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Conv refine (#20644)

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* add condition judgement for performance improvement test=develop

* add condition judgement for performance improvement test=develop

* refine code style test=develop
revert-20712-fix_depthwise_conv
wangchaochaohu 6 years ago committed by GitHub
parent 57b656f956
commit 7783d3bd43
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GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 32 additions and 28 deletions
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60
paddle/fluid/operators/conv_cudnn_op.cu
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@ -540,23 +540,25 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
workspace_size);
}
std::vector<int> starts(transformed_input_channel.dims().size(), 0);
std::vector<int> axes(transformed_input_channel.dims().size(), 0);
if (!is_sys_pad) {
std::vector<int> starts(transformed_input_channel.dims().size(), 0);
std::vector<int> axes(transformed_input_channel.dims().size(), 0);
for (size_t i = 0; i < transformed_input_channel.dims().size(); ++i) {
starts[i] = input_pad[2 * i];
axes[i] = i;
}
for (size_t i = 0; i < transformed_input_channel.dims().size(); ++i) {
starts[i] = input_pad[2 * i];
axes[i] = i;
}
transformed_input_grad_channel.mutable_data(ctx.GetPlace());
if (transformed_input_channel.dims().size() == 4) {
Slice_2<paddle::platform::CUDADeviceContext, T, 4>(
ctx, &transformed_input_grad, &transformed_input_grad_channel,
starts, axes);
} else {
Slice_2<paddle::platform::CUDADeviceContext, T, 5>(
ctx, &transformed_input_grad, &transformed_input_grad_channel,
starts, axes);
transformed_input_grad_channel.mutable_data(ctx.GetPlace());
if (transformed_input_channel.dims().size() == 4) {
Slice_2<paddle::platform::CUDADeviceContext, T, 4>(
ctx, &transformed_input_grad, &transformed_input_grad_channel,
starts, axes);
} else {
Slice_2<paddle::platform::CUDADeviceContext, T, 5>(
ctx, &transformed_input_grad, &transformed_input_grad_channel,
starts, axes);
}
}
if (channel_last) {
@ -982,20 +984,22 @@ class CUDNNConvDoubleGradOpKernel : public framework::OpKernel<T> {
workspace_size);
}
// reverse padded input
std::vector<int> starts(X->dims().size(), 0);
std::vector<int> axes(X->dims().size(), 0);
if (!is_sys_pad) {
// reverse padded input
std::vector<int> starts(X->dims().size(), 0);
std::vector<int> axes(X->dims().size(), 0);
for (size_t i = 0; i < X->dims().size(); ++i) {
starts[i] = input_pad[2 * i];
axes[i] = i;
}
if (X->dims().size() == 4) {
Slice_2<paddle::platform::CUDADeviceContext, T, 4>(
ctx, &transformed_dX, &transformed_dX_channel, starts, axes);
} else {
Slice_2<paddle::platform::CUDADeviceContext, T, 5>(
ctx, &transformed_dX, &transformed_dX_channel, starts, axes);
for (size_t i = 0; i < X->dims().size(); ++i) {
starts[i] = input_pad[2 * i];
axes[i] = i;
}
if (X->dims().size() == 4) {
Slice_2<paddle::platform::CUDADeviceContext, T, 4>(
ctx, &transformed_dX, &transformed_dX_channel, starts, axes);
} else {
Slice_2<paddle::platform::CUDADeviceContext, T, 5>(
ctx, &transformed_dX, &transformed_dX_channel, starts, axes);
}
}
if (channel_last) {
TransToChannelLast<paddle::platform::CUDADeviceContext, T>(

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