| /external/protobuf/benchmarks/ |
| D | Makefile.am | 5 datasets/google_message1/proto3/benchmark_message1_proto3.proto
8 datasets/google_message1/proto2/benchmark_message1_proto2.proto \
9 datasets/google_message2/benchmark_message2.proto \
10 datasets/google_message3/benchmark_message3.proto \
11 datasets/google_message3/benchmark_message3_1.proto \
12 datasets/google_message3/benchmark_message3_2.proto \
13 datasets/google_message3/benchmark_message3_3.proto \
14 datasets/google_message3/benchmark_message3_4.proto \
15 datasets/google_message3/benchmark_message3_5.proto \
16 datasets/google_message3/benchmark_message3_6.proto \
[all …]
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| D | download_data.sh | 3 curl -O https://storage.googleapis.com/protobuf_opensource_benchmark_data/datasets.tar.gz
4 tar -zvxf datasets.tar.gz
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| /external/protobuf/kokoro/linux/benchmark/ |
| D | run.sh | 22 datasets=$(for file in $(find . -type f -name "dataset.*.pb" -not -path "./tmp/*"); do echo "$(pwd)…
23 echo $datasets
42 ./python-pure-python-benchmark --json --behavior_prefix="pure-python-benchmark" $datasets >> tmp/p…
45 …flection-benchmark --json --behavior_prefix="cpp-reflection-benchmark" $datasets >> tmp/python_re…
48 …code-benchmark --json --behavior_prefix="cpp-generated-code-benchmark" $datasets >> tmp/python_res…
65 …-benchmark_min_time=5.0 --benchmark_out_format=json --benchmark_out="tmp/cpp_result.json" $datasets
81 ./go-benchmark $datasets > tmp/go_result.txt
86 ./java-benchmark -Cresults.file.options.file="tmp/java_result.json" $datasets
90 ./js-benchmark $datasets --json_output=$(pwd)/tmp/node_result.json
93 proto3_datasets=$(for file in $datasets; do echo $(pwd)/tmp/proto3_data/${file#$(pwd)}; done | xarg…
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| /external/tensorflow/tensorflow/python/data/experimental/ops/ |
| D | interleave_ops.py | 152 def sample_from_datasets_v2(datasets, weights=None, seed=None): argument
175 num_datasets = len(datasets)
199 if len(datasets) == 1:
200 return datasets[0]
232 return _DirectedInterleaveDataset(selector_input, datasets)
236 def sample_from_datasets_v1(datasets, weights=None, seed=None): argument
238 sample_from_datasets_v2(datasets, weights, seed))
243 def choose_from_datasets_v2(datasets, choice_dataset): argument
282 return _DirectedInterleaveDataset(choice_dataset, datasets)
286 def choose_from_datasets_v1(datasets, choice_dataset): argument
[all …]
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| D | distribute.py | 327 datasets = {}
329 datasets[devices[0]] = dataset
330 return datasets
349 datasets[device] = ds
350 return datasets
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| D | optimization.py | 72 def __init__(self, datasets, num_experiments=10): argument
99 self._datasets = list(datasets)
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| /external/tensorflow/tensorflow/python/data/kernel_tests/ |
| D | zip_test.py | 32 datasets = tuple([
36 return dataset_ops.Dataset.zip(datasets)
79 datasets = [
83 dataset = dataset_ops.Dataset.zip((datasets[0], (datasets[1], datasets[2])))
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| /external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
| D | zip_dataset_serialization_test.py | 40 datasets = [
44 return dataset_ops.Dataset.zip((datasets[0], (datasets[1], datasets[2])))
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| /external/tensorflow/tensorflow/python/tpu/ |
| D | datasets_test.py | 33 from tensorflow.python.tpu import datasets
72 dataset = datasets.StreamingFilesDataset(
97 dataset = datasets.StreamingFilesDataset(
126 dataset = datasets.StreamingFilesDataset(filenames, filetype='tfrecord')
158 dataset = datasets.StreamingFilesDataset(
183 dataset = datasets.StreamingFilesDataset(
200 datasets.StreamingFilesDataset(
205 datasets.StreamingFilesDataset(
210 datasets.StreamingFilesDataset(123, filetype='tfrecord')
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| /external/tensorflow/tensorflow/python/tools/api/generator/ |
| D | api_init_files_v1.bzl | 128 "keras/datasets/__init__.py",
129 "keras/datasets/boston_housing/__init__.py",
130 "keras/datasets/cifar10/__init__.py",
131 "keras/datasets/cifar100/__init__.py",
132 "keras/datasets/fashion_mnist/__init__.py",
133 "keras/datasets/imdb/__init__.py",
134 "keras/datasets/mnist/__init__.py",
135 "keras/datasets/reuters/__init__.py",
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| D | api_init_files.bzl | 132 "keras/datasets/__init__.py",
133 "keras/datasets/boston_housing/__init__.py",
134 "keras/datasets/cifar10/__init__.py",
135 "keras/datasets/cifar100/__init__.py",
136 "keras/datasets/fashion_mnist/__init__.py",
137 "keras/datasets/imdb/__init__.py",
138 "keras/datasets/mnist/__init__.py",
139 "keras/datasets/reuters/__init__.py",
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| /external/guava/guava-tests/benchmark/com/google/common/math/ |
| D | QuantilesBenchmark.java | 39 private double[][] datasets = new double[0x100][]; field in QuantilesBenchmark
45 datasets[i] = new double[datasetSize]; in setUp()
47 datasets[i][j] = rng.nextDouble(); in setUp()
55 return datasets[i & 0xFF].clone(); in dataset()
|
| /external/guava/android/guava-tests/benchmark/com/google/common/math/ |
| D | QuantilesBenchmark.java | 39 private double[][] datasets = new double[0x100][]; field in QuantilesBenchmark
45 datasets[i] = new double[datasetSize]; in setUp()
47 datasets[i][j] = rng.nextDouble(); in setUp()
55 return datasets[i & 0xFF].clone(); in dataset()
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_ZipDataset.pbtxt | 7 List of `N` variant Tensors representing datasets to be zipped together.
23 elements from each of the input datasets.
26 dataset, and no error will be raised if input datasets have different sizes.
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| D | api_def_ExperimentalDirectedInterleaveDataset.pbtxt | 13 `N` datasets with the same type that will be interleaved according to
18 A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
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| D | api_def_DirectedInterleaveDataset.pbtxt | 13 `N` datasets with the same type that will be interleaved according to
18 A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
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| D | api_def_ParallelInterleaveDatasetV2.pbtxt | 20 Number of datasets (each created by applying `f` to the elements of
36 input datasets in parallel. The Python API `tf.data.experimental.AUTOTUNE`
63 dataset will fetch records from the interleaved datasets in parallel.
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| D | api_def_ParallelInterleaveDatasetV3.pbtxt | 20 Number of datasets (each created by applying `f` to the elements of
36 input datasets in parallel. The Python API `tf.data.experimental.AUTOTUNE`
73 dataset will fetch records from the interleaved datasets in parallel.
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| /external/tensorflow/tensorflow/python/keras/api/ |
| D | BUILD | 38 "tensorflow.python.keras.datasets.boston_housing",
39 "tensorflow.python.keras.datasets.cifar10",
40 "tensorflow.python.keras.datasets.cifar100",
41 "tensorflow.python.keras.datasets.fashion_mnist",
42 "tensorflow.python.keras.datasets.imdb",
43 "tensorflow.python.keras.datasets.mnist",
44 "tensorflow.python.keras.datasets.reuters",
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| /external/protobuf/benchmarks/go/ |
| D | go_benchmark_test.go | 24 var datasets []Dataset var
74 datasets = append(datasets, ds)
79 for _, ds := range datasets {
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| /external/protobuf/benchmarks/python/ |
| D | py_benchmark.py | 35 import datasets.google_message1.proto2.benchmark_message1_proto2_pb2 as benchmark_message1_proto2_p…
36 import datasets.google_message1.proto3.benchmark_message1_proto3_pb2 as benchmark_message1_proto3_p…
37 import datasets.google_message2.benchmark_message2_pb2 as benchmark_message2_pb2
38 import datasets.google_message3.benchmark_message3_pb2 as benchmark_message3_pb2
39 import datasets.google_message4.benchmark_message4_pb2 as benchmark_message4_pb2
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| /external/pdfium/testing/resources/pixel/xfa_specific/ |
| D | bug_1282.in | 11 (datasets)
51 <xfa:datasets xmlns:xfa="http://www.xfa.org/schema/xfa-data/1.0/">
59 </xfa:datasets>
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| /external/tensorflow/tensorflow/python/keras/datasets/ |
| D | BUILD | 2 # Contains the Keras datasets package (internal TensorFlow version).
18 name = "datasets",
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| /external/tensorflow/tensorflow/lite/g3doc/models/recommendation/ |
| D | overview.md | 48 [MovieLens](https://grouplens.org/datasets/movielens/1m/) dataset for research
106 own datasets.
111 [MovieLens](https://grouplens.org/datasets/movielens/1m/) dataset, you may want
115 * Input context length: The best input context length varies with datasets. We
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| /external/tensorflow/tensorflow/core/kernels/data/experimental/ |
| D | snapshot_util.cc | 484 explicit NestedDataset(std::vector<DatasetBase*> datasets, in NestedDataset() argument
486 : DatasetBase(DatasetContext(std::move(params))), datasets_(datasets) { in NestedDataset()
582 std::vector<DatasetBase*> datasets; in MakeNestedDataset() local
584 datasets.reserve(shard_dirs.size()); in MakeNestedDataset()
589 if (start_index % shard_dirs.size() > datasets.size()) { in MakeNestedDataset()
593 datasets.push_back( in MakeNestedDataset()
604 std::rotate(datasets.begin(), in MakeNestedDataset()
605 datasets.begin() + (start_index % shard_dirs.size()), in MakeNestedDataset()
606 datasets.end()); in MakeNestedDataset()
610 datasets, DatasetContext::Params({"snapshot_util::Reader::NestedDataset", in MakeNestedDataