From 91db457fc0f8409f5c05995482289d7386f3e986 Mon Sep 17 00:00:00 2001 From: chengduoZH Date: Wed, 18 Oct 2017 18:40:29 +0800 Subject: [PATCH] follow comments --- paddle/operators/conv3d_op.cc | 4 ++-- paddle/operators/conv3d_op.h | 22 ++++++++++++------- .../v2/framework/tests/test_conv3d_op.py | 10 ++------- 3 files changed, 18 insertions(+), 18 deletions(-) diff --git a/paddle/operators/conv3d_op.cc b/paddle/operators/conv3d_op.cc index 714cf8abbf5..f86ed86a502 100644 --- a/paddle/operators/conv3d_op.cc +++ b/paddle/operators/conv3d_op.cc @@ -87,11 +87,11 @@ Conv3DOpMaker::Conv3DOpMaker(framework::OpProto* proto, "The format of output tensor is also NCDHW."); AddAttr>("strides", "strides of convolution operator.") .SetDefault({1, 1, 1}); - AddAttr>("paddings", "paddings of convolution operator.") + AddAttr>("paddings", "The paddings of convolution operator.") .SetDefault({0, 0, 0}); AddAttr( "groups", - "group size of convolution operator. " + "The group size of convolution operator. " "Refer to grouped convolution in Alex Krizhevsky's paper: " "when group=2, the first half of the filters are only connected to the " "first half of the input channels, and the second half only connected " diff --git a/paddle/operators/conv3d_op.h b/paddle/operators/conv3d_op.h index 960d104877d..0bc06739679 100644 --- a/paddle/operators/conv3d_op.h +++ b/paddle/operators/conv3d_op.h @@ -93,10 +93,13 @@ class GemmConv3DKernel : public framework::OpKernel { Tensor col_matrix = col; col_matrix.Resize(col_matrix_shape); - framework::DDim input_shape = {input->dims()[1], input->dims()[2], - input->dims()[3], input->dims()[4]}; - framework::DDim filter_matrix_shape = {filter.dims()[0], - filter.numel() / filter.dims()[0]}; + framework::DDim input_shape = { + input->dims()[1], input->dims()[2], input->dims()[3], + input->dims()[4]}; // channel, depth, height, width + framework::DDim filter_matrix_shape = { + filter.dims()[0], + filter.numel() / filter.dims()[0]}; // filter_out_channel, + // filter_in_channel*filter_depth*filter_height*filter_width filter.Resize(filter_matrix_shape); framework::DDim output_matrix_shape = { @@ -177,15 +180,18 @@ class GemmConvGrad3DKernel : public framework::OpKernel { Tensor col_matrix = col; col_matrix.Resize(col_matrix_shape); - framework::DDim input_shape = {input->dims()[1], input->dims()[2], - input->dims()[3], input->dims()[4]}; + framework::DDim input_shape = { + input->dims()[1], input->dims()[2], input->dims()[3], + input->dims()[4]}; // channel, depth, height, width framework::DDim output_matrix_shape = {output_grad->dims()[1], output_grad->dims()[2] * output_grad->dims()[3] * output_grad->dims()[4]}; - framework::DDim filter_matrix_shape = {filter.dims()[0], - filter.numel() / filter.dims()[0]}; + framework::DDim filter_matrix_shape = { + filter.dims()[0], + filter.numel() / filter.dims()[0]}; // filter_out_channel, + // filter_in_channel*filter_depth*filter_height*filter_width filter.Resize(filter_matrix_shape); // convolution backward input operator: gemm + col2vol diff --git a/python/paddle/v2/framework/tests/test_conv3d_op.py b/python/paddle/v2/framework/tests/test_conv3d_op.py index e81f2a166ca..4e12b1a0c89 100644 --- a/python/paddle/v2/framework/tests/test_conv3d_op.py +++ b/python/paddle/v2/framework/tests/test_conv3d_op.py @@ -34,7 +34,7 @@ def conv3d_forward_naive(input, filter, group, conv_param): for k in range(sub_out_c): out[:, g * sub_out_c + k, d, i, j] = \ np.sum(input_pad_masked * f_sub[k, :, :, :, :], - axis=(1, 2, 3,4)) + axis=(1, 2, 3, 4)) return out @@ -65,7 +65,6 @@ class TestConv3dOp(OpTest): self.check_grad( set(['Input', 'Filter']), 'Output', max_relative_error=0.05) - def test_check_grad_no_filter(self): self.check_grad( ['Input'], 'Output', @@ -80,8 +79,6 @@ class TestConv3dOp(OpTest): no_grad_set=set(['Input'])) def init_test_case(self): - # self.groups = 1 - # self.op_type = "conv3d" self.pad = [0, 0, 0] self.stride = [1, 1, 1] self.input_size = [2, 3, 5, 5, 5] # NCDHW @@ -98,8 +95,6 @@ class TestConv3dOp(OpTest): class TestCase1(TestConv3dOp): def init_test_case(self): - # self.groups = 1 - # self.op_type = "conv3d" self.pad = [1, 1, 1] self.stride = [1, 1, 1] self.input_size = [2, 3, 5, 5, 5] # NCDHW @@ -114,7 +109,6 @@ class TestCase1(TestConv3dOp): self.op_type = "conv3d" -''' class TestWithGroup1(TestConv3dOp): def init_group(self): self.groups = 3 @@ -129,7 +123,7 @@ class TestWithGroup2(TestCase1): def init_op_type(self): self.op_type = "conv3d" -''' + if __name__ == '__main__': unittest.main() -- GitLab