| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| api_def_Conv3DBackpropFilter.pbtxt | 19 Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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| api_def_Conv3DBackpropInput.pbtxt | 19 Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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| api_def_ExtractImagePatches.pbtxt | 12 4-D Tensor with shape `[batch, out_rows, out_cols, ksize_rows *
15 `out_rows` and `out_cols` are the dimensions of the output patches.
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| api_def_Conv3DBackpropFilterV2.pbtxt | 21 Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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| api_def_Conv3DBackpropInputV2.pbtxt | 21 Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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| /external/tensorflow/tensorflow/python/framework/ |
| common_shapes.py | 166 out_cols, depth_out], where out_rows and out_cols depend on the
213 out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, filter_rows,
217 output_shape = [batch_size, out_rows, out_cols, depth_out]
235 out_cols, depth_in*depthwise_multiplier], where out_rows and out_cols depend
274 out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, filter_rows,
278 return [tensor_shape.TensorShape([batch_size, out_rows, out_cols, depth_out])]
295 out_cols, depth_out], where out_rows and out_cols depend on th
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| deep_conv2d.h | 80 int out_cols; member in struct:tensorflow::Conv2DArgs
93 out_cols(0),
102 int out_rows, int out_cols);
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| depthwise_conv_op.cc | 93 const int64 base_output_index = (out_r * args.out_cols + out_c) * out_depth;
192 args.out_rows * args.out_cols * args.out_depth;
213 for (int64 out_c = 0; out_c < args.out_cols; ++out_c) {
235 const int64 shard_cost = kCostMultiplier * args.out_cols * args.out_depth;
341 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; variable
347 padding_, &out_cols, &pad_cols));
349 ShapeFromFormat(data_format_, batch, out_rows, out_cols, out_depth);
366 << out_rows << ", " << out_cols << ", " << out_depth << "]";
396 args.out_cols = out_cols;
[all...] |
| dilation_ops.cc | 68 int64* out_rows, int64* out_cols) {
111 padding, out_cols, pad_left));
129 int64 out_rows = 0, out_cols = 0; variable
132 &out_cols);
135 // [ batch, out_rows, out_cols, depth ]
138 const std::vector<int64> out_sizes = {batch, out_rows, out_cols, depth};
228 int64 out_rows = 0, out_cols = 0; variable
231 &out_cols);
234 // [ batch, out_rows, out_cols, depth ]
240 out_cols == out_backprop.dim_size(2) &
348 int64 out_rows = 0, out_cols = 0; variable
[all...] |
| conv_ops.cc | 139 int /*out_cols*/, int /*out_depth*/, int /*dilation_rows*/,
155 int out_cols, int out_depth, int dilation_rows,
161 in_depth, out_depth, out_rows, out_cols)) {
175 args.out_cols = out_cols;
196 int out_cols, int out_depth, int stride_rows, int stride_cols,
210 int out_cols, int out_depth, int dilation_rows,
373 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; variable
379 stride_cols, padding_, &out_cols, &pad_cols));
381 ShapeFromFormat(data_format_, batch, out_rows, out_cols, out_depth)
566 const int64 out_cols = GetTensorDim(*output, data_format, 'W'); local
[all...] |
| depthwise_conv_grad_op.cc | 112 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; \
118 padding_, &out_cols, &pad_cols)); \
125 context, output_cols == out_cols, \
128 "actual = ", output_cols, ", computed = ", out_cols)); \
141 args.out_cols = out_cols; \
148 << ", output: [" << batch << ", " << out_rows << ", " << out_cols \
162 // 'out_backprop': [batch, out_rows, out_cols, out_depth]
190 const int64 out_cols = args.out_cols; local
[all...] |
| extract_image_patches_op.cc | 86 int64 out_rows = 0, out_cols = 0; variable
93 padding_, &out_cols, &pad_cols));
95 const std::vector<int64> out_sizes = {batch, out_rows, out_cols,
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| deep_conv2d.cc | 50 int out_depth, int out_rows, int out_cols) {
66 const int64 col_tiles = (out_cols + out_tile_cols - 1) / out_tile_cols;
75 int out_depth, int out_rows, int out_cols) {
