PoolingSpec Class Reference

#include <PoolingSpec.h>

Public Member Functions
	PoolingSpec (const ::caffe::PoolingParameter &param)
const nncc::core::ADT::tensor::Shape &	ifm_shape (void) const
void	ifm_shape (const nncc::core::ADT::tensor::Shape &shape)
PoolingMethod	method (void) const
uint32_t	window_height (void) const
uint32_t	window_width (void) const
uint32_t	vertical_pad (void) const
uint32_t	horizontal_pad (void) const
uint32_t	vertical_stride (void) const
uint32_t	horizontal_stride (void) const
nncc::core::ADT::tensor::Shape	ofm_shape (void) const

Detailed Description

Definition at line 30 of file PoolingSpec.h.

Constructor & Destructor Documentation

PoolingSpec()

PoolingSpec::PoolingSpec

(

const ::caffe::PoolingParameter &

param

)

Definition at line 23 of file PoolingSpec.cpp.

                                                           : _param(param)
{
  // DO NOTHING
}

Member Function Documentation

horizontal_pad()

uint32_t PoolingSpec::horizontal_pad

(

void

)

const

Definition at line 87 of file PoolingSpec.cpp.

{
  // NOTE The input of Pooling SHOULD BE a rank-4 tensor.
  // Reference: PoolingLayer<Dtype>::Reshape in pooling_layer.cpp
  auto raw_padding = build_raw_padding().with(_param);
  auto spatial_padding = build_spatial_padding(2 /* SPATIAL RANK */).with(raw_padding);
  return spatial_padding.value(1 /* W */);
}

References build_raw_padding(), build_spatial_padding(), PaddingBase< Derived >::value(), RawPaddingBuilder::with(), and SpatialPaddingBuilder::with().

Referenced by ofm_shape().

horizontal_stride()

uint32_t PoolingSpec::horizontal_stride

(

void

)

const

Definition at line 111 of file PoolingSpec.cpp.

{
  if (_param.has_stride_w())
  {
    return _param.stride_w();
  }
 
  if (_param.has_stride())
  {
    return _param.stride();
  }
 
  return 1;
}

Referenced by ofm_shape().

ifm_shape() [1/2]

void PoolingSpec::ifm_shape ( const nncc::core::ADT::tensor::Shape &  shape )

inline

Definition at line 37 of file PoolingSpec.h.

{ _ifm_shape = shape; }

ifm_shape() [2/2]

const nncc::core::ADT::tensor::Shape & PoolingSpec::ifm_shape ( void  ) const

inline

Definition at line 36 of file PoolingSpec.h.

{ return _ifm_shape; }

Referenced by caffeimport::PoolingBuilder::build().

method()

PoolingMethod PoolingSpec::method

(

void

)

const

Definition at line 28 of file PoolingSpec.cpp.

{
  if (!_param.has_pool())
  {
    // Default pooling method is MAX
    // Reference: http://caffe.berkeleyvision.org/tutorial/layers/pooling.html
    return PoolingMethod::Max;
  }
 
  std::map<::caffe::PoolingParameter_PoolMethod, PoolingMethod> methods;
 
  // NOTE STOCHASTIC Pooling is not supported, yet
  // TODO Support STOCHASTIC Pooling
  methods[::caffe::PoolingParameter_PoolMethod_MAX] = PoolingMethod::Max;
  methods[::caffe::PoolingParameter_PoolMethod_AVE] = PoolingMethod::Avg;
 
  assert(_param.has_pool());
  return methods.at(_param.pool());
}

References Avg, and Max.

ofm_shape()

nncc::core::ADT::tensor::Shape PoolingSpec::ofm_shape

(

void

)

const

Definition at line 126 of file PoolingSpec.cpp.

{
  nncc::core::ADT::tensor::Shape res;
 
  // NOTE Caffe supports only pooling over rank-4 tensor
  assert(_ifm_shape.rank() == 4);
  res.resize(4);
 
  // N (= the number of bacths) SHOULD be same
  res.dim(0) = _ifm_shape.dim(0);
  // C (= the number of chaanels) SHOULD be same
  res.dim(1) = _ifm_shape.dim(1);
 
  // H and W are derived from IFM, Window, and Padding
  const auto effective_input_height = _ifm_shape.dim(2) + 2 * vertical_pad() - window_height();
  const auto effective_input_width = _ifm_shape.dim(3) + 2 * horizontal_pad() - window_width();
  // TODO Remove the following asserts
  assert(effective_input_height % vertical_stride() == 0);
  assert(effective_input_width % horizontal_stride() == 0);
  res.dim(2) = effective_input_height / vertical_stride() + 1;
  res.dim(3) = effective_input_width / horizontal_stride() + 1;
  return res;
}

References nncc::core::ADT::tensor::Shape::dim(), horizontal_pad(), horizontal_stride(), nncc::core::ADT::tensor::Shape::rank(), nncc::core::ADT::tensor::Shape::resize(), vertical_pad(), vertical_stride(), window_height(), and window_width().

vertical_pad()

uint32_t PoolingSpec::vertical_pad

(

void

)

const

Definition at line 78 of file PoolingSpec.cpp.

{
  // NOTE The input of Pooling SHOULD BE a rank-4 tensor.
  // Reference: PoolingLayer<Dtype>::Reshape in pooling_layer.cpp
  auto raw_padding = build_raw_padding().with(_param);
  auto spatial_padding = build_spatial_padding(2 /* SPATIAL RANK */).with(raw_padding);
  return spatial_padding.value(0 /* H */);
}

References build_raw_padding(), build_spatial_padding(), PaddingBase< Derived >::value(), RawPaddingBuilder::with(), and SpatialPaddingBuilder::with().

Referenced by ofm_shape().

vertical_stride()

uint32_t PoolingSpec::vertical_stride

(

void

)

const

Definition at line 96 of file PoolingSpec.cpp.

{
  if (_param.has_stride_h())
  {
    return _param.stride_h();
  }
 
  if (_param.has_stride())
  {
    return _param.stride();
  }
 
  return 1;
}

Referenced by ofm_shape().

window_height()

uint32_t PoolingSpec::window_height

(

void

)

const

Definition at line 48 of file PoolingSpec.cpp.

{
  // NOTE Global pooling is not supported, yet
  // TODO Support global pooling
  assert(!_param.global_pooling());
 
  if (_param.has_kernel_h())
  {
    return _param.kernel_h();
  }
 
  assert(_param.has_kernel_size());
  return _param.kernel_size();
}

Referenced by ofm_shape().

window_width()

uint32_t PoolingSpec::window_width

(

void

)

const

Definition at line 63 of file PoolingSpec.cpp.

{
  // NOTE Global pooling is not supported, yet
  // TODO Support global pooling
  assert(!_param.global_pooling());
 
  if (_param.has_kernel_w())
  {
    return _param.kernel_w();
  }
 
  assert(_param.has_kernel_size());
  return _param.kernel_size();
}

Referenced by ofm_shape().

---

The documentation for this class was generated from the following files:

• compiler/enco/frontend/caffe/src/PoolingSpec.h
• compiler/enco/frontend/caffe/src/PoolingSpec.cpp