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Commit 1df7b845 authored by Benjamin Thomas Graham's avatar Benjamin Thomas Graham
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3d segmantation

parent f2e3800b
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Showing with 175 additions and 30 deletions
sparseconvnet/SCN/generic/CPU/MaxPooling.cpp 0 → 100644
View file @ 1df7b845
// Copyright 2016-present, Facebook, Inc.
// All rights reserved.
//
// This source code is licensed under the license found in the
// LICENSE file in the root directory of this source tree.
#ifndef TH_GENERIC_FILE_
#define TH_GENERIC_FILE_ "generic/CPU/MaxPooling.cpp"
#else
#include "MaxPooling.h"
extern "C" void scn_DR_(MaxPooling_updateOutput)(
THLongTensor *inputSize, THLongTensor *outputSize, THLongTensor *poolSize,
THLongTensor *poolStride, void **m, THTensor *input_features,
THTensor *output_features, long nFeaturesToDrop) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1] - nFeaturesToDrop;
auto _rules =
_m.getRuleBook(inputSize, outputSize, poolSize, poolStride, true);
uInt nActive = _m.getNActive(outputSize);
THTensor_(resize2d)(output_features, nActive,
input_features->size[1] - nFeaturesToDrop);
THTensor_(zero)(output_features);
auto iF = THTensor_(data)(input_features) + nFeaturesToDrop;
auto oF = THTensor_(data)(output_features);
for (auto &r : _rules) {
uInt nHot = r.size() / 2;
MaxPooling_ForwardPass<real>(iF, oF, nPlanes, input_features->stride[0],
output_features->stride[0], &r[0], nHot);
}
}
extern "C" void scn_DR_(MaxPooling_updateGradInput)(
THLongTensor *inputSize, THLongTensor *outputSize, THLongTensor *poolSize,
THLongTensor *poolStride, void **m, THTensor *input_features,
THTensor *d_input_features, THTensor *output_features,
THTensor *d_output_features, long nFeaturesToDrop) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1] - nFeaturesToDrop;
auto _rules =
_m.getRuleBook(inputSize, outputSize, poolSize, poolStride, true);
uInt nActive = _m.getNActive(outputSize);
THTensor_(resizeAs)(d_input_features, input_features);
THTensor_(zero)(d_input_features);
auto iF = THTensor_(data)(input_features);
auto oF = THTensor_(data)(output_features);
auto diF = THTensor_(data)(d_input_features);
auto doF = THTensor_(data)(d_output_features);
for (auto &r : _rules) {
uInt nHot = r.size() / 2;
MaxPooling_BackwardPass<real>(iF, diF, oF, doF, nPlanes,
input_features->stride[0],
output_features->stride[0], &r[0], nHot);
}
}
extern "C" void scn_DR_(RandomizedStrideMaxPooling_updateOutput)(
THLongTensor *inputSize, THLongTensor *outputSize, THLongTensor *poolSize,
THLongTensor *poolStride, void **m, THTensor *input_features,
THTensor *output_features, long nFeaturesToDrop) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1] - nFeaturesToDrop;
auto _rules =
_m.getRandomizedStrideRuleBook(inputSize, outputSize, poolSize, poolStride, true);
uInt nActive = _m.getNActive(outputSize);
THTensor_(resize2d)(output_features, nActive,
input_features->size[1] - nFeaturesToDrop);
THTensor_(zero)(output_features);
auto iF = THTensor_(data)(input_features) + nFeaturesToDrop;
auto oF = THTensor_(data)(output_features);
for (auto &r : _rules) {
uInt nHot = r.size() / 2;
