fix above comments

paddle/cuda/include/hl_matrix.h

@@ -244,12 +244,21 @@ extern void hl_matrix_rotate(
  * @param[out]   matDst     output matrix.
  *
  */
-extern void hl_matrix_vol2Col(real* matSrc,
-                 int channel, int depth, int height, int width,
-                 int filterD, int filterH, int filterW,
-                 int strideD, int strideH, int strideW,
-                 int paddingD, int paddingH, int paddingW,
-                 real* matDst);
+extern void hl_matrix_vol2Col(const real* dataSrc,
+                              int channels,
+                              int depth,
+                              int height,
+                              int width,
+                              int filterD,
+                              int filterH,
+                              int filterW,
+                              int strideD,
+                              int strideH,
+                              int strideW,
+                              int paddingD,
+                              int paddingH,
+                              int paddingW,
+                              real* dataDst);
 
 /**
  * @brief  Matrix col2Vol: Convert col matrix into 3D volume
@@ -273,13 +282,22 @@ extern void hl_matrix_vol2Col(real* matSrc,
  * @param[in]   alpha      input
  *
  */
-extern void hl_matrix_col2Vol(real* matDst,
-                int channels, int depth, int height, int width,
-                int filterD, int filterH, int filterW,
-                int strideD, int strideH, int strideW,
-                int paddingD, int paddingH, int paddingW,
-                real* matSrc,
-                real alpha, real beta);
-
+extern void hl_matrix_col2Vol(real* dataDst,
+                              int channels,
+                              int depth,
+                              int height,
+                              int width,
+                              int filterD,
+                              int filterH,
+                              int filterW,
+                              int strideD,
+                              int strideH,
+                              int strideW,
+                              int paddingD,
+                              int paddingH,
+                              int paddingW,
+                              const real* dataSrc,
+                              real alpha,
+                              real beta);
 
 #endif /* HL_MATRIX_H_ */

paddle/cuda/include/stub/hl_matrix_stub.h

@@ -99,19 +99,38 @@ inline void hl_matrix_collect_shared_bias(real* B_d,
 inline void hl_matrix_rotate(
     real* mat, real* matRot, int dimM, int dimN, bool clockWise) {}
 
-inline void hl_matrix_vol2Col(real* data,
-                       int channels, int depth, int height, int width,
-                       int filterD, int filterH, int filterW,
-                       int strideD, int strideH, int strideW,
-                       int paddingD, int paddingH, int paddingW,
-                       real* data_col) {}
-
-inline void hl_matrix_col2Vol(real* data,
-                       int channels, int depth, int height, int width,
-                       int filterD, int filterH, int filterW,
-                       int strideD, int strideH, int strideW,
-                       int paddingD, int paddingH, int paddingW,
-                       real* data_Im,
-                       real alpha, real beta) {}
+inline void hl_matrix_vol2Col(const real* dataSrc,
+                              int channels,
+                              int depth,
+                              int height,
+                              int width,
+                              int filterD,
+                              int filterH,
+                              int filterW,
+                              int strideD,
+                              int strideH,
+                              int strideW,
+                              int paddingD,
+                              int paddingH,
+                              int paddingW,
+                              real* dataDst) {}
+
+inline void hl_matrix_col2Vol(real* dataDst,
+                              int channels,
+                              int depth,
+                              int height,
+                              int width,
+                              int filterD,
+                              int filterH,
+                              int filterW,
+                              int strideD,
+                              int strideH,
+                              int strideW,
+                              int paddingD,
+                              int paddingH,
+                              int paddingW,
+                              const real* dataSrc,
+                              real alpha,
+                              real beta) {}
 
 #endif  // HL_MATRIX_STUB_H_

paddle/cuda/src/hl_cuda_matrix.cu

@@ -594,7 +594,7 @@ void hl_matrix_rotate(
 }
 
 __global__ void keMatrixVol2Col(int num_kernels,
-                                real* dataSrc,
+                                const real* dataSrc,
                                 real* dataDst,
                                 int depth,
                                 int height,
@@ -643,7 +643,7 @@ __global__ void keMatrixVol2Col(int num_kernels,
   }
 }
 
