hasktorch-indef-0.0.1.0: Core Hasktorch abstractions wrapping FFI bindings

Copyright(c) Sam Stites 2017
LicenseBSD3
Maintainersam@stites.io
Stabilityexperimental
Portabilitynon-portable
Safe HaskellNone
LanguageHaskell2010

Torch.Indef.Dynamic.NN.Pooling

Description

DYNAMIC-NN MODULE WARNING: this module is mostly unfinished and undocumented. It provides, in essence, direct calls to the torch neural network libraries: THNN and THCUNN. Because the dynamic tensor code requires a lot of runtime checks which requires a lot of thought regarding a good API, the recommended route is to use Static tensors, which have a much more natural API and is inherently safer.

Synopsis

Documentation

_spatialAdaptiveAveragePooling_updateOutput :: Dynamic -> Dynamic -> Int -> Int -> IO () Source #

spatialAdaptiveAveragePooling forward pass (updates the output tensor)

_spatialAdaptiveAveragePooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IO () Source #

spatialAdaptiveAveragePooling backward pass (updates the gradInput tensor)

_spatialAveragePooling_updateOutput :: Dynamic -> Dynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> Bool -> IO () Source #

spatialAveragePooling forward pass (updates the output tensor)

_spatialAveragePooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> Bool -> IO () Source #

spatialAveragePooling backward pass (updates the gradInput tensor)

_volumetricAveragePooling_updateOutput :: Dynamic -> Dynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> Bool -> IO () Source #

volumetricAveragePooling forward pass (updates the output tensor)

_volumetricAveragePooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> Bool -> IO () Source #

volumetricAveragePooling backward pass (updates the gradInput tensor)

_volumetricAdaptiveAveragePooling_updateOutput :: Dynamic -> Dynamic -> Int -> Int -> Int -> IO () Source #

volumetricAdaptiveAveragePooling forward pass (updates the output tensor)

_volumetricAdaptiveAveragePooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IO () Source #

volumetricAdaptiveAveragePooling backward pass (updates the gradInput tensor)

_featureLPPooling_updateOutput :: Dynamic -> Dynamic -> Double -> Int -> Int -> Bool -> IO () Source #

featureLPPooling forward pass (updates the output tensor)

_featureLPPooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> Dynamic -> Double -> Int -> Int -> Bool -> IO () Source #

featureLPPooling backward pass (updates the gradInput tensor)

_temporalMaxPooling_updateOutput :: Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> IO () Source #

temporalMaxPooling forward pass (updates the output tensor)

_temporalMaxPooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> IO () Source #

temporalMaxPooling backward pass (updates the gradInput tensor)

_spatialAdaptiveMaxPooling_updateOutput :: Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> IO () Source #

spatialAdaptiveMaxPooling forward pass (updates the output tensor)

_spatialAdaptiveMaxPooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IndexDynamic -> IO () Source #

spatialAdaptiveMaxPooling backward pass (updates the gradInput tensor)

_spatialFractionalMaxPooling_updateOutput :: Dynamic -> Dynamic -> Int -> Int -> Int -> Int -> IndexDynamic -> Dynamic -> IO () Source #

spatialFractionalMaxPooling forward pass (updates the output tensor)

_spatialFractionalMaxPooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> Int -> Int -> Int -> Int -> IndexDynamic -> IO () Source #

spatialFractionalMaxPooling backward pass (updates the gradInput tensor)

_spatialMaxPooling_updateOutput Source #

Arguments

:: Dynamic

input

-> Dynamic

output

-> IndexDynamic

indices

-> (Int, Int)

kernel size

-> (Int, Int)

step size

-> (Int, Int)

padding size

-> Bool

ceil mode

-> IO () 

spatialMaxPooling forward pass (updates the output tensor)

_spatialMaxPooling_updateGradInput Source #

Arguments

:: Dynamic

input

-> Dynamic

grad output

-> Dynamic

grad input

-> IndexDynamic

indices

-> (Int, Int)

kernel size

-> (Int, Int)

step size

-> (Int, Int)

padding size

-> Bool

ceil mode

-> IO () 

spatialMaxPooling backward pass (updates the gradInput tensor)

_spatialDilatedMaxPooling_updateOutput Source #

Arguments

:: Dynamic

input

-> Dynamic

output

-> IndexDynamic

indices

-> (Int, Int)

kernel size

-> (Int, Int)

step size

-> (Int, Int)

padding size

-> (Int, Int)

dilation size

-> Bool

ceil mode

-> IO () 

spatialDilatedMaxPooling forward pass (updates the output tensor)

_spatialDilatedMaxPooling_updateGradInput Source #

Arguments

:: Dynamic

input

-> Dynamic

grad output

-> Dynamic

grad input

-> IndexDynamic

indices

-> (Int, Int)

kernel size

-> (Int, Int)

step size

-> (Int, Int)

padding size

-> (Int, Int)

dilation size

-> Bool

ceil mode

-> IO () 

spatialDilatedMaxPooling backward pass (updates the gradInput tensor)

_spatialMaxUnpooling_updateOutput :: Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> IO () Source #

spatialMaxUnpooling forward pass (updates the output tensor)

_spatialMaxUnpooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> IO () Source #

spatialMaxUnpooling backward pass (updates the gradInput tensor)

_volumetricFractionalMaxPooling_updateOutput :: Dynamic -> Dynamic -> Int -> Int -> Int -> Int -> Int -> Int -> IndexDynamic -> Dynamic -> IO () Source #

volumetricFractionalMaxPooling forward pass (updates the output tensor)

_volumetricFractionalMaxPooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> Int -> Int -> Int -> Int -> Int -> Int -> IndexDynamic -> IO () Source #

volumetricFractionalMaxPooling backward pass (updates the gradInput tensor)

_volumetricMaxPooling_updateOutput :: Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> IO () Source #

volumetricMaxPooling forward pass (updates the output tensor)

_volumetricMaxPooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> IO () Source #

volumetricMaxPooling backward pass (updates the gradInput tensor)

_volumetricDilatedMaxPooling_updateOutput :: Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> IO () Source #

volumetricDilatedMaxPooling forward pass (updates the output tensor)

_volumetricDilatedMaxPooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> IO () Source #

volumetricDilatedMaxPooling backward pass (updates the gradInput tensor)

_volumetricMaxUnpooling_updateOutput :: Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> IO () Source #

volumetricMaxUnpooling forward pass (updates the output tensor)

_volumetricMaxUnpooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> IO () Source #

volumetricMaxUnpooling backward pass (updates the gradInput tensor)

_volumetricAdaptiveMaxPooling_updateOutput :: Dynamic -> Dynamic -> IndexDynamic -> Int -> Int -> Int -> IO () Source #

volumetricAdaptiveMaxPooling forward pass (updates the output tensor)

_volumetricAdaptiveMaxPooling_updateGradInput :: Dynamic -> Dynamic -> Dynamic -> IndexDynamic -> IO () Source #

volumetricAdaptiveMaxPooling backward pass (updates the gradInput tensor)