MaxPooling_ForwardPass<real>(iF, oF, nPlanes, input_features->stride[0],
output_features->stride[0], &r[0], nHot);
}
}
extern "C" void scn_DR_(RandomizedStrideMaxPooling_updateGradInput)(
THLongTensor *inputSize, THLongTensor *outputSize, THLongTensor *poolSize,
THLongTensor *poolStride, void **m, THTensor *input_features,
THTensor *d_input_features, THTensor *output_features,
THTensor *d_output_features, long nFeaturesToDrop) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1] - nFeaturesToDrop;
auto _rules =
_m.getRandomizedStrideRuleBook(inputSize, outputSize, poolSize, poolStride, true);
uInt nActive = _m.getNActive(outputSize);
THTensor_(resizeAs)(d_input_features, input_features);
THTensor_(zero)(d_input_features);
auto iF = THTensor_(data)(input_features);
auto oF = THTensor_(data)(output_features);
auto diF = THTensor_(data)(d_input_features);
auto doF = THTensor_(data)(d_output_features);
for (auto &r : _rules) {
uInt nHot = r.size() / 2;
MaxPooling_BackwardPass<real>(iF, diF, oF, doF, nPlanes,
input_features->stride[0],
output_features->stride[0], &r[0], nHot);
}
}
#endif
PyTorch/sparseconvnet/SCN/generic/CPU/SparseToDense.cpp → sparseconvnet/SCN/generic/CPU/SparseToDense.cpp
View file @ 1df7b845
......@@ -11,7 +11,7 @@
extern "C" void scn_DR_(SparseToDense_updateOutput)(
THLongTensor *inputSize, void **m, THTensor *input_features,
THTensor *output_features, void *rulesBuffer, long nPlanes) {
THTensor *output_features, long nPlanes) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
......@@ -39,8 +39,7 @@ extern "C" void scn_DR_(SparseToDense_updateOutput)(
}
extern "C" void scn_DR_(SparseToDense_updateGradInput)(
THLongTensor *inputSize, void **m, THTensor *input_features,
THTensor *d_input_features, THTensor *d_output_features,
void *rulesBuffer) {
THTensor *d_input_features, THTensor *d_output_features) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
THTensor_(resizeAs)(d_input_features, input_features);
......
PyTorch/sparseconvnet/SCN/generic/CPU/MaxPooling.cpp → sparseconvnet/SCN/generic/CPU/UnPooling.cpp
View file @ 1df7b845
......@@ -5,19 +5,19 @@
// LICENSE file in the root directory of this source tree.
#ifndef TH_GENERIC_FILE_
#define TH_GENERIC_FILE_ "generic/CPU/MaxPooling.cpp"
#define TH_GENERIC_FILE_ "generic/CPU/UnPooling.cpp"
#else
#include "MaxPooling.h"
#include "UnPooling.h"
extern "C" void scn_DR_(MaxPooling_updateOutput)(
extern "C" void scn_DR_(UnPooling_updateOutput)(
THLongTensor *inputSize, THLongTensor *outputSize, THLongTensor *poolSize,
THLongTensor *poolStride, void **m, THTensor *input_features,
THTensor *output_features, long nFeaturesToDrop, void *rulesBuffer) {
THTensor *output_features, long nFeaturesToDrop) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1] - nFeaturesToDrop;
auto _rules =
_m.getRuleBook(inputSize, outputSize, poolSize, poolStride, true);
_m.getRuleBook(outputSize, inputSize, poolSize, poolStride, true);
uInt nActive = _m.getNActive(outputSize);
THTensor_(resize2d)(output_features, nActive,
input_features->size[1] - nFeaturesToDrop);
......@@ -28,34 +28,33 @@ extern "C" void scn_DR_(MaxPooling_updateOutput)(
for (auto &r : _rules) {
uInt nHot = r.size() / 2;
MaxPooling_ForwardPass<real>(iF, oF, nPlanes, input_features->stride[0],
