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Searched refs:output_window_dims (Results 1 – 5 of 5) sorted by relevance

/external/tensorflow/tensorflow/compiler/xla/service/
Dshape_inference.cc2455 if (!c_is_sorted(dim_numbers.output_window_dims())) { in ValidateGatherDimensionNumbers()
2458 Join(dim_numbers.output_window_dims(), ", ").c_str()); in ValidateGatherDimensionNumbers()
2461 if (c_adjacent_find(dim_numbers.output_window_dims()) != in ValidateGatherDimensionNumbers()
2462 dim_numbers.output_window_dims().end()) { in ValidateGatherDimensionNumbers()
2465 Join(dim_numbers.output_window_dims(), ", ").c_str()); in ValidateGatherDimensionNumbers()
2473 int64 window_index = dim_numbers.output_window_dims(i); in ValidateGatherDimensionNumbers()
2592 Join(gather_dim_numbers.output_window_dims(), ",").c_str(), in InferGatherShape()
2627 c_binary_search(gather_dim_numbers.output_window_dims(), i); in InferGatherShape()
Dhlo_instruction.cc1173 tensorflow::gtl::ArraySlice<int64> output_window_dims, in MakeGatherDimNumbers() argument
1177 for (int64 output_window_dim : output_window_dims) { in MakeGatherDimNumbers()
3363 string output_window_dims = in GatherDimensionNumbersToString() local
3365 Join(gather_dimension_numbers_->output_window_dims(), ","), "}"); in GatherDimensionNumbersToString()
3374 {output_window_dims, elided_window_dims, gather_dims_to_operand_dims}, in GatherDimensionNumbersToString()
Dhlo_instruction.h503 tensorflow::gtl::ArraySlice<int64> output_window_dims,
/external/tensorflow/tensorflow/docs_src/performance/xla/
Doperation_semantics.md1041 <b> `gather(operand, gather_indices, output_window_dims, elided_window_dims, window_bounds, gather_…
1051 |`output_window_dims` | `ArraySlice<int64>` | The set of dimensions in the |
1064 : : : `output_window_dims`) and the window :
1085 composed of the values in `Out` at dimensions `output_window_dims`, embedded
1091 The output is a tensor of rank `output_window_dims.size` + `gather_indices.rank`
1094 `output_window_dims`, in ascending order. E.g. if the output tensor has rank 5,
1095 `output_window_dims` is {`2`, `4`} then `output_gather_dims` is {`0`, `1`, `3`}
1103 2. If `i` is present in `output_window_dims` (i.e. equal to
1104 `output_window_dims[k]` for some `k`) then we pick the corresponding bound
1125 `k` < `output_window_dims.size` (`window_dims_to_operand_dims` is
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/external/tensorflow/tensorflow/compiler/xla/
Dxla_data.proto413 // else Out[output_window_dims[i++]]
414 repeated int64 output_window_dims = 1; field