem" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleAPI__HTTPBodyExtensionsItem'" PrefixI True) (S1 (MetaSel (Just "_gahttpbeiAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text JSONValue))))

googleAPI__HTTPBodyExtensionsItem Source #

Creates a value of GoogleAPI__HTTPBodyExtensionsItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gahttpbeiAddtional :: Lens' GoogleAPI__HTTPBodyExtensionsItem (HashMap Text JSONValue) Source #

Properties of the object. Contains field 'type with type URL.

GoogleCloudMlV1__CancelJobRequest

data GoogleCloudMlV1__CancelJobRequest Source #

Request message for the CancelJob method.

See: googleCloudMlV1__CancelJobRequest smart constructor.

Instances
Eq GoogleCloudMlV1__CancelJobRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__CancelJobRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__CancelJobRequest -> c GoogleCloudMlV1__CancelJobRequest #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__CancelJobRequest #

toConstr :: GoogleCloudMlV1__CancelJobRequest -> Constr #

dataTypeOf :: GoogleCloudMlV1__CancelJobRequest -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__CancelJobRequest) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__CancelJobRequest) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__CancelJobRequest -> GoogleCloudMlV1__CancelJobRequest #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__CancelJobRequest -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__CancelJobRequest -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__CancelJobRequest -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__CancelJobRequest -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__CancelJobRequest -> m GoogleCloudMlV1__CancelJobRequest #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__CancelJobRequest -> m GoogleCloudMlV1__CancelJobRequest #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__CancelJobRequest -> m GoogleCloudMlV1__CancelJobRequest #

Show GoogleCloudMlV1__CancelJobRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__CancelJobRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__CancelJobRequest :: Type -> Type #

ToJSON GoogleCloudMlV1__CancelJobRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__CancelJobRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__CancelJobRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__CancelJobRequest = D1 (MetaData "GoogleCloudMlV1__CancelJobRequest" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__CancelJobRequest'" PrefixI False) (U1 :: Type -> Type))

googleCloudMlV1__CancelJobRequest :: GoogleCloudMlV1__CancelJobRequest Source #

Creates a value of GoogleCloudMlV1__CancelJobRequest with the minimum fields required to make a request.

GoogleCloudMlV1__TrainingOutput

data GoogleCloudMlV1__TrainingOutput Source #

Represents results of a training job. Output only.

See: googleCloudMlV1__TrainingOutput smart constructor.

Instances
Eq GoogleCloudMlV1__TrainingOutput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__TrainingOutput Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__TrainingOutput -> c GoogleCloudMlV1__TrainingOutput #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__TrainingOutput #

toConstr :: GoogleCloudMlV1__TrainingOutput -> Constr #

dataTypeOf :: GoogleCloudMlV1__TrainingOutput -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__TrainingOutput) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__TrainingOutput) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__TrainingOutput -> GoogleCloudMlV1__TrainingOutput #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__TrainingOutput -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__TrainingOutput -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__TrainingOutput -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__TrainingOutput -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingOutput -> m GoogleCloudMlV1__TrainingOutput #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingOutput -> m GoogleCloudMlV1__TrainingOutput #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__TrainingOutput -> m GoogleCloudMlV1__TrainingOutput #

Show GoogleCloudMlV1__TrainingOutput Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__TrainingOutput Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__TrainingOutput :: Type -> Type #

ToJSON GoogleCloudMlV1__TrainingOutput Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__TrainingOutput Source # 
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type Rep GoogleCloudMlV1__TrainingOutput Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__TrainingOutput = D1 (MetaData "GoogleCloudMlV1__TrainingOutput" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__TrainingOutput'" PrefixI True) ((S1 (MetaSel (Just "_gcmvtoIsHyperparameterTuningJob") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)) :*: S1 (MetaSel (Just "_gcmvtoCompletedTrialCount") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Int64)))) :*: (S1 (MetaSel (Just "_gcmvtoConsumedMLUnits") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe (Textual Double))) :*: S1 (MetaSel (Just "_gcmvtoTrials") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleCloudMlV1__HyperparameterOutput])))))

googleCloudMlV1__TrainingOutput :: GoogleCloudMlV1__TrainingOutput Source #

Creates a value of GoogleCloudMlV1__TrainingOutput with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvtoIsHyperparameterTuningJob :: Lens' GoogleCloudMlV1__TrainingOutput (Maybe Bool) Source #

Whether this job is a hyperparameter tuning job.

gcmvtoCompletedTrialCount :: Lens' GoogleCloudMlV1__TrainingOutput (Maybe Int64) Source #

The number of hyperparameter tuning trials that completed successfully. Only set for hyperparameter tuning jobs.

gcmvtoConsumedMLUnits :: Lens' GoogleCloudMlV1__TrainingOutput (Maybe Double) Source #

The amount of ML units consumed by the job.

gcmvtoTrials :: Lens' GoogleCloudMlV1__TrainingOutput [GoogleCloudMlV1__HyperparameterOutput] Source #

Results for individual Hyperparameter trials. Only set for hyperparameter tuning jobs.

