| /external/tensorflow/tensorflow/contrib/boosted_trees/python/ops/ |
| D | stats_accumulator_ops.py | 44 (stamp_token, num_updates, partition_ids, feature_ids, gradients,
51 saver.BaseSaverBuilder.SaveSpec(partition_ids, slice_spec,
72 def deserialize(self, stamp_token, num_updates, partition_ids, feature_ids, argument
77 self._resource_handle, stamp_token, num_updates, partition_ids,
81 self._resource_handle, stamp_token, num_updates, partition_ids,
99 partition_ids=restored_tensors[2],
196 def add(self, stamp_token, partition_ids, feature_ids, gradients, hessians): argument
198 partition_ids, feature_ids, gradients, hessians = (self._make_summary(
199 partition_ids, feature_ids, gradients, hessians))
202 [self.resource_handle], stamp_token, [partition_ids], [feature_ids],
[all …]
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| /external/tensorflow/tensorflow/contrib/boosted_trees/python/kernel_tests/ |
| D | split_handler_ops_test.py | 42 partition_ids = array_ops.constant([0, 0, 1], dtype=dtypes.int32)
51 partition_ids=partition_ids,
115 partition_ids = array_ops.constant([0, 0, 1], dtype=dtypes.int32)
125 partition_ids=partition_ids,
157 partition_ids = array_ops.constant([], dtype=dtypes.int32)
165 partition_ids=partition_ids,
194 partition_ids = array_ops.constant([0, 0, 0, 1, 1], dtype=dtypes.int32)
206 partition_ids=partition_ids,
282 partition_ids = array_ops.constant([0, 1], dtype=dtypes.int32)
291 partition_ids=partition_ids,
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| D | stats_accumulator_ops_test.py | 40 partition_ids=[1, 2],
68 partition_ids=[1, 2, 1],
97 partition_ids=[1, 2],
103 partition_ids=[1],
129 partition_ids=[1, 2],
171 partition_ids=[1, 2],
181 partition_ids=[3, 4],
205 partition_ids=[1, 2, 1],
229 partition_ids=[1, 2],
238 partition_ids=[1],
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| D | training_ops_test.py | 344 partition_ids=[
458 partition_ids=[
610 partition_ids=[
796 partition_ids=[
936 partition_ids=[handler1_partitions, handler2_partitions],
1006 partition_ids=[
1111 partition_ids=[handler1_partitions, handler2_partitions],
1194 partition_ids=[handler1_partitions],
1262 partition_ids=[handler1_partitions, handler2_partitions],
1343 partition_ids=[handler1_partitions],
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| /external/tensorflow/tensorflow/contrib/boosted_trees/kernels/ |
| D | split_handler_ops.cc | 152 const auto& partition_ids = partition_ids_t->vec<int32>(); in Compute() local
172 for (int i = 1; i < partition_ids.size(); ++i) { in Compute()
173 if (partition_ids(i) != partition_ids(i - 1)) { in Compute()
175 OP_REQUIRES(context, partition_ids(i) >= partition_ids(i - 1), in Compute()
180 if (partition_ids.size() > 0) { in Compute()
181 partition_boundaries.push_back(partition_ids.size()); in Compute()
227 bucket_boundaries, partition_ids, bucket_ids, gradients_t, in Compute()
234 bucket_boundaries, partition_ids, bucket_ids, gradients_t, in Compute()
246 const tensorflow::TTypes<int32>::ConstVec& partition_ids, in ComputeNormalDecisionTree() argument
299 (*output_partition_ids)(root_idx) = partition_ids(start_index); in ComputeNormalDecisionTree()
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| D | stats_accumulator_ops.cc | 140 auto partition_ids = partition_ids_t->vec<int32>(); in SerializeScalarAccumulatorToOutput() local
163 partition_ids(i) = iter.first.partition_id; in SerializeScalarAccumulatorToOutput()
181 auto partition_ids = partition_ids_t->vec<int32>(); in SerializeTensorAccumulatorToOutput() local
208 partition_ids(i) = iter.first.partition_id; in SerializeTensorAccumulatorToOutput()
229 const auto& partition_ids = partition_ids_t.vec<int32>(); in AddToScalarAccumulator() local
238 PartitionKey(partition_ids(i), feature_ids_and_dimensions(i, 0), in AddToScalarAccumulator()
274 const auto& partition_ids = partition_ids_t.vec<int32>(); in AddToTensorAccumulator() local
301 PartitionKey(partition_ids(i), feature_ids_and_dimensions(i, 0), in AddToTensorAccumulator()
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| D | training_ops.cc | 448 const auto& partition_ids = partition_ids_list[handler_id].vec<int32>(); in FindBestSplitsPerPartitionNormal() local
451 OP_REQUIRES(context, partition_ids.size() == gains.size(), in FindBestSplitsPerPartitionNormal()
454 partition_ids.size(), " != ", gains.size())); in FindBestSplitsPerPartitionNormal()
455 OP_REQUIRES(context, partition_ids.size() == splits.size(), in FindBestSplitsPerPartitionNormal()
458 partition_ids.size(), " != ", splits.size())); in FindBestSplitsPerPartitionNormal()
462 const auto& partition_id = partition_ids(candidate_idx); in FindBestSplitsPerPartitionNormal()
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| /external/tensorflow/tensorflow/contrib/boosted_trees/lib/learner/batch/ |
| D | ordinal_split_handler.py | 270 are_splits_ready, partition_ids, gains, split_infos = (
278 return are_splits_ready, partition_ids, gains, split_infos
307 num_minibatches, partition_ids, bucket_ids, gradients, hessians = (
311 num_minibatches, partition_ids, bucket_ids, gradients, hessians = (
320 with ops.control_dependencies([flush_quantiles, partition_ids]):
322 partition_ids, gains, split_infos = (
326 partition_ids=partition_ids,
338 return are_splits_ready, partition_ids, gains, split_infos
450 are_splits_ready, partition_ids, gains, split_infos = (
457 return are_splits_ready, partition_ids, gains, split_infos
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| D | categorical_split_handler.py | 165 partition_ids = array_ops.concat(
177 return (partition_ids, feature_ids_and_dimensions, filtered_gradients,
180 partition_ids, feature_ids, gradients_out, hessians_out = (
182 result = self._stats_accumulator.schedule_add(partition_ids, feature_ids,
190 num_minibatches, partition_ids, feature_ids, gradients, hessians = (
198 partition_ids, gains, split_infos = (
201 partition_ids=partition_ids,
217 return (are_splits_ready, partition_ids, gains, split_infos)
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| D | categorical_split_handler_test.py | 59 partition_ids = [0, 0, 0, 1]
86 partition_ids,
95 partition_ids,
182 partition_ids = [1, 1, 1, 2]
210 partition_ids,
219 partition_ids,
293 partition_ids = [0, 0, 0, 1]
321 partition_ids,
330 partition_ids,
419 partition_ids = [0, 0, 0, 1]
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| D | ordinal_split_handler_test.py | 63 partition_ids = array_ops.constant([0, 0, 0, 1], dtype=dtypes.int32)
89 partition_ids,
103 partition_ids,
197 partition_ids = array_ops.constant([1, 1, 1, 2], dtype=dtypes.int32)
224 partition_ids,
241 partition_ids,
333 partition_ids = array_ops.constant([0, 0, 0, 1], dtype=dtypes.int32)
360 partition_ids,
374 partition_ids,
383 partition_ids,
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| /external/tensorflow/tensorflow/contrib/boosted_trees/python/training/functions/ |
| D | gbdt_batch_test.py | 241 partition_ids = array_ops.zeros([4], dtypes.int32)
251 "partition_ids": partition_ids,
505 partition_ids = array_ops.zeros([4], dtypes.int32)
515 "partition_ids": partition_ids,
609 partition_ids = array_ops.zeros([4], dtypes.int32)
619 "partition_ids": partition_ids,
713 partition_ids = array_ops.zeros([4], dtypes.int32)
723 "partition_ids": partition_ids,
785 partition_ids = array_ops.zeros([4], dtypes.int32)
795 "partition_ids": partition_ids,
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| D | gbdt_batch.py | 86 partition_ids, argument
109 result[PARTITION_IDS] = partition_ids
527 partition_ids = prediction_ops.gradient_trees_partition_examples(
538 return _make_predictions_dict(ensemble_stamp, predictions, partition_ids,
651 partition_ids = predictions_dict[PARTITION_IDS]
924 ensemble_stamp, partition_ids, squeezed_gradients, squeezed_hessians,
1062 partition_ids, gains, split_info) = handler.make_splits(
1065 partition_ids_list.append(partition_ids)
1073 partition_ids = array_ops.concat(partition_ids_list, axis=0)
1099 partition_ids_list = list(array_ops.split(partition_ids, sizes, axis=0))
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