modify the format and delete useless comment

cblas_new
xzl 8 years ago
parent fc8aedb1de
commit c43f6936c0

@ -15,7 +15,6 @@ limitations under the License. */
#include "DepthwiseConvOp.h" #include "DepthwiseConvOp.h"
#include "ConvOp.h" #include "ConvOp.h"
#include "GemmFunctor.h" #include "GemmFunctor.h"
//#include "paddle/math/MemoryHandle.h"
namespace paddle { namespace paddle {
@ -28,6 +27,7 @@ public:
int outputChannels, int outputChannels,
int outputHeight, int outputHeight,
int outputWidth, int outputWidth,
int inputChannels,
int inputHeight, int inputHeight,
int inputWidth, int inputWidth,
int filterHeight, int filterHeight,
@ -114,7 +114,7 @@ public:
const TensorShape& output = outputs[0].shape(); const TensorShape& output = outputs[0].shape();
size_t batchSize = input[0]; size_t batchSize = input[0];
// size_t inputChannels = input[1]; size_t inputChannels = input[1];
size_t inputHeight = input[2]; size_t inputHeight = input[2];
size_t inputWidth = input[3]; size_t inputWidth = input[3];
size_t filterHeight = getFilterHeight(filter); size_t filterHeight = getFilterHeight(filter);
@ -134,6 +134,7 @@ public:
outputChannels, outputChannels,
outputHeight, outputHeight,
outputWidth, outputWidth,
inputChannels,
inputHeight, inputHeight,
inputWidth, inputWidth,
filterHeight, filterHeight,
@ -168,8 +169,6 @@ public:
CHECK_EQ(numInputs_, inputs.size()); CHECK_EQ(numInputs_, inputs.size());
CHECK_EQ(numOutputs_, outputs.size()); CHECK_EQ(numOutputs_, outputs.size());
check(inputs, outputs); check(inputs, outputs);
// Since the implementation of Col2ImFunctor is ADD_TO,
// this function only supports ADD_TO mode.
CHECK_EQ(outputs[0].getArgType(), ADD_TO); CHECK_EQ(outputs[0].getArgType(), ADD_TO);
const TensorShape& output = inputs[0].shape(); const TensorShape& output = inputs[0].shape();
const TensorShape& filter = inputs[1].shape(); const TensorShape& filter = inputs[1].shape();
@ -228,12 +227,11 @@ public:
} }
void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { void calc(const BufferArgs& inputs, const BufferArgs& outputs) override {
// CHECK_EQ(numInputs_, inputs.size()); CHECK_EQ(numInputs_, inputs.size());
// CHECK_EQ(numOutputs_, outputs.size()); CHECK_EQ(numOutputs_, outputs.size());
check(inputs, outputs); check(inputs, outputs);
const TensorShape& output = inputs[0].shape(); const TensorShape& output = inputs[0].shape();
const TensorShape& input = inputs[1].shape(); const TensorShape& input = inputs[1].shape();
// const TensorShape& multiplier = inputs[2].shape();
const TensorShape& filter = outputs[0].shape(); const TensorShape& filter = outputs[0].shape();
size_t batchSize = input[0]; size_t batchSize = input[0];

@ -29,6 +29,7 @@ namespace paddle {
* \param[in] outputChannels channels of outputData. * \param[in] outputChannels channels of outputData.
* \param[in] outputHeight height of outputData. * \param[in] outputHeight height of outputData.
* \param[in] outputWidth width of outputData. * \param[in] outputWidth width of outputData.
* \param[in] inputChannels channels of inputData.
* \param[in] inputHeight height of inputData. * \param[in] inputHeight height of inputData.
* \param[in] inputWidth width of inputData.. * \param[in] inputWidth width of inputData..
* \param[in] filterHeight height of filter. * \param[in] filterHeight height of filter.
@ -49,8 +50,9 @@ public:
int outputChannels, int outputChannels,
int outputHeight, int outputHeight,
int outputWidth, int outputWidth,
int inputChannels,
int inputHeight, int inputHeight,
int intputWidth, int inputWidth,
int filterHeight, int filterHeight,
int filterWidth, int filterWidth,
int strideH, int strideH,

@ -24,7 +24,7 @@ __global__
void ConvolutionDepthwiseForward(const int nthreads, void ConvolutionDepthwiseForward(const int nthreads,
const T* const inputData, const T* const filterData, const T* const inputData, const T* const filterData,
const int batchSize, const int outputChannels, const int outputHeight, const int batchSize, const int outputChannels, const int outputHeight,
const int outputWidth, const int inputHeight, const int inputWidth, const int outputWidth,const int inputChannels, const int inputHeight, const int inputWidth,
const int filterHeight, const int filterWidth, const int strideH, const int filterHeight, const int filterWidth, const int strideH,
const int strideW, const int paddingH, const int paddingW, const int strideW, const int paddingH, const int paddingW,
T* const outputData) { T* const outputData) {
@ -49,7 +49,7 @@ void ConvolutionDepthwiseForward(const int nthreads,
for (int kw = 0; kw < filterWidth; ++kw) { for (int kw = 0; kw < filterWidth; ++kw) {
const int h_in = -paddingH + h * strideH + kh; const int h_in = -paddingH + h * strideH + kh;
const int w_in = -paddingW + w * strideW + kw; const int w_in = -paddingW + w * strideW + kw;
const int offset = ((n * outputChannels + c) * inputHeight + h_in) const int offset = ((n * inputChannels + c) * inputHeight + h_in)
* inputWidth + w_in; * inputWidth + w_in;
value += (*weight) * inputData[offset]; value += (*weight) * inputData[offset];
++weight; ++weight;
@ -80,15 +80,15 @@ __global__
void ConvolutionDepthwiseInputBackward(const int nthreads, void ConvolutionDepthwiseInputBackward(const int nthreads,
const T* const top_diff, const T* const weight_data, const T* const top_diff, const T* const weight_data,
const int num, const int outputChannels, const int outputHeight, const int num, const int outputChannels, const int outputHeight,
const int outputWidth, const int inputHeight, const int inputWidth, const int outputWidth,const int inputChannels, const int inputHeight, const int inputWidth,
const int filterHeight, const int filterWidth, const int strideH, const int filterHeight, const int filterWidth, const int strideH,
const int strideW, const int paddingH, const int paddingW, const int strideW, const int paddingH, const int paddingW,
T* const bottom_diff) { T* const bottom_diff) {
int index = int index =
(blockIdx.x * gridDim.y + blockIdx.y) * blockDim.x + threadIdx.x; (blockIdx.x * gridDim.y + blockIdx.y) * blockDim.x + threadIdx.x;
if(index < nthreads) { if(index < nthreads) {
const int n = index / outputChannels / inputHeight / inputWidth; const int n = index / inputChannels / inputHeight / inputWidth;
const int c = (index / inputHeight / inputWidth) % outputChannels; const int c = (index / inputHeight / inputWidth) % inputChannels;
const int h = (index / inputWidth) % inputHeight; const int h = (index / inputWidth) % inputHeight;
const int w = index % inputWidth; const int w = index % inputWidth;
const T* weight = weight_data + c * filterHeight * filterWidth; const T* weight = weight_data + c * filterHeight * filterWidth;
@ -121,7 +121,7 @@ __global__
void ConvolutionDepthwiseFilterBackward(const int num_i, const int nthreads, void ConvolutionDepthwiseFilterBackward(const int num_i, const int nthreads,
const T* const top_diff, const T* const inputData, const T* const top_diff, const T* const inputData,
const int num, const int outputChannels, const int outputHeight, const int num, const int outputChannels, const int outputHeight,
const int outputWidth, const int inputHeight, const int inputWidth, const int outputWidth, const int inputChannels, const int inputHeight, const int inputWidth,
const int filterHeight, const int filterWidth, const int strideH, const int filterHeight, const int filterWidth, const int strideH,
const int strideW, const int paddingH, const int paddingW, const int strideW, const int paddingH, const int paddingW,
T* const buffer_data) { T* const buffer_data) {
@ -141,7 +141,7 @@ void ConvolutionDepthwiseFilterBackward(const int num_i, const int nthreads,
const int n = num_i; const int n = num_i;
const int top_offset = ((n * outputChannels + c) * outputHeight + h) const int top_offset = ((n * outputChannels + c) * outputHeight + h)
* outputWidth + w; * outputWidth + w;
const int bottom_offset = ((n * outputChannels + c) * inputHeight + h_in) const int bottom_offset = ((n * inputChannels + c) * inputHeight + h_in)
* inputWidth + w_in; * inputWidth + w_in;
buffer_data[index] = top_diff[top_offset] * inputData[bottom_offset]; buffer_data[index] = top_diff[top_offset] * inputData[bottom_offset];
} else { } else {
@ -159,6 +159,7 @@ public:
int outputChannels, int outputChannels,
int outputHeight, int outputHeight,
int outputWidth, int outputWidth,
int inputChannels,
int inputHeight, int inputHeight,
int inputWidth, int inputWidth,
int filterHeight, int filterHeight,
@ -186,6 +187,7 @@ public:
outputChannels, outputChannels,
outputHeight, outputHeight,
outputWidth, outputWidth,
inputChannels,
inputHeight, inputHeight,
inputWidth, inputWidth,
filterHeight, filterHeight,
@ -237,6 +239,7 @@ public:
outputChannels, outputChannels,
outputHeight, outputHeight,
outputWidth, outputWidth,
inputChannels,
inputHeight, inputHeight,
inputWidth, inputWidth,
filterHeight, filterHeight,
@ -290,6 +293,7 @@ public:
outputChannels, outputChannels,
outputHeight, outputHeight,
outputWidth, outputWidth,
inputChannels,
inputHeight, inputHeight,
inputWidth, inputWidth,
filterHeight, filterHeight,

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