Searched refs:filter_planes (Results 1 – 5 of 5) sorted by relevance
| /external/tensorflow/tensorflow/core/kernels/ |
| D | eigen_benchmark_cpu_test.cc | 253 int filter_planes) { in CuboidConvolution() argument
263 filter_height, filter_width, filter_planes, input_depth, filter_count); in CuboidConvolution()
270 (input_depth * filter_height * filter_width * filter_planes); in CuboidConvolution()
282 int filter_width, int filter_planes) { in CuboidConvolutionBackwardInput() argument
292 filter_height, filter_width, filter_planes, input_depth, filter_count); in CuboidConvolutionBackwardInput()
298 (input_depth * filter_height * filter_width * filter_planes); in CuboidConvolutionBackwardInput()
310 int filter_width, int filter_planes) { in CuboidConvolutionBackwardKernel() argument
320 filter_height, filter_width, filter_planes, input_depth, filter_count); in CuboidConvolutionBackwardKernel()
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| D | conv_ops_3d.cc | 228 const int64 filter_planes = filter.dim_size(0); in launch() local
241 0, (out_planes - 1) * strides[0] + filter_planes - in_planes); in launch()
251 if (!is_grouped_convolution && filter_planes == 1 && filter_rows == 1 && in launch()
278 } else if (!is_grouped_convolution && filter_planes == in_planes && in launch()
414 .set_spatial_dim(DimIndex::Z, filter_planes) in launch()
487 {{filter_planes, filter_rows, filter_cols}}, in launch()
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| D | eigen_benchmark.h | 263 Eigen::Index filter_planes = filter_dims[2]; in CuboidConvolutionBackwardKernel() local
281 input, output_backward, filter_planes, filter_rows, filter_cols); in CuboidConvolutionBackwardKernel()
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| /external/tensorflow/tensorflow/core/kernels/mkl/ |
| D | mkl_conv_ops.h | 258 int filter_planes = in GetFilterSizeInMklOrder() local
274 mkldnn_sizes[MklDnnDims3D::Dim3d_D] = filter_planes; in GetFilterSizeInMklOrder()
349 int filter_planes, filter_rows, filter_cols; variable
354 filter_planes = filter_shape.dim_size(TF_3DFILTER_DIM_P);
421 input_planes, filter_planes, dilation_planes,
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | conv_ops_3d_test.py | 468 filter_planes, filter_rows, filter_cols = filter_shape
472 filter_planes, filter_rows, filter_cols, in_depth, out_depth
482 math.ceil((input_planes - filter_planes + 1.0) / strides[1]))
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