-void hl_matrix_vol2Col(real* dataSrc,
+void hl_matrix_vol2Col(const real* dataSrc,
                        int channels,
                        int depth,
                        int height,
@@ -666,7 +666,7 @@ void hl_matrix_vol2Col(real* dataSrc,
   const int threads = 512;
   const int blocks = DIVUP(num_kernels, threads);
 
-  keMatrixVol2Col<<<blocks, threads>>>(num_kernels,
+  keMatrixVol2Col<<<blocks, threads, 0, STREAM_DEFAULT>>>(num_kernels,
                                                           dataSrc,
                                                           dataDst,
                                                           depth,
@@ -689,7 +689,7 @@ void hl_matrix_vol2Col(real* dataSrc,
 
 __global__ void keMatrixCol2Vol(int num_kernels,
                                 real* dataDst,
-                                real* dataSrc,
+                                const real* dataSrc,
                                 int depth,
                                 int height,
                                 int width,
@@ -759,7 +759,7 @@ void hl_matrix_col2Vol(real* dataDst,
                        int paddingD,
                        int paddingH,
                        int paddingW,
-                       real* dataSrc,
+                       const real* dataSrc,
                        real alpha,
                        real beta) {
   int depth_col = (depth + 2 * paddingD - filterD) / strideD + 1;
@@ -770,7 +770,7 @@ void hl_matrix_col2Vol(real* dataDst,
   const int threads = 512;
   const int blocks = DIVUP(num_kernels, threads);
 
-  keMatrixCol2Vol<<<blocks, threads>>>(num_kernels,
+  keMatrixCol2Vol<<<blocks, threads, 0, STREAM_DEFAULT>>>(num_kernels,
                                                           dataDst,
                                                           dataSrc,
                                                           depth,

paddle/gserver/layers/Conv3DLayer.cpp

@@ -28,16 +28,26 @@ bool Conv3DLayer::init(const LayerMap &layerMap,
     const ConvConfig &conf = inputConfig.conv_conf();
     M_.push_back(numFilters_ / conf.groups());
     K_.push_back(filterPixels_[index] * filterChannels_[index]);
-    if (nullptr != weights_[index]->getW())
-      weights_[index]->getW()->reshape(weights_[index]->getW()->getWidth(),
-                                       weights_[index]->getW()->getHeight());
-    if (nullptr != weights_[index]->getWGrad())
-      weights_[index]->getWGrad()->reshape(
-          weights_[index]->getWGrad()->getWidth(),
-          weights_[index]->getWGrad()->getHeight());
+
+    // create a new weight
+    size_t height, width;
+    width = filterPixels_[index] * filterChannels_[index];
+    height = numFilters_;
+    CHECK_EQ(parameters_[index]->getSize(), width * height);
+    Weight *w = new Weight(height, width, parameters_[index]);
+    weights_.emplace_back(w);
     ++index;
   }
-  CHECK(inputLayers_.size() == parameters_.size());
+  if (biasParameter_.get()) {
+    if (sharedBiases_) {
+      CHECK_EQ((size_t)numFilters_, biasParameter_->getSize());
+      biases_ =
+          std::unique_ptr<Weight>(new Weight(1, numFilters_, biasParameter_));
+    } else {
+      biases_ =
+          std::unique_ptr<Weight>(new Weight(1, getSize(), biasParameter_));
+    }
+  }
   return true;
 }
 

paddle/gserver/layers/Conv3DLayer.h

@@ -12,13 +12,11 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-
 #pragma once
-
+#include <vector>
 #include "ConvBaseLayer.h"
-#include "paddle/math/Matrix.h"
 #include "paddle/math/MathUtils.h"
-#include <vector>
+#include "paddle/math/Matrix.h"
 
 namespace paddle {
 
@@ -30,21 +28,17 @@ namespace paddle {
 class Conv3DLayer : public ConvBaseLayer {
 public:
   explicit Conv3DLayer(const LayerConfig& config) : ConvBaseLayer(config) {}
-
   ~Conv3DLayer() {}
 
