Safe Haskell	None
Language	Haskell2010

TensorSafe.Layers

Description

This module exposes all Layers declared at TensorSafe.Layers.

Synopsis

data Add :: ls1 -> ls2 -> Type
data BatchNormalization :: Nat -> Nat -> Nat -> Type
data Conv2D :: Nat -> Nat -> Nat -> Nat -> Nat -> Nat -> Type
data Dense :: Nat -> Nat -> Type
data Dropout :: Nat -> Nat -> Type
data Flatten
data GlobalAvgPooling2D
data Input
data LSTM :: Nat -> Bool -> Type
data MaxPooling :: Nat -> Nat -> Nat -> Nat -> Type
data Relu
data Sigmoid
data ZeroPadding2D :: Nat -> Nat -> Type

Documentation

data Add :: ls1 -> ls2 -> Type Source #

Adds the dimensions of the shapes to a list of values with shape D1

Instances

Show (Add a b) Source #
Instance details Defined in TensorSafe.Layers.Add Methods showsPrec :: Int -> Add a b -> ShowS # show :: Add a b -> String # showList :: [Add a b] -> ShowS #
Layer (Add ls6 ls7) Source #
Instance details Defined in TensorSafe.Layers.Add Methods layer :: Add ls6 ls7 Source # compile :: Add ls6 ls7 -> InputShape -> CNetwork Source #

data BatchNormalization :: Nat -> Nat -> Nat -> Type Source #

A classic BatchNormalization layer with axis, momentum and epsilon parameters

Instances

Show (BatchNormalization a b c) Source #
Instance details Defined in TensorSafe.Layers.BatchNormalization Methods showsPrec :: Int -> BatchNormalization a b c -> ShowS # show :: BatchNormalization a b c -> String # showList :: [BatchNormalization a b c] -> ShowS #
(KnownNat axis, KnownNat momentum, KnownNat epsilon) => Layer (BatchNormalization axis momentum epsilon) Source #
Instance details Defined in TensorSafe.Layers.BatchNormalization Methods layer :: BatchNormalization axis momentum epsilon Source # compile :: BatchNormalization axis momentum epsilon -> InputShape -> CNetwork Source #

data Conv2D :: Nat -> Nat -> Nat -> Nat -> Nat -> Nat -> Type Source #

A 2D Convolutional layer

Instances

Show (Conv2D a b c d e f) Source #
Instance details Defined in TensorSafe.Layers.Conv2D Methods showsPrec :: Int -> Conv2D a b c d e f -> ShowS # show :: Conv2D a b c d e f -> String # showList :: [Conv2D a b c d e f] -> ShowS #
(KnownNat channels, KnownNat filters, KnownNat kernelRows, KnownNat kernelColumns, KnownNat strideRows, KnownNat strideColumns) => Layer (Conv2D channels filters kernelRows kernelColumns strideRows strideColumns) Source #
Instance details Defined in TensorSafe.Layers.Conv2D Methods layer :: Conv2D channels filters kernelRows kernelColumns strideRows strideColumns Source # compile :: Conv2D channels filters kernelRows kernelColumns strideRows strideColumns -> InputShape -> CNetwork Source #

data Dense :: Nat -> Nat -> Type Source #

A classic Dense, or FullyConnected, layer with input and output parameters.

Instances

Show (Dense a b) Source #
Instance details Defined in TensorSafe.Layers.Dense Methods showsPrec :: Int -> Dense a b -> ShowS # show :: Dense a b -> String # showList :: [Dense a b] -> ShowS #
(KnownNat input, KnownNat output) => Layer (Dense input output) Source #
Instance details Defined in TensorSafe.Layers.Dense Methods layer :: Dense input output Source # compile :: Dense input output -> InputShape -> CNetwork Source #

data Dropout :: Nat -> Nat -> Type Source #

A Dropout layer with rate and seed arguments

Instances

Show (Dropout a b) Source #
Instance details Defined in TensorSafe.Layers.Dropout Methods showsPrec :: Int -> Dropout a b -> ShowS # show :: Dropout a b -> String # showList :: [Dropout a b] -> ShowS #
(KnownNat rate, KnownNat seed) => Layer (Dropout rate seed) Source #
Instance details Defined in TensorSafe.Layers.Dropout Methods layer :: Dropout rate seed Source # compile :: Dropout rate seed -> InputShape -> CNetwork Source #

data Flatten Source #

Flattens the dimensions of the shapes to a list of values with shape D1

Instances

Show Flatten Source #
Instance details Defined in TensorSafe.Layers.Flatten Methods showsPrec :: Int -> Flatten -> ShowS # show :: Flatten -> String # showList :: [Flatten] -> ShowS #
Layer Flatten Source #
Instance details Defined in TensorSafe.Layers.Flatten Methods layer :: Flatten Source # compile :: Flatten -> InputShape -> CNetwork Source #

data GlobalAvgPooling2D Source #

A GlobalAvgPooling2D function

Instances

Show GlobalAvgPooling2D Source #
Instance details Defined in TensorSafe.Layers.GlobalAvgPooling2D Methods showsPrec :: Int -> GlobalAvgPooling2D -> ShowS # show :: GlobalAvgPooling2D -> String # showList :: [GlobalAvgPooling2D] -> ShowS #
Layer GlobalAvgPooling2D Source #
Instance details Defined in TensorSafe.Layers.GlobalAvgPooling2D Methods layer :: GlobalAvgPooling2D Source # compile :: GlobalAvgPooling2D -> InputShape -> CNetwork Source #

data Input Source #

Inputs the dimensions of the shapes to a list of values with shape D1

Instances

Show Input Source #
Instance details Defined in TensorSafe.Layers.Input Methods showsPrec :: Int -> Input -> ShowS # show :: Input -> String # showList :: [Input] -> ShowS #
Layer Input Source #
Instance details Defined in TensorSafe.Layers.Input Methods layer :: Input Source # compile :: Input -> InputShape -> CNetwork Source #

data LSTM :: Nat -> Bool -> Type Source #

A LSTM layer with a number of units and a option to return the original sequences.

Instances

Show (LSTM a b) Source #
Instance details Defined in TensorSafe.Layers.LSTM Methods showsPrec :: Int -> LSTM a b -> ShowS # show :: LSTM a b -> String # showList :: [LSTM a b] -> ShowS #
KnownNat units => Layer (LSTM units b) Source #
Instance details Defined in TensorSafe.Layers.LSTM Methods layer :: LSTM units b Source # compile :: LSTM units b -> InputShape -> CNetwork Source #

data MaxPooling :: Nat -> Nat -> Nat -> Nat -> Type Source #

A 2D MaxPooling pooling that works for D2 and D3 shapes

Instances

Show (MaxPooling a b c d) Source #
Instance details Defined in TensorSafe.Layers.MaxPooling Methods showsPrec :: Int -> MaxPooling a b c d -> ShowS # show :: MaxPooling a b c d -> String # showList :: [MaxPooling a b c d] -> ShowS #
(KnownNat kernelRows, KnownNat kernelColumns, KnownNat strideRows, KnownNat strideColumns) => Layer (MaxPooling kernelRows kernelColumns strideRows strideColumns) Source #
Instance details Defined in TensorSafe.Layers.MaxPooling Methods layer :: MaxPooling kernelRows kernelColumns strideRows strideColumns Source # compile :: MaxPooling kernelRows kernelColumns strideRows strideColumns -> InputShape -> CNetwork Source #

data Relu Source #

A ReLu activation function

Instances

Show Relu Source #
Instance details Defined in TensorSafe.Layers.Relu Methods showsPrec :: Int -> Relu -> ShowS # show :: Relu -> String # showList :: [Relu] -> ShowS #
Layer Relu Source #
Instance details Defined in TensorSafe.Layers.Relu Methods layer :: Relu Source # compile :: Relu -> InputShape -> CNetwork Source #

data Sigmoid Source #

A Sigmoid activation function

Instances

Show Sigmoid Source #
Instance details Defined in TensorSafe.Layers.Sigmoid Methods showsPrec :: Int -> Sigmoid -> ShowS # show :: Sigmoid -> String # showList :: [Sigmoid] -> ShowS #
Layer Sigmoid Source #
Instance details Defined in TensorSafe.Layers.Sigmoid Methods layer :: Sigmoid Source # compile :: Sigmoid -> InputShape -> CNetwork Source #

data ZeroPadding2D :: Nat -> Nat -> Type Source #

A ZeroPadding2D layer with padding_rows and padding_cols arguments

Instances

Show (ZeroPadding2D a b) Source #
Instance details Defined in TensorSafe.Layers.ZeroPadding2D Methods showsPrec :: Int -> ZeroPadding2D a b -> ShowS # show :: ZeroPadding2D a b -> String # showList :: [ZeroPadding2D a b] -> ShowS #
(KnownNat padding_rows, KnownNat padding_cols) => Layer (ZeroPadding2D padding_rows padding_cols) Source #
Instance details Defined in TensorSafe.Layers.ZeroPadding2D Methods layer :: ZeroPadding2D padding_rows padding_cols Source # compile :: ZeroPadding2D padding_rows padding_cols -> InputShape -> CNetwork Source #