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| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2016-06-20 10:40:18 -0800 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2016-06-20 12:00:45 -0700 |
| commit | 84f4e8f39e6480294bf27a481ebf17b9ab245a14 (patch) | |
| tree | 58e1301c7b33d325902a3620c4c2cba786012091 /tensorflow/core/kernels/depthwise_conv_grad_op.cc | |
| parent | 6a830d140fa034289faef0313caf32ccc05bf9c8 (diff) | |
Refactor Get2dOutputSizes/Get2dOutputSizesVerbose/Get3dOutputSizes to share a common 1-dimensional GetWindowedOutputSize/GetWindowedOutputSizeVerbose.
The output sizes and padding of each dimension of a windowed operation (such as convolution or pooling) are orthogonal and can be computed independently. We can simplify the code by providing a 1D size computation and calling it for each dimension.
Also remove special cases for 1x1 spatial convolutions in dimension calculations; they add complexity and are a case that the general code handles correctly.
In general, 2D convolutions and their gradients have a lot of shape calculation code that is duplicated for each spatial dimension. This CL is a step in the direction of treating spatial dimensions the same so we can share more code.
Change: 125360639
Diffstat (limited to 'tensorflow/core/kernels/depthwise_conv_grad_op.cc')
| -rw-r--r-- | tensorflow/core/kernels/depthwise_conv_grad_op.cc | 17 |
1 files changed, 7 insertions, 10 deletions
diff --git a/tensorflow/core/kernels/depthwise_conv_grad_op.cc b/tensorflow/core/kernels/depthwise_conv_grad_op.cc index 161c88d814..f9076cb903 100644 --- a/tensorflow/core/kernels/depthwise_conv_grad_op.cc +++ b/tensorflow/core/kernels/depthwise_conv_grad_op.cc @@ -79,16 +79,13 @@ typedef Eigen::GpuDevice GPUDevice; errors::InvalidArgument( \ label, ": depth_multiplier * in_depth not equal to out_depth")); \ const auto stride = strides_[1]; \ - int out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; \ - if (filter_cols == filter_rows && filter_rows == 1 && stride == 1) { \ - out_rows = input_rows; \ - out_cols = input_cols; \ - } else { \ - OP_REQUIRES_OK( \ - context, Get2dOutputSize(input_rows, input_cols, filter_rows, \ - filter_cols, stride, stride, padding_, \ - &out_rows, &out_cols, &pad_rows, &pad_cols)); \ - } \ + int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; \ + OP_REQUIRES_OK(context, \ + GetWindowedOutputSize(input_rows, filter_rows, stride, \ + padding_, &out_rows, &pad_rows)); \ + OP_REQUIRES_OK(context, \ + GetWindowedOutputSize(input_cols, filter_cols, stride, \ + padding_, &out_cols, &pad_cols)); \ OP_REQUIRES( \ context, output_rows == out_rows, \ errors::InvalidArgument( \ |