-  bool init(const LayerMap &layerMap, const ParameterMap &parameterMap);
-
-  size_t getSize();
+  bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
 
   void forward(PassType passType);
   void addBias();
-
   void backward(const UpdateCallback& callback);
-
   void bpropBiases();
   void bpropData(int i);
   void bpropWeights(int i);
+  size_t getSize();
 
 protected:
   // Figure out the dimensions for individual gemms.

paddle/gserver/layers/ConvBaseLayer.cpp

@@ -21,8 +21,7 @@ bool ConvBaseLayer::init(const LayerMap& layerMap,
                          const ParameterMap& parameterMap) {
   /* Initialize the basic parent class */
   Layer::init(layerMap, parameterMap);
-  isDeconv_ = (config_.type() == "exconv" || config_.type() == "cudnn_conv" ||
-               config_.type() == "conv3d" || config_.type() == "deconv3d")
+  isDeconv_ = (config_.type() == "exconv" || config_.type() == "cudnn_conv")
                   ? false
                   : true;
 
@@ -56,28 +55,9 @@ bool ConvBaseLayer::init(const LayerMap& layerMap,
   }
 
   CHECK(inputLayers_.size() == parameters_.size());
-  for (size_t i = 0; i < inputLayers_.size(); i++) {
-    size_t height, width;
-    height = filterPixels_[i] * filterChannels_[i];
-    width = (!isDeconv_) ? numFilters_ : channels_[i];
-
-    // create a new weight
-    CHECK_EQ(parameters_[i]->getSize(), width * height);
-    Weight* w = new Weight(height, width, parameters_[i]);
-    weights_.emplace_back(w);
-  }
 
-  /* initialize the biases_ */
-  if (biasParameter_.get()) {
-    if (sharedBiases_) {
-      CHECK_EQ((size_t)numFilters_, biasParameter_->getSize());
-      biases_ =
-          std::unique_ptr<Weight>(new Weight(1, numFilters_, biasParameter_));
-    } else {
-      biases_ =
-          std::unique_ptr<Weight>(new Weight(1, getSize(), biasParameter_));
-    }
-  }
+  // create new weights_ in derived class
+  // create new biases_ in derived class
 
   // default caffe model
   caffeMode_ = true;

paddle/gserver/layers/ConvBaseLayer.h

@@ -23,7 +23,6 @@ namespace paddle {
  * with learned filters and (optionally) adds biases.
  */
 
-
 class ConvBaseLayer : public Layer {
 protected:
   typedef std::vector<int> IntV;

paddle/gserver/layers/CudnnConvBaseLayer.cpp

@@ -46,8 +46,26 @@ bool CudnnConvBaseLayer::init(const LayerMap &layerMap,
     projConf_.emplace_back(conf);
     projections_.emplace_back(
         Projection::create(*projConf_[i], parameters_[i], useGpu_));
+
+    // create a new weight
+    size_t height, width;
+    height = filterPixels_[i] * filterChannels_[i];
+    width = (!isDeconv_) ? numFilters_ : channels_[i];
+    CHECK_EQ(parameters_[i]->getSize(), width * height);
+    Weight *w = new Weight(height, width, parameters_[i]);
+    weights_.emplace_back(w);
   }
 
+  if (biasParameter_.get()) {
+    if (sharedBiases_) {
+      CHECK_EQ((size_t)numFilters_, biasParameter_->getSize());
+      biases_ =
+          std::unique_ptr<Weight>(new Weight(numFilters_, 1, biasParameter_));
+    } else {
+      biases_ =
+          std::unique_ptr<Weight>(new Weight(getSize(), 1, biasParameter_));
+    }
+  }
   if (biases_.get() && sharedBiases_) {
     hl_create_tensor_descriptor(&biasDesc_);
     hl_create_tensor_descriptor(&outputDesc_);

paddle/gserver/layers/DeConv3DLayer.cpp

@@ -20,9 +20,6 @@ namespace paddle {
 
 REGISTER_LAYER(deconv3d, DeConv3DLayer);
 