GoogleAPI__HTTPBody

data GoogleAPI__HTTPBody Source #

Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top-level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged.

See: googleAPI__HTTPBody smart constructor.

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Eq GoogleAPI__HTTPBody Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Data GoogleAPI__HTTPBody Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleAPI__HTTPBody -> c GoogleAPI__HTTPBody #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleAPI__HTTPBody #

toConstr :: GoogleAPI__HTTPBody -> Constr #

dataTypeOf :: GoogleAPI__HTTPBody -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleAPI__HTTPBody) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleAPI__HTTPBody) #

gmapT :: (forall b. Data b => b -> b) -> GoogleAPI__HTTPBody -> GoogleAPI__HTTPBody #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleAPI__HTTPBody -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleAPI__HTTPBody -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleAPI__HTTPBody -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleAPI__HTTPBody -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleAPI__HTTPBody -> m GoogleAPI__HTTPBody #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleAPI__HTTPBody -> m GoogleAPI__HTTPBody #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleAPI__HTTPBody -> m GoogleAPI__HTTPBody #

Show GoogleAPI__HTTPBody Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleAPI__HTTPBody Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleAPI__HTTPBody :: Type -> Type #

ToJSON GoogleAPI__HTTPBody Source # 
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FromJSON GoogleAPI__HTTPBody Source # 
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type Rep GoogleAPI__HTTPBody Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleAPI__HTTPBody = D1 (MetaData "GoogleAPI__HTTPBody" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleAPI__HTTPBody'" PrefixI True) (S1 (MetaSel (Just "_gahttpbExtensions") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleAPI__HTTPBodyExtensionsItem])) :*: (S1 (MetaSel (Just "_gahttpbData") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bytes)) :*: S1 (MetaSel (Just "_gahttpbContentType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))))

googleAPI__HTTPBody :: GoogleAPI__HTTPBody Source #

Creates a value of GoogleAPI__HTTPBody with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gahttpbExtensions :: Lens' GoogleAPI__HTTPBody [GoogleAPI__HTTPBodyExtensionsItem] Source #

Application specific response metadata. Must be set in the first response for streaming APIs.

gahttpbContentType :: Lens' GoogleAPI__HTTPBody (Maybe Text) Source #

The HTTP Content-Type string representing the content type of the body.

GoogleIAMV1__TestIAMPermissionsRequest

data GoogleIAMV1__TestIAMPermissionsRequest Source #

Request message for `TestIamPermissions` method.

See: googleIAMV1__TestIAMPermissionsRequest smart constructor.

Instances
Eq GoogleIAMV1__TestIAMPermissionsRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleIAMV1__TestIAMPermissionsRequest Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleIAMV1__TestIAMPermissionsRequest -> c GoogleIAMV1__TestIAMPermissionsRequest #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleIAMV1__TestIAMPermissionsRequest #

toConstr :: GoogleIAMV1__TestIAMPermissionsRequest -> Constr #

dataTypeOf :: GoogleIAMV1__TestIAMPermissionsRequest -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleIAMV1__TestIAMPermissionsRequest) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleIAMV1__TestIAMPermissionsRequest) #

gmapT :: (forall b. Data b => b -> b) -> GoogleIAMV1__TestIAMPermissionsRequest -> GoogleIAMV1__TestIAMPermissionsRequest #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__TestIAMPermissionsRequest -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleIAMV1__TestIAMPermissionsRequest -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleIAMV1__TestIAMPermissionsRequest -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleIAMV1__TestIAMPermissionsRequest -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleIAMV1__TestIAMPermissionsRequest -> m GoogleIAMV1__TestIAMPermissionsRequest #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__TestIAMPermissionsRequest -> m GoogleIAMV1__TestIAMPermissionsRequest #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleIAMV1__TestIAMPermissionsRequest -> m GoogleIAMV1__TestIAMPermissionsRequest #

Show GoogleIAMV1__TestIAMPermissionsRequest Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleIAMV1__TestIAMPermissionsRequest Source # 
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ToJSON GoogleIAMV1__TestIAMPermissionsRequest Source # 
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FromJSON GoogleIAMV1__TestIAMPermissionsRequest Source # 
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type Rep GoogleIAMV1__TestIAMPermissionsRequest Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleIAMV1__TestIAMPermissionsRequest = D1 (MetaData "GoogleIAMV1__TestIAMPermissionsRequest" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleIAMV1__TestIAMPermissionsRequest'" PrefixI True) (S1 (MetaSel (Just "_giamvtiamprPermissions") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (Maybe [Text]))))

googleIAMV1__TestIAMPermissionsRequest :: GoogleIAMV1__TestIAMPermissionsRequest Source #

Creates a value of GoogleIAMV1__TestIAMPermissionsRequest with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

giamvtiamprPermissions :: Lens' GoogleIAMV1__TestIAMPermissionsRequest [Text] Source #

The set of permissions to check for the `resource`. Permissions with wildcards (such as '*' or 'storage.*') are not allowed. For more information see IAM Overview.

