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change outputsize func name

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emailweixu-patch-1
Yang Yang 7 years ago
parent 89ead8d151
commit cb06337f9e
7 changed files with 26 additions and 25 deletions
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5
paddle/fluid/operators/conv_op.cc
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@ -60,8 +60,9 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
"Due to the settings of paddings, filter_dims and "
"dilations, the output size is less than 0, please check "
"again.");
output_shape.push_back(OutputSize(in_dims[i + 2], filter_dims[i + 2],
dilations[i], paddings[i], strides[i]));
output_shape.push_back(ConvOutputSize(in_dims[i + 2], filter_dims[i + 2],
dilations[i], paddings[i],
strides[i]));
}
ctx->SetOutputDim("Output", framework::make_ddim(output_shape));
ctx->ShareLoD("Input", "Output");

4
paddle/fluid/operators/conv_op.h
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@ -28,8 +28,8 @@ using Tensor = framework::Tensor;
// Base convolution operator definations for other conv
// like operators to reuse the implementation.
inline int OutputSize(int input_size, int filter_size, int dilation,
int padding, int stride) {
inline int ConvOutputSize(int input_size, int filter_size, int dilation,
int padding, int stride) {
const int dkernel = dilation * (filter_size - 1) + 1;
const int output_size = (input_size + 2 * padding - dkernel) / stride + 1;
return output_size;

8
paddle/fluid/operators/im2sequence_op.cc
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@ -41,10 +41,10 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
int img_height = in_dim[2];
int img_width = in_dim[3];
int output_height = OutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]);
int output_width =
OutputSize(img_width, kernels[1], paddings[1], paddings[3], strides[1]);
int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]);
int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1],
paddings[3], strides[1]);
ctx->SetOutputDim("Out", {batch_size * output_height * output_width,
img_channels * kernels[0] * kernels[1]});

20
paddle/fluid/operators/im2sequence_op.h
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@ -26,8 +26,8 @@ namespace operators {
using Tensor = framework::Tensor;
using LoDTensor = framework::LoDTensor;
inline int OutputSize(int input_size, int filter_size, int padding_0,
int padding_1, int stride) {
inline int Im2SeqOutputSize(int input_size, int filter_size, int padding_0,
int padding_1, int stride) {
const int output_size =
(input_size + padding_0 + padding_1 - filter_size) / stride + 1;
return output_size;
@ -53,10 +53,10 @@ class Im2SequenceKernel : public framework::OpKernel<T> {
auto kernels = ctx.Attr<std::vector<int>>("kernels");
auto strides = ctx.Attr<std::vector<int>>("strides");
auto paddings = ctx.Attr<std::vector<int>>("paddings");
int output_height = OutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]);
int output_width =
OutputSize(img_width, kernels[1], paddings[1], paddings[3], strides[1]);
int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]);
int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1],
paddings[3], strides[1]);
const std::vector<int> dilations({1, 1});
@ -109,10 +109,10 @@ class Im2SequenceGradKernel : public framework::OpKernel<T> {
auto kernels = ctx.Attr<std::vector<int>>("kernels");
auto strides = ctx.Attr<std::vector<int>>("strides");
auto paddings = ctx.Attr<std::vector<int>>("paddings");
int output_height = OutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]);
int output_width =
OutputSize(img_width, kernels[1], paddings[1], paddings[3], strides[1]);
int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]);
int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1],
paddings[3], strides[1]);
const std::vector<int> dilations({1, 1});

4
paddle/fluid/operators/pool_op.cc
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@ -17,7 +17,7 @@ limitations under the License. */
namespace paddle {
namespace operators {
int OutputSizePool(int input_size, int filter_size, int padding, int stride) {
int PoolOutputSize(int input_size, int filter_size, int padding, int stride) {
int output_size = (input_size - filter_size + 2 * padding) / stride + 1;
return output_size;
}
@ -55,7 +55,7 @@ void PoolOp::InferShape(framework::InferShapeContext *ctx) const {
std::vector<int64_t> output_shape({in_x_dims[0], in_x_dims[1]});
for (size_t i = 0; i < ksize.size(); ++i) {
output_shape.push_back(
OutputSizePool(in_x_dims[i + 2], ksize[i], paddings[i], strides[i]));
PoolOutputSize(in_x_dims[i + 2], ksize[i], paddings[i], strides[i]));
}
ctx->SetOutputDim("Out", framework::make_ddim(output_shape));
ctx->ShareLoD("X", "Out");

4
paddle/fluid/operators/pool_with_index_op.cc
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@ -17,7 +17,7 @@ limitations under the License. */
namespace paddle {
namespace operators {
inline int OutputSizeMaxPool(int input_size, int filter_size, int padding,
inline int MaxPoolOutputSize(int input_size, int filter_size, int padding,
int stride) {
int output_size = (input_size - filter_size + 2 * padding) / stride + 1;
return output_size;
@ -61,7 +61,7 @@ class MaxPoolWithIndexOp : public framework::OperatorWithKernel {
std::vector<int64_t> output_shape({in_x_dims[0], in_x_dims[1]});
for (size_t i = 0; i < ksize.size(); ++i) {
output_shape.push_back(OutputSizeMaxPool(in_x_dims[i + 2], ksize[i],
output_shape.push_back(MaxPoolOutputSize(in_x_dims[i + 2], ksize[i],
paddings[i], strides[i]));
}
ctx->SetOutputDim("Out", framework::make_ddim(output_shape));

6
paddle/fluid/operators/unpool_op.cc
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@ -64,7 +64,7 @@ Paper: http://www.matthewzeiler.com/wp-content/uploads/2017/07/iccv2011.pdf
}
};
int OutputSize(int input_size, int ksize, int padding, int stride) {
int UnpoolOutputSize(int input_size, int ksize, int padding, int stride) {
int output_size = (input_size - 1) * stride - 2 * padding + ksize;
return output_size;
}
@ -101,8 +101,8 @@ class UnpoolOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_EQ(in_x_dims, in_y_dims);
std::vector<int64_t> output_shape({in_x_dims[0], in_x_dims[1]});
for (size_t i = 0; i < ksize.size(); ++i) {
output_shape.push_back(
OutputSize(in_x_dims[i + 2], ksize[i], paddings[i], strides[i]));
output_shape.push_back(UnpoolOutputSize(in_x_dims[i + 2], ksize[i],
paddings[i], strides[i]));
}
ctx->SetOutputDim("Out", framework::make_ddim(output_shape));
}

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