output_features->stride[0], &r[0], nHot);
UnPooling_ForwardPass<real>(iF, oF, nPlanes, input_features->size[1],
output_features->size[1], &r[0], nHot,
_rules.size());
}
}
extern "C" void scn_DR_(MaxPooling_updateGradInput)(
extern "C" void scn_DR_(UnPooling_updateGradInput)(
THLongTensor *inputSize, THLongTensor *outputSize, THLongTensor *poolSize,
THLongTensor *poolStride, void **m, THTensor *input_features,
THTensor *d_input_features, THTensor *output_features,
THTensor *d_output_features, long nFeaturesToDrop, void *rulesBuffer) {
THTensor *d_input_features, THTensor *d_output_features,
long nFeaturesToDrop) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1] - nFeaturesToDrop;
auto _rules =
_m.getRuleBook(inputSize, outputSize, poolSize, poolStride, true);
_m.getRuleBook(outputSize, inputSize, poolSize, poolStride, true);
uInt nActive = _m.getNActive(outputSize);
THTensor_(resizeAs)(d_input_features, input_features);
THTensor_(zero)(d_input_features);
auto iF = THTensor_(data)(input_features);
auto oF = THTensor_(data)(output_features);
auto diF = THTensor_(data)(d_input_features);
auto diF = THTensor_(data)(d_input_features) + nFeaturesToDrop;
auto doF = THTensor_(data)(d_output_features);
for (auto &r : _rules) {
uInt nHot = r.size() / 2;
MaxPooling_BackwardPass<real>(iF, diF, oF, doF, nPlanes,
input_features->stride[0],
output_features->stride[0], &r[0], nHot);
UnPooling_BackwardPass<real>(diF, doF, nPlanes, input_features->size[1],
d_output_features->size[1], &r[0], nHot,
_rules.size());
}
}
#endif
sparseconvnet/SCN/generic/CPU/UnPooling.h 0 → 100644
View file @ 1df7b845
// Copyright 2016-present, Facebook, Inc.
// All rights reserved.
//
// This source code is licensed under the license found in the
// LICENSE file in the root directory of this source tree.
#ifndef CPU_UNPOOLING_H
#define CPU_UNPOOLING_H
#include "../SparseConvNet.h"
template <typename T>
void UnPooling_ForwardPass(T *input_features, T *output_features, uInt nPlanes,
uInt input_stride, uInt output_stride, uInt *rules,
uInt nHot, uInt filterVolume) {
for (uInt outSite = 0; outSite < nHot; outSite++) {
uInt i = rules[2 * outSite + 1] * input_stride;
uInt o = rules[2 * outSite] * output_stride;
for (uInt plane = 0; plane < nPlanes; plane++)
output_features[o + plane] += input_features[i + plane];
}
}
template <typename T>
void UnPooling_BackwardPass(T *d_input_features, T *d_output_features,
uInt nPlanes, uInt input_stride, uInt output_stride,
uInt *rules, uInt nHot, uInt filterVolume) {
for (uInt outSite = 0; outSite < nHot; outSite++) {
uInt i = rules[2 * outSite + 1] * input_stride;
uInt o = rules[2 * outSite] * output_stride;
for (uInt plane = 0; plane < nPlanes; plane++)
d_input_features[i + plane] += d_output_features[o + plane];
}
}
#endif /* CPU_UNPOOLING_H */
PyTorch/sparseconvnet/SCN/generic/GPU/ActivePooling.cu → sparseconvnet/SCN/generic/GPU/ActivePooling.cu
View file @ 1df7b845
......@@ -11,7 +11,7 @@
extern "C" void scn_DR_(ActivePooling_updateOutput)(
THLongTensor *inputSize, void **m, THCTensor *input_features,
THCTensor *output_features, THCITensor *rulesBuffer, bool average) {
THCTensor *output_features, bool average) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1];