GoogleCloudMlV1__ListLocationsResponse

data GoogleCloudMlV1__ListLocationsResponse Source #

Instances
Eq GoogleCloudMlV1__ListLocationsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__ListLocationsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__ListLocationsResponse -> c GoogleCloudMlV1__ListLocationsResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__ListLocationsResponse #

toConstr :: GoogleCloudMlV1__ListLocationsResponse -> Constr #

dataTypeOf :: GoogleCloudMlV1__ListLocationsResponse -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__ListLocationsResponse) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__ListLocationsResponse) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__ListLocationsResponse -> GoogleCloudMlV1__ListLocationsResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ListLocationsResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__ListLocationsResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__ListLocationsResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__ListLocationsResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListLocationsResponse -> m GoogleCloudMlV1__ListLocationsResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListLocationsResponse -> m GoogleCloudMlV1__ListLocationsResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__ListLocationsResponse -> m GoogleCloudMlV1__ListLocationsResponse #

Show GoogleCloudMlV1__ListLocationsResponse Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__ListLocationsResponse Source # 
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ToJSON GoogleCloudMlV1__ListLocationsResponse Source # 
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FromJSON GoogleCloudMlV1__ListLocationsResponse Source # 
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type Rep GoogleCloudMlV1__ListLocationsResponse Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__ListLocationsResponse = D1 (MetaData "GoogleCloudMlV1__ListLocationsResponse" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" False) (C1 (MetaCons "GoogleCloudMlV1__ListLocationsResponse'" PrefixI True) (S1 (MetaSel (Just "_gcmvllrNextPageToken") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_gcmvllrLocations") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [GoogleCloudMlV1__Location]))))

googleCloudMlV1__ListLocationsResponse :: GoogleCloudMlV1__ListLocationsResponse Source #

Creates a value of GoogleCloudMlV1__ListLocationsResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

gcmvllrNextPageToken :: Lens' GoogleCloudMlV1__ListLocationsResponse (Maybe Text) Source #

Optional. Pass this token as the `page_token` field of the request for a subsequent call.

gcmvllrLocations :: Lens' GoogleCloudMlV1__ListLocationsResponse [GoogleCloudMlV1__Location] Source #

Locations where at least one type of CMLE capability is available.

GoogleCloudMlV1__VersionLabels

data GoogleCloudMlV1__VersionLabels Source #

Optional. One or more labels that you can add, to organize your model versions. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

See: googleCloudMlV1__VersionLabels smart constructor.

Instances
Eq GoogleCloudMlV1__VersionLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Data GoogleCloudMlV1__VersionLabels Source # 
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Defined in Network.Google.MachineLearning.Types.Product

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GoogleCloudMlV1__VersionLabels -> c GoogleCloudMlV1__VersionLabels #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GoogleCloudMlV1__VersionLabels #

toConstr :: GoogleCloudMlV1__VersionLabels -> Constr #

dataTypeOf :: GoogleCloudMlV1__VersionLabels -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c GoogleCloudMlV1__VersionLabels) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GoogleCloudMlV1__VersionLabels) #

gmapT :: (forall b. Data b => b -> b) -> GoogleCloudMlV1__VersionLabels -> GoogleCloudMlV1__VersionLabels #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__VersionLabels -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GoogleCloudMlV1__VersionLabels -> r #

gmapQ :: (forall d. Data d => d -> u) -> GoogleCloudMlV1__VersionLabels -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GoogleCloudMlV1__VersionLabels -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionLabels -> m GoogleCloudMlV1__VersionLabels #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionLabels -> m GoogleCloudMlV1__VersionLabels #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GoogleCloudMlV1__VersionLabels -> m GoogleCloudMlV1__VersionLabels #

Show GoogleCloudMlV1__VersionLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Generic GoogleCloudMlV1__VersionLabels Source # 
Instance details

Defined in Network.Google.MachineLearning.Types.Product

Associated Types

type Rep GoogleCloudMlV1__VersionLabels :: Type -> Type #

ToJSON GoogleCloudMlV1__VersionLabels Source # 
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Defined in Network.Google.MachineLearning.Types.Product

FromJSON GoogleCloudMlV1__VersionLabels Source # 
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type Rep GoogleCloudMlV1__VersionLabels Source # 
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Defined in Network.Google.MachineLearning.Types.Product

type Rep GoogleCloudMlV1__VersionLabels = D1 (MetaData "GoogleCloudMlV1__VersionLabels" "Network.Google.MachineLearning.Types.Product" "gogol-ml-0.4.0-E5tHTl2V6ffJIUGt4f8uUo" True) (C1 (MetaCons "GoogleCloudMlV1__VersionLabels'" PrefixI True) (S1 (MetaSel (Just "_gcmvvlAddtional") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 (HashMap Text Text))))

googleCloudMlV1__VersionLabels Source #

Creates a value of GoogleCloudMlV1__VersionLabels with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired: