| /external/v8/tools/heap-stats/ |
| D | global-timeline.js | 77 const data_set = gc_data[this.selection.data_set].field_data;
80 const total = data_set.tagged_fields +
81 data_set.embedder_fields +
82 data_set.other_raw_fields +
83 data_set.unboxed_double_fields;
84 const ptr_compr_benefit = data_set.tagged_fields / 2;
94 data.push(data_set.embedder_fields / KB);
95 data.push(data_set.tagged_fields / KB);
96 data.push(data_set.other_raw_fields / KB);
97 data.push(data_set.unboxed_double_fields / KB);
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| D | model.js | 48 finalizeDataSet(data_set) { argument
51 let data = data_set.instance_type_data;
53 [...data_set.non_empty_instance_types].sort((a, b) => {
63 data_set.instance_type_data = data;
64 data_set.singleInstancePeakMemory = max;
66 Object.entries(data_set.instance_type_data).forEach(([name, entry]) => {
68 name, entry, data_set.bucket_sizes, 'histogram', ' overall');
70 name, entry, data_set.bucket_sizes, 'over_allocated_histogram',
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| D | trace-file-reader.js | 127 createDatasetIfNeeded(data, entry, data_set) { argument
128 if (!(data_set in data[entry.isolate].gcs[entry.id])) {
129 data[entry.isolate].gcs[entry.id][data_set] = {
134 data[entry.isolate].data_sets.add(data_set);
138 addFieldTypeData(data, isolate, gc_id, data_set, tagged_fields, argument
140 data[isolate].gcs[gc_id][data_set].field_data = {
148 addInstanceTypeData(data, isolate, gc_id, data_set, instance_type, entry) { argument
149 data[isolate].gcs[gc_id][data_set].instance_type_data[instance_type] = {
156 data[isolate].gcs[gc_id][data_set].overall += entry.overall;
158 data[isolate].gcs[gc_id][data_set].non_empty_instance_types.add(
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| D | details-selection.js | 58 return this.selectedIsolate.gcs[this.selection.gc][this.selection.data_set];
199 this.selection.data_set = this.datasetSelect.value;
383 this.selectedIsolate.gcs[this.selection.gc][this.selection.data_set]
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| D | histogram-viewer.js | 81 .gcs[this.selection.gc][this.selection.data_set];
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| /external/tensorflow/tensorflow/examples/how_tos/reading_data/ |
| D | convert_to_records.py | 40 def convert_to(data_set, name): argument
42 images = data_set.images
43 labels = data_set.labels
44 num_examples = data_set.num_examples
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| /external/tensorflow/tensorflow/examples/tutorials/mnist/ |
| D | fully_connected_feed.py | 59 def fill_feed_dict(data_set, images_pl, labels_pl): argument
78 images_feed, labels_feed = data_set.next_batch(FLAGS.batch_size,
91 data_set): argument
104 steps_per_epoch = data_set.num_examples // FLAGS.batch_size
107 feed_dict = fill_feed_dict(data_set,
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| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/ |
| D | model_ops.cc | 181 std::unique_ptr<TensorDataSet> data_set(new TensorDataSet(input_spec_, 0)); in Compute() local
182 data_set->set_input_tensors(input_data, sparse_input_indices, in Compute()
191 const int num_data = data_set->NumItems(); in Compute()
208 auto traverse = [this, &out, &data_set, decision_tree_resource, num_data, in Compute()
212 TraverseTree(decision_tree_resource, data_set, static_cast<int32>(start), in Compute()
282 std::unique_ptr<TensorDataSet> data_set(new TensorDataSet(input_spec_, 0)); in Compute() local
283 data_set->set_input_tensors(input_data, sparse_input_indices, in Compute()
292 const int num_data = data_set->NumItems(); in Compute()
307 auto traverse = [&set_leaf_ids, &data_set, decision_tree_resource, in Compute()
311 TraverseTree(decision_tree_resource, data_set, static_cast<int32>(start), in Compute()
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| D | stats_ops.cc | 249 std::unique_ptr<TensorDataSet> data_set( in Compute() local
251 data_set->set_input_tensors(input_data, sparse_input_indices, in Compute()
266 const int32 num_data = data_set->NumItems(); in Compute()
310 auto update = [&target, &leaf_ids_tensor, &num_targets, &data_set, in Compute()
315 UpdateStats(fertile_stats_resource, data_set, target, num_targets, in Compute()
322 &ready_to_split, &data_set, in Compute()
326 UpdateStatsCollated(fertile_stats_resource, tree_resource, data_set, in Compute()
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| /external/tensorflow/tensorflow/contrib/factorization/examples/ |
| D | mnist.py | 65 def fill_feed_dict(data_set, images_pl, labels_pl, batch_size): argument
79 images_feed, labels_feed = data_set.next_batch(batch_size, FLAGS.fake_data)
91 data_set): argument
106 batch_size = min(FLAGS.batch_size, data_set.num_examples)
107 steps_per_epoch = data_set.num_examples // batch_size
110 feed_dict = fill_feed_dict(data_set,
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| /external/u-boot/drivers/gpio/ |
| D | adi_gpio2.c | 373 gpio_array[gpio_bank(gpio)]->data_set = gpio_bit(gpio); in gpio_set_value()
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