auto _rules = _m.getActivePoolingRuleBook(inputSize);
......@@ -20,9 +20,10 @@ extern "C" void scn_DR_(ActivePooling_updateOutput)(
THCTensor_(resize2d)(state, output_features, batchSize, nPlanes);
THCTensor_(zero)(state, output_features);
if (THCITensor_nElement(state, rulesBuffer) < 1 << 22)
THCITensor_resize1d(state, rulesBuffer, 1 << 22);
uInt *rb = (uInt *)THCITensor_data(state, rulesBuffer);
auto rulesBuffer = THCITensor_(new)(state);
if (THCITensor_(nElement)(state, rulesBuffer) < 1 << 22)
THCITensor_(resize1d)(state, rulesBuffer, 1 << 22);
uInt *rb = (uInt *)THCITensor_(data)(state, rulesBuffer);
uInt rowBatchSize = std::min((uInt)32768, (1 << 22) / (maxActive + 1));
THAssert(rowBatchSize > 0);
......@@ -36,11 +37,12 @@ extern "C" void scn_DR_(ActivePooling_updateOutput)(
ActivePooling_ForwardPass<real>(iF, oF + o * nPlanes, batchSize_, maxActive,
nPlanes, rb, average);
}
THCITensor_(free)(state, rulesBuffer);
}
extern "C" void scn_DR_(ActivePooling_updateGradInput)(
THLongTensor *inputSize, void **m, THCTensor *input_features,
THCTensor *d_input_features, THCTensor *d_output_features,
THCITensor *rulesBuffer, bool average) {
bool average) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1];
auto _rules = _m.getActivePoolingRuleBook(inputSize);
......@@ -49,9 +51,10 @@ extern "C" void scn_DR_(ActivePooling_updateGradInput)(
THCTensor_(resizeAs)(state, d_input_features, input_features);
THCTensor_(zero)(state, d_input_features);
if (THCITensor_nElement(state, rulesBuffer) < 1 << 22)
THCITensor_resize1d(state, rulesBuffer, 1 << 22);
uInt *rb = (uInt *)THCITensor_data(state, rulesBuffer);
auto rulesBuffer = THCITensor_(new)(state);
if (THCITensor_(nElement)(state, rulesBuffer) < 1 << 22)
THCITensor_(resize1d)(state, rulesBuffer, 1 << 22);
uInt *rb = (uInt *)THCITensor_(data)(state, rulesBuffer);
uInt rowBatchSize = std::min((uInt)32768, (1 << 22) / (maxActive + 1));
THAssert(rowBatchSize > 0);
......@@ -65,5 +68,6 @@ extern "C" void scn_DR_(ActivePooling_updateGradInput)(
ActivePooling_BackwardPass<real>(diF, doF + o * nPlanes, batchSize_,
maxActive, nPlanes, rb, average);
}
THCITensor_(free)(state, rulesBuffer);
}
#endif
PyTorch/sparseconvnet/SCN/generic/GPU/AveragePooling.cu → sparseconvnet/SCN/generic/GPU/AveragePooling.cu
View file @ 1df7b845
......@@ -13,7 +13,7 @@
extern "C" void scn_DR_(AveragePooling_updateOutput)(
THLongTensor *inputSize, THLongTensor *outputSize, THLongTensor *poolSize,
THLongTensor *poolStride, void **m, THCTensor *input_features,
THCTensor *output_features, long nFeaturesToDrop, THCITensor *rulesBuffer) {
THCTensor *output_features, long nFeaturesToDrop) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1] - nFeaturesToDrop;
......@@ -37,7 +37,7 @@ extern "C" void scn_DR_(AveragePooling_updateGradInput)(
THLongTensor *inputSize, THLongTensor *outputSize, THLongTensor *poolSize,
THLongTensor *poolStride, void **m, THCTensor *input_features,
THCTensor *d_input_features, THCTensor *d_output_features,
long nFeaturesToDrop, THCITensor *rulesBuffer) {
long nFeaturesToDrop) {
SCN_INITIALIZE_AND_REFERENCE(Metadata<Dimension>, m)
uInt nPlanes = input_features->size[1] - nFeaturesToDrop;
......
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