-#define DECONV_OUTPUT_SIZE(IN_SIZE, STRID, PAD, KSIZE) \
-  (((IN_SIZE)-1) * (STRID)-2 * (PAD) + (KSIZE))
-
 bool DeConv3DLayer::init(const LayerMap &layerMap,
                          const ParameterMap &parameterMap) {
   if (!ConvBaseLayer::init(layerMap, parameterMap)) return false;
@@ -32,14 +29,25 @@ bool DeConv3DLayer::init(const LayerMap &layerMap,
   for (int index = 0; index < config_.inputs().size(); ++index) {
     M_.push_back(filterChannels_[index]);
     K_.push_back(filterPixels_[index] * (numFilters_ / groups_[index]));
-    if (weights_[index]->getW())
-      weights_[index]->getW()->reshape(filterPixels_[index] * numFilters_,
-                                       filterChannels_[index]);
-    if (weights_[index]->getWGrad())
-      weights_[index]->getWGrad()->reshape(filterPixels_[index] * numFilters_,
-                                           filterChannels_[index]);
-  }
-  CHECK(inputLayers_.size() == parameters_.size());
+
+    // create a new weight
+    size_t height, width;
+    height = filterPixels_[index] * numFilters_;
+    width = filterChannels_[index];
+    CHECK_EQ(parameters_[index]->getSize(), width * height);
+    Weight *w = new Weight(height, width, parameters_[index]);
+    weights_.emplace_back(w);
+  }
+  if (biasParameter_.get()) {
+    if (sharedBiases_) {
+      CHECK_EQ((size_t)numFilters_, biasParameter_->getSize());
+      biases_ =
+          std::unique_ptr<Weight>(new Weight(1, numFilters_, biasParameter_));
+    } else {
+      biases_ =
+          std::unique_ptr<Weight>(new Weight(1, getSize(), biasParameter_));
+    }
+  }
   return true;
 }
 
@@ -52,22 +60,22 @@ size_t DeConv3DLayer::getSize() {
   outputW_.clear();
   outputD_.clear();
   N_.clear();
-  No_.clear();
+  NOut_.clear();
   size_t layerSize = 0;
   for (size_t i = 0; i < inputLayers_.size(); ++i) {
     // imgSizeH_.push_back(inputLayers_[i]->getOutput().getFrameHeight());
     // imgSizeW_.push_back(inputLayers_[i]->getOutput().getFrameWidth());
     // imgSizeD_.push_back(inputLayers_[i]->getOutput().getFrameDepth());
-    outputW_.push_back(DECONV_OUTPUT_SIZE(
-        imgSizeW_[i], stride_[i], padding_[i], filterSize_[i]));
-    outputH_.push_back(DECONV_OUTPUT_SIZE(
-        imgSizeH_[i], strideY_[i], paddingY_[i], filterSizeY_[i]));
-    outputD_.push_back(DECONV_OUTPUT_SIZE(
-        imgSizeD_[i], strideZ_[i], paddingZ_[i], filterSizeZ_[i]));
-    No_.push_back(outputD_[i] * outputH_[i] * outputW_[i]);
+    outputW_.push_back(
+        imageSize(imgSizeW_[i], filterSize_[i], padding_[i], stride_[i], true));
+    outputH_.push_back(imageSize(
+        imgSizeH_[i], filterSizeY_[i], paddingY_[i], strideY_[i], true));
+    outputD_.push_back(imageSize(
+        imgSizeD_[i], filterSizeZ_[i], paddingZ_[i], strideZ_[i], true));
+    NOut_.push_back(outputD_[i] * outputH_[i] * outputW_[i]);
     N_.push_back(imgSizeD_[i] * imgSizeH_[i] * imgSizeW_[i]);
     CHECK(layerSize == 0 || N_[i] * size_t(numFilters_) == layerSize);
-    layerSize += No_[i] * numFilters_;
+    layerSize += NOut_[i] * numFilters_;
   }
   getOutput().setFrameHeight(outputH_[0]);
   getOutput().setFrameWidth(outputW_[0]);

paddle/gserver/layers/DeConv3DLayer.h

@@ -12,13 +12,12 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-
 #pragma once
 
