diff --git a/paddle/operators/deconv2d_op.cc b/paddle/operators/conv2dtranspose_op.cc similarity index 93% rename from paddle/operators/deconv2d_op.cc rename to paddle/operators/conv2dtranspose_op.cc index 98a47f02b417ae51aa066a614ef600fa80782243..c1b231906e2f172b6f9cee55f850d1a5ec6c3221 100644 --- a/paddle/operators/deconv2d_op.cc +++ b/paddle/operators/conv2dtranspose_op.cc @@ -12,8 +12,7 @@ See the License for the specific language governing permissions and limitations under the License. */ -#include "paddle/operators/deconv2d_op.h" -#include "paddle/operators/conv2d_op.h" +#include "paddle/operators/conv2dtranspose_op.h" namespace paddle { namespace operators { @@ -54,18 +53,18 @@ Conv2DTransposeOpMaker::Conv2DTransposeOpMaker( : OpProtoAndCheckerMaker(proto, op_checker) { AddInput( "Input", - "The input tensor of convolution transpose operator. " + "(Tensor) The input tensor of convolution transpose operator. " "The format of input tensor is NCHW. Where N is batch size, C is the " "number of input channels, H and W is the height and width of image."); AddInput("Filter", - "The filter tensor of convolution transpose operator." + "(Tensor) The filter tensor of convolution transpose operator." "The format of the filter tensor is CMHW, where C is the number of " "output image channels, M is the number of input image channels, " "H and W is height and width of filter. " "We enforce groups number == 1 and padding == 0 in " "convolution transpose Scenario."); AddOutput("Output", - "The output tensor of convolution transpose operator." + "(Tensor) The output tensor of convolution transpose operator." "The format of output tensor is also NCHW."); AddAttr>("strides", "strides of convolution transpose operator.") diff --git a/paddle/operators/deconv2d_op.cu b/paddle/operators/conv2dtranspose_op.cu similarity index 94% rename from paddle/operators/deconv2d_op.cu rename to paddle/operators/conv2dtranspose_op.cu index 660ec32e353f8b340fdca409ca1d57dfb4601f45..761bc1959e69be94f43571728e6b92a322558b99 100644 --- a/paddle/operators/deconv2d_op.cu +++ b/paddle/operators/conv2dtranspose_op.cu @@ -12,7 +12,7 @@ See the License for the specific language governing permissions and limitations under the License. */ -#include "paddle/operators/deconv2d_op.h" +#include "paddle/operators/conv2dtranspose_op.h" namespace ops = paddle::operators; diff --git a/paddle/operators/deconv2d_op.h b/paddle/operators/conv2dtranspose_op.h similarity index 94% rename from paddle/operators/deconv2d_op.h rename to paddle/operators/conv2dtranspose_op.h index 91bf6193b210c17071c798888fe518994f1760c8..293b7ce9ba9454e50ca14eb947de293de0bb56ff 100644 --- a/paddle/operators/deconv2d_op.h +++ b/paddle/operators/conv2dtranspose_op.h @@ -14,7 +14,6 @@ limitations under the License. */ #pragma once -#include "glog/logging.h" #include "paddle/framework/eigen.h" #include "paddle/framework/op_registry.h" #include "paddle/operators/math/im2col.h" @@ -62,7 +61,8 @@ class GemmConv2DTransposeKernel : public framework::OpKernel { std::vector strides = context.Attr>("strides"); - // no paddings and groups allowed in deconv + // TODO(Zhuoyuan): Paddings can be added in future. + // groups will alway be disabled in conv2dtranspose. const int batch_size = input->dims()[0]; const int m = input->dims()[1]; @@ -91,7 +91,8 @@ class GemmConv2DTransposeKernel : public framework::OpKernel { // col_matrix shares the same piece of data with col, // but will be reshaped into a two-dimensional matrix shape // to call the matrix multiplication interface. - Tensor col_matrix = col; + Tensor col_matrix; + col_matrix.ShareDataWith(col); col_matrix.Resize(col_matrix_shape); DDim output_shape = {c, o_h, o_w}; @@ -100,7 +101,7 @@ class GemmConv2DTransposeKernel : public framework::OpKernel { DDim filter_matrix_shape = {m, c * k_h * k_w}; filter.Resize(filter_matrix_shape); - // deconvolution: gemm + col2im (similar to conv-backward on input) + // convolution transpose: gemm + col2im (similar to conv-backward on input) output->mutable_data(context.GetPlace()); auto t = framework::EigenVector::Flatten(*output); @@ -142,7 +143,7 @@ class GemmConv2DTransposeGradKernel : public framework::OpKernel { context.Output(framework::GradVarName("Filter")); std::vector strides = context.Attr>("strides"); - // Actually, no paddings and groups allowed in deconv. + // Actually, no paddings and groups allowed in conv transpose. std::vector paddings = context.Attr>("paddings"); const int batch_size = input->dims()[0]; @@ -180,11 +181,12 @@ class GemmConv2DTransposeGradKernel : public framework::OpKernel { DDim filter_matrix_shape = {m, c * k_h * k_w}; filter.Resize(filter_matrix_shape); - // deconvolution grad on input: + // convolution transpose grad on input: // im2col + gemm (similar to conv-forward) // input need to compute gradient if (input_grad) { - Tensor col_matrix = col; + Tensor col_matrix; + col_matrix.ShareDataWith(col); DDim col_matrix_shape = {c * k_h * k_w, h * w}; col_matrix.Resize(col_matrix_shape); @@ -216,7 +218,8 @@ class GemmConv2DTransposeGradKernel : public framework::OpKernel { // filter gradient required if (filter_grad) { - Tensor col_matrix_f = col; + Tensor col_matrix_f; + col_matrix_f.ShareDataWith(col); DDim col_matrix_shape_f = {c * h * w, k_h * k_w}; col_matrix_f.Resize(col_matrix_shape_f); diff --git a/python/paddle/v2/framework/tests/test_deconv_op.py b/python/paddle/v2/framework/tests/test_conv2dtranspose_op.py similarity index 84% rename from python/paddle/v2/framework/tests/test_deconv_op.py rename to python/paddle/v2/framework/tests/test_conv2dtranspose_op.py index c3baea8048636a1768ddfd54f59c09edd2798249..71ca262f00378381d2d65e87d198d6b1755e9a2b 100644 --- a/python/paddle/v2/framework/tests/test_deconv_op.py +++ b/python/paddle/v2/framework/tests/test_conv2dtranspose_op.py @@ -3,14 +3,14 @@ import numpy as np from op_test import OpTest -def deconv2d_forward_naive(input_, filter_, deconv_param): +def conv2dtranspose_forward_naive(input_, filter_, conv2dtranspose_param): # [2, 3, 5, 5] in_n, in_c, in_h, in_w = input_.shape # [3, 6, 3, 3] f_c, out_c, f_h, f_w = filter_.shape assert in_c == f_c - stride, pad = deconv_param['stride'], deconv_param['pad'] + stride, pad = conv2dtranspose_param['stride'], conv2dtranspose_param['pad'] out_h = (in_h - 1) * stride[0] + f_h out_w = (in_w - 1) * stride[1] + f_w @@ -32,18 +32,19 @@ def deconv2d_forward_naive(input_, filter_, deconv_param): return out -class TestDeconv2dOp(OpTest): +class TestConv2dTransposeOp(OpTest): def setUp(self): - # init as deconv + # init as conv transpose self.init_op_type() # [2, 3, 5, 5] -> kernel [3, 6, 3, 3] -> output [2, 6, 7, 7] self.init_test_case() - deconv2d_param = {'stride': self.stride, 'pad': self.pad} + conv2dtranspose_param = {'stride': self.stride, 'pad': self.pad} input_ = np.random.random(self.input_size).astype("float32") filter_ = np.random.random(self.filter_size).astype("float32") - output = deconv2d_forward_naive(input_, filter_, deconv2d_param) + output = conv2dtranspose_forward_naive(input_, filter_, + conv2dtranspose_param) # print 'deconv output py', output, output.shape self.inputs = {'Input': input_, 'Filter': filter_} @@ -85,7 +86,7 @@ class TestDeconv2dOp(OpTest): self.filter_size = [f_c, 6, 3, 3] def init_op_type(self): - self.op_type = "deconv2d" + self.op_type = "conv2dtranspose" """