Searched refs:ksize_rows (Results 1 – 5 of 5) sorted by relevance
| /external/tensorflow/tensorflow/core/kernels/ |
| D | extract_image_patches_op.cc | 74 const int ksize_rows = ksizes_[1]; in Compute() local
83 const int ksize_rows_eff = ksize_rows + (ksize_rows - 1) * (rate_rows - 1); in Compute()
96 ksize_rows * ksize_cols * depth}; in Compute()
108 context->eigen_device<Device>(), input.tensor<T, 4>(), ksize_rows, in Compute()
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| D | extract_volume_patches_op.cc | 82 const int ksize_rows = ksizes_[2]; in Compute() local
115 GetWindowedOutputSize(in_rows, ksize_rows, stride_rows, in Compute()
123 ksize_planes * ksize_rows * ksize_cols * depth}; in Compute()
136 ksize_rows, ksize_cols, stride_planes, stride_rows, stride_cols, in Compute()
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_ExtractVolumePatches.pbtxt | 13 ksize_planes * ksize_rows * ksize_cols * depth]` containing patches
14 with size `ksize_planes x ksize_rows x ksize_cols x depth` vectorized
40 ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]
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| D | api_def_ExtractImagePatches.pbtxt | 12 4-D Tensor with shape `[batch, out_rows, out_cols, ksize_rows *
14 `ksize_rows x ksize_cols x depth` vectorized in the "depth" dimension. Note
50 ksizes = [1, ksize_rows, ksize_cols, 1]
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| /external/tensorflow/tensorflow/core/ops/ |
| D | array_ops.cc | 2456 int32 ksize_rows = ksizes[1]; in __anondb9326b23902() local
2465 int32 ksize_rows_eff = ksize_rows + (ksize_rows - 1) * (rate_rows - 1); in __anondb9326b23902()
2473 c->Dim(input_shape, 3), ksize_rows * ksize_cols, &output_depth_dim)); in __anondb9326b23902()
2552 int32 ksize_rows = ksizes[2]; in __anondb9326b23a02() local
2576 ksize_planes * ksize_rows * ksize_cols, in __anondb9326b23a02()
2600 in_rows, ksize_rows, stride_rows, padding, &output_rows, in __anondb9326b23a02()
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