popnn::pooling Namespace Reference

Functions for pooling operations. More...

Functions
poplar::Tensor	pool (poplar::Graph &graph, const PoolParams &params, const poplar::Tensor &in, poplar::program::Sequence &prog, const poplar::DebugContext &debugContext={}, const poplar::OptionFlags &options={})
	Add a pooling operation to the graph. More...
poplar::Tensor	poolInputGradient (poplar::Graph &graph, const PoolParams &params, const poplar::Tensor &in, const poplar::Tensor &pooled, const poplar::Tensor &pooledGradient, bool useScaledGradient, poplar::program::Sequence &prog, const poplar::DebugContext &debugContext={}, const poplar::OptionFlags &options={})
	Calculate the gradient with respect to the input of a pooling operation given the gradient of the output. More...
poplar::Tensor	poolInputGradient (poplar::Graph &graph, const PoolParams &params, const unsigned fwdChansPerGroup, const poplar::Tensor &pooledGradient, poplar::program::Sequence &prog, const poplar::DebugContext &debugContext={}, const poplar::OptionFlags &options={})
	Calculate the gradient with respect to the input of a pooling operation given the gradient of the output. More...

Detailed Description

Functions for pooling operations.

Function Documentation

pool()

poplar::Tensor popnn::pooling::pool	(	poplar::Graph &	graph,
		const PoolParams &	params,
		const poplar::Tensor &	in,
		poplar::program::Sequence &	prog,
		const poplar::DebugContext &	debugContext = {},
		const poplar::OptionFlags &	options = {}
	)

Add a pooling operation to the graph.

This performs a pooling over the spatial dimensions [...]. The shape of the input should be [batchSize * numChannels * ...].

Parameters

graph	The graph that the operation will be added to.
params	The pooling parameters.
in	The input tensor.
prog	The program sequence to append the operation to.
debugContext	Optional debug information.
options	Pooling options (not currently used).

Returns

A tensor with the results of the pooling operation.

poolInputGradient() [1/2]

poplar::Tensor popnn::pooling::poolInputGradient	(	poplar::Graph &	graph,
		const PoolParams &	params,
		const poplar::Tensor &	in,
		const poplar::Tensor &	pooled,
		const poplar::Tensor &	pooledGradient,
		bool	useScaledGradient,
		poplar::program::Sequence &	prog,
		const poplar::DebugContext &	debugContext = {},
		const poplar::OptionFlags &	options = {}
	)

Calculate the gradient with respect to the input of a pooling operation given the gradient of the output.

While this function can be used for maximum, average or sum pooling, poolInputGradient(poplar::Graph&, const PoolParams&, const unsigned, const poplar::Tensor&, poplar::program::Sequence&, const poplar::DebugContext&, const poplar::OptionFlags&) is recommended for average or sum pooling.

This performs a pooling over the spatial dimensions [...]. The shape of the input should be [batchSize * numChannels * ...].

Parameters

graph	The graph the operation will be added to.
params	The pooling parameters.
in	The forward activations tensor input to pooling.
pooled	The output of pooling in the forward pass.
pooledGradient	The gradients to the pooling operation.
useScaledGradient	Use a scaled gradient if set to true. Otherwise, the gradient is propagated to all the positions which matched the pooled value in the forward pass.
prog	The program sequence to append the operation to.
debugContext	Optional debug information.
options	The pooling options. See pool().

Returns

A tensor with the results of the pooling operation.

poolInputGradient() [2/2]

poplar::Tensor popnn::pooling::poolInputGradient	(	poplar::Graph &	graph,
		const PoolParams &	params,
		const unsigned	fwdChansPerGroup,
		const poplar::Tensor &	pooledGradient,
		poplar::program::Sequence &	prog,
		const poplar::DebugContext &	debugContext = {},
		const poplar::OptionFlags &	options = {}
	)

Calculate the gradient with respect to the input of a pooling operation given the gradient of the output.

This function should be used for average and sum pooling.

This performs a pooling over the spatial dimensions [...]. The shape of the output will be [batchSize * numChannels * ...].

Parameters

graph	The graph the operation will be added to.
params	The pooling parameters.
fwdChansPerGroup	Used in creating the output tensor.
pooledGradient	The gradients to the pooling operation.
prog	The program sequence to append the operation to.
debugContext	Optional debug information.
options	The pooling options. See pool().

Returns

A tensor with the results of the pooling operation.