+#include <vector>
 #include "ConvBaseLayer.h"
-#include "paddle/math/Matrix.h"
 #include "paddle/math/MathUtils.h"
-#include <vector>
+#include "paddle/math/Matrix.h"
 
 namespace paddle {
 
@@ -30,28 +29,23 @@ namespace paddle {
 class DeConv3DLayer : public ConvBaseLayer {
 public:
   explicit DeConv3DLayer(const LayerConfig& config) : ConvBaseLayer(config) {}
-
   ~DeConv3DLayer() {}
-
-    bool init(const LayerMap &layerMap, const ParameterMap &parameterMap);
-
-    size_t getSize();
+  bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
 
   void forward(PassType passType);
   void addBias();
-
   void backward(const UpdateCallback& callback);
-
   void bpropBiases();
   void bpropData(int i);
   void bpropWeights(int i);
+  size_t getSize();
 
 protected:
   // Figure out the dimensions for individual gemms.
   IntV M_;  /// numFilters_ / filter_group_;
   IntV N_;  /// channels_ * filterSizeZ_ * filterSize_ * filterSizeY_
   IntV K_;  /// outputD_ * outputH_ * outputW_
-    IntV No_;
+  IntV NOut_;
   MatrixPtr colBuf_;
 };
 

paddle/gserver/layers/ExpandConvBaseLayer.cpp

@@ -22,12 +22,31 @@ bool ExpandConvBaseLayer::init(const LayerMap &layerMap,
   /* Initialize the basic convolutional parent class */
   ConvBaseLayer::init(layerMap, parameterMap);
 
+  int index = 0;
   for (auto &inputConfig : config_.inputs()) {
     const ConvConfig &conf = inputConfig.conv_conf();
     /* Consistent caffe mode for multiple input */
     caffeMode_ = conf.caffe_mode();
-  }
 
+    // create a new weight
+    size_t height, width;
+    height = filterPixels_[index] * filterChannels_[index];
+    width = (!isDeconv_) ? numFilters_ : channels_[index];
+    CHECK_EQ(parameters_[index]->getSize(), width * height);
+    Weight *w = new Weight(height, width, parameters_[index]);
+    weights_.emplace_back(w);
+    index++;
+  }
+  if (biasParameter_.get()) {
+    if (sharedBiases_) {
+      CHECK_EQ((size_t)numFilters_, biasParameter_->getSize());
+      biases_ =
+          std::unique_ptr<Weight>(new Weight(numFilters_, 1, biasParameter_));
+    } else {
+      biases_ =
+          std::unique_ptr<Weight>(new Weight(getSize(), 1, biasParameter_));
+    }
+  }
   getOutputSize();
 
   return true;

paddle/gserver/tests/test_LayerGrad.cpp

@@ -2019,7 +2019,7 @@ void test3DConvLayer(const string& type, bool trans, bool useGpu) {
   const int CHANNELS = 3;
   const int IMAGE_SIZE = 9;
   const int IMAGE_SIZE_Y = 9;
-  const int IMAGE_SIZE_Z = 9;  //  2, 3, 5, 5, 5
+  const int IMAGE_SIZE_Z = 9;
 
   TestConfig config;
   config.biasSize = NUM_FILTERS;
@@ -2084,10 +2084,6 @@ TEST(Layer, test3DConvLayer) {
 #endif
 }
 
-int deConvOutputSize(int inSize, int kSize, int pad, int stride) {
-  return (inSize - 1) * stride - 2 * pad + kSize;
-}
-
 void test3DDeConvLayer(const string& type, bool trans, bool useGpu) {
   // filter size
   const int NUM_FILTERS = 6;
@@ -2126,16 +2122,21 @@ void test3DDeConvLayer(const string& type, bool trans, bool useGpu) {
   conv->set_img_size(IMAGE_SIZE);
   conv->set_img_size_y(IMAGE_SIZE_Y);
   conv->set_img_size_z(IMAGE_SIZE_Z);
-  conv->set_output_x(deConvOutputSize(
-      conv->img_size(), conv->filter_size(), conv->padding(), conv->stride()));
-  conv->set_output_y(deConvOutputSize(conv->img_size_y(),
+  conv->set_output_x(imageSize(conv->img_size(),
+                               conv->filter_size(),
+                               conv->padding(),
+                               conv->stride(),
+                               true));
+  conv->set_output_y(imageSize(conv->img_size_y(),
                                conv->filter_size_y(),
                                conv->padding_y(),
-                                      conv->stride_y()));
-  conv->set_output_z(deConvOutputSize(conv->img_size_z(),
+                               conv->stride_y(),
+                               true));
+  conv->set_output_z(imageSize(conv->img_size_z(),
                                conv->filter_size_z(),
                                conv->padding_z(),
-                                      conv->stride_z()));
+                               conv->stride_z(),
+                               true));
   config.layerConfig.set_size(conv->output_x() * conv->output_y() *
                               conv->output_z() * NUM_FILTERS);
   conv->set_groups(1);

paddle/math/tests/test_matrixCompare.cpp

@@ -18,6 +18,7 @@ limitations under the License. */
 
 #include <gtest/gtest.h>
 #include "TensorCheck.h"
+#include "paddle/math/MathUtils.h"
 #include "paddle/math/Matrix.h"
 #include "paddle/math/SparseMatrix.h"
 #include "paddle/testing/TestUtil.h"
@@ -1203,19 +1204,6 @@ TEST(Matrix, warpCTC) {
   }
 }
 
-int outputSizeCol2Vol(
-    int imageSize, int filterSize, int padding, int stride, bool caffeMode) {
-  int outputSize;
-  if (!caffeMode) {
-    outputSize =
-        (imageSize - filterSize + 2 * padding + stride - 1) / stride + 1;
-  } else {
-    outputSize = (imageSize - filterSize + 2 * padding) / stride + 1;
-  }
-  CHECK_GE(outputSize, 1);
-  return outputSize;
-}
-
 void testMatrixCol2Vol(int depth, int height, int width) {
   int channel = 3;
   int filterX = 3, filterY = 4, filterZ = 5;
@@ -1229,9 +1217,9 @@ void testMatrixCol2Vol(int depth, int height, int width) {
   cpuImage->randomizeUniform();
   gpuImage->copyFrom(*cpuImage);
 
-  int outD = outputSizeCol2Vol(depth, filterZ, padZ, strideZ, true);
-  int outH = outputSizeCol2Vol(height, filterY, padZ, strideY, true);
-  int outW = outputSizeCol2Vol(width, filterX, padZ, strideX, true);
+  int outD = outputSize(depth, filterZ, padZ, strideZ, true);
+  int outH = outputSize(height, filterY, padY, strideY, true);
+  int outW = outputSize(width, filterX, padX, strideX, true);
 
   int colBufHeight = channel * filterZ * filterY * filterX;
   int colBufWidth = outD * outH * outW;
@@ -1305,11 +1293,9 @@ void testMatrixCol2Vol(int depth, int height, int width) {
 }
 
 TEST(Matrix, col2Vol) {
-  for (auto depth : {9, 16, 64, 128}) {
-    for (auto height : {9, 11, 73, 128, 256}) {
-      for (auto width : {
-               9, 32, 100, 512,
-           }) {
+  for (auto depth : {9, 16, 64}) {
+    for (auto height : {9, 11, 128}) {
+      for (auto width : {9, 32, 128}) {
         VLOG(3) << "depth=" << depth << " height=" << height
                 << " width=" << width;
         testMatrixCol2Vol(depth, height, width);