| /external/tensorflow/tensorflow/core/kernels/boosted_trees/quantiles/ |
| D | weighted_quantiles_summary.h | 49 max_rank = max; in SummaryEntry()
58 max_rank = 0; in SummaryEntry()
63 min_rank == other.min_rank && max_rank == other.max_rank;
68 << entry.min_rank << ", " << entry.max_rank << "}";
72 WeightType PrevMaxRank() const { return max_rank - weight; } in PrevMaxRank()
80 WeightType max_rank; member
147 it1->max_rank + it2->PrevMaxRank()); in Merge()
156 it2->max_rank + it1->PrevMaxRank()); in Merge()
164 it1->max_rank + it2->max_rank); in Merge()
177 it1->max_rank + other_entries.back().max_rank); in Merge()
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | cwise_ops.cc | 68 int max_rank = std::max(lhs_shape.dims(), rhs_shape.dims()); in Compile() local
70 if (min_rank != max_rank) { in Compile()
74 extend_dimension.push_back(max_rank - min_rank + i); in Compile()
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| /external/tensorflow/tensorflow/core/grappler/optimizers/data/vectorization/ |
| D | cwise_op_vectorizer.cc | 69 Output max_rank = ops::Maximum(scope, rank_0, rank_1); in ExpandDimsForBroadcast() local
73 [&scope, &max_rank](const WrappedTensor& tensor, const Output& rank) { in ExpandDimsForBroadcast()
79 Output rank_diff = ops::Sub(scope, max_rank, rank); in ExpandDimsForBroadcast()
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_BoostedTreesFlushQuantileSummaries.pbtxt | 14 max_rank) for a single feature.
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| D | api_def_BoostedTreesQuantileStreamResourceAddSummaries.pbtxt | 19 summary Tensor is rank 2, containing summaries (value, weight, min_rank, max_rank)
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| D | api_def_BoostedTreesMakeQuantileSummaries.pbtxt | 26 (value, weight, min_rank, max_rank) of a single feature.
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| /external/tensorflow/tensorflow/core/kernels/boosted_trees/ |
| D | quantile_ops.cc | 198 output(row, 3) = entry.max_rank; in Compute()
257 output(row, 3) = entry.max_rank; in Compute()
320 float max_rank = summary_values(i, 3); in Compute() local
321 QuantileSummaryEntry entry(value, weight, min_rank, max_rank); in Compute()
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| /external/tensorflow/tensorflow/compiler/mlir/lite/ir/ |
| D | tfl_ops.cc | 65 int64_t max_rank = -1; in VerifyOperandsHaveSameShapesOrBroadcastableShape() local
79 max_rank = std::max(max_rank, shaped_type.getRank()); in VerifyOperandsHaveSameShapesOrBroadcastableShape()
109 if (has_unknown_shape_input) return max_rank <= max_bcast_rank; in VerifyOperandsHaveSameShapesOrBroadcastableShape()
113 return has_same_shape || max_rank <= max_bcast_rank; in VerifyOperandsHaveSameShapesOrBroadcastableShape()
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| /external/tensorflow/tensorflow/core/grappler/costs/ |
| D | op_level_cost_estimator.cc | 203 int max_rank = 1; in CwiseOutputElementCount() local
205 max_rank = std::max(max_rank, input_properties.shape().dim_size()); in CwiseOutputElementCount()
209 output_shape.mutable_dim()->Reserve(max_rank); in CwiseOutputElementCount()
210 for (int i = 0; i < max_rank; ++i) { in CwiseOutputElementCount()
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| D | graph_properties.cc | 2338 const int64 max_rank = 4; in PropagateShapes() local
2340 max_rank * max_loop_length * std::max<int64>(1, num_loops * num_loops); in PropagateShapes()
2342 const int64 max_resource_iterations = num_queues * num_queues * max_rank; in PropagateShapes()
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | randomized_tests.cc | 297 int max_rank = kDefaultMaxRank,
444 std::vector<int64> OpTest::RandomDims(int min_rank, int max_rank, in RandomDims() argument
447 CHECK_LE(min_rank, max_rank); in RandomDims()
448 std::uniform_int_distribution<int> rank_distribution(min_rank, max_rank); in RandomDims()
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| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| D | pfor.py | 838 max_rank = ranks[0]
840 max_rank = math_ops.maximum(rank, max_rank)
845 rank_diff = array_ops.reshape(max_rank - ranks[i], [1])
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| /external/tensorflow/tensorflow/compiler/tf2tensorrt/convert/ |
| D | convert_nodes.cc | 318 const int max_rank = nvinfer1::Dims::MAX_DIMS + (use_implicit_batch ? 1 : 0); in ValidateTensorProperties() local
319 if (shape.dims() > max_rank) { in ValidateTensorProperties()
320 return errors::OutOfRange("Input tensor rank is greater than ", max_rank); in ValidateTensorProperties()
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