76 return filter_rows * filter_cols * in_depth * out_depth * out_rows * out_cols;
99 int out_rows, int out_cols) {
117 t.output_shape().cols, in_depth, out_depth, out_rows, out_cols);
119 filter_rows, filter_cols, in_depth, out_depth, out_rows, out_cols);
732 // [out_rows, out_cols, out_depth]
799 out_c_start < 0 || out_c_start >= args.out_cols) {
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| pooling_ops_3d_sycl.h | 35 const int out_rows, const int out_cols,
52 out_cols_(out_cols),
126 const int out_rows, const int out_cols,
133 out_cols, window, stride, padding),
188 const int out_cols = GetTensorDim(*output, data_format, '2'); local
208 out_planes, out_rows, out_cols, window, stride,
532 const int out_rows, const int out_cols,
539 out_cols, window, stride, padding),
594 const int out_cols = GetTensorDim(*output, data_format, '2'); local
614 out_planes, out_rows, out_cols, window, stride
[all...] |
| fractional_avg_pool_op.cc | 246 const int64 out_cols = out_backprop.dim_size(2); variable
277 out_cols * out_rows * out_batch);
288 for (int64 c = 0; c < out_cols; ++c) {
296 const int64 out_index = (b * out_rows + r) * out_cols + c;
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| quantized_conv_ops.cc | 540 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; variable
546 padding_, &out_cols, &pad_cols));
549 CHECK_GT(out_cols, 0);
551 TensorShape out_shape({batch, out_rows, out_cols, out_depth});
554 // [ in_batch, out_rows, out_cols, out_depth ]
564 padding_, output->flat<T3>().data(), out_rows, out_cols,
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| conv_ops_using_gemm.cc | 520 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; variable
526 padding_, &out_cols, &pad_cols));
528 ShapeFromFormat(data_format_, batch, out_rows, out_cols, out_depth);
531 // [ in_batch, out_rows, out_cols, out_depth ]
552 output->flat<T>().data(), out_rows, out_cols);
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| mkl_conv_ops.cc | 174 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; variable
180 padding_, &out_cols, &pad_cols));
182 ShapeFromFormat(data_format_, batch, out_rows, out_cols, out_depth);
185 // [ in_batch, out_rows, out_cols, out_depth ]
218 mkl_context.out_sizes[MklDims::W] = static_cast<size_t>(out_cols);
[all...] |
| depthwise_conv_op_gpu.cu.cc | 45 args.in_cols == args.out_cols && args.pad_rows >= 0 &&
58 args.in_cols == args.out_cols && args.pad_rows >= 0 &&
88 const int out_width = args.out_cols;
324 const int out_width = args.out_cols;
626 const int num_outputs = args.out_rows * args.out_cols * block_count;
698 args.batch * args.out_rows * args.out_cols * args.out_depth;
[all...] |
| depthwise_conv_op.h | 40 int out_cols; member in struct:tensorflow::DepthwiseArgs
55 out_cols(0),
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| conv_ops_3d.cc | 189 int64 out_cols = GetTensorDim(*output, data_format, '2'); local
197 0, (out_cols - 1) * strides[2] + filter_cols - in_cols);
321 .set_spatial_dim(DimIndex::X, out_cols)
357 {{out_planes, out_rows, out_cols}}, out_depth),
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| mkl_conv_ops.h | 241 int64 out_rows = 0, out_cols = 0; local
249 &out_cols, &pad_left, &pad_right));
253 ShapeFromFormat(data_format_, out_batch, out_rows, out_cols, out_depth);
261 mkldnn_sizes[MklDnnDims::Dim_W] = static_cast<int>(out_cols);
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| /external/tensorflow/tensorflow/core/kernels/neon/ |
| neon_depthwise_conv_op.cc | 90 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; variable
96 padding_, &out_cols, &pad_cols));
97 TensorShape out_shape({batch, out_rows, out_cols, out_depth});
105 // [ in_batch, out_rows, out_cols, out_depth ]
115 << out_rows << ", " << out_cols << ", " << out_depth << "]";
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| /external/tensorflow/tensorflow/core/grappler/costs/ |
| utils_test.cc | 65 int out_cols = 9; local
81 CreateConstOp("output_backprop", {batch, out_rows, out_cols, out_depth},
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| /external/trappy/trappy/ |
| thermal.py | 275 out_cols = [s for s in self.data_frame.columns
279 plot_dfr = self.data_frame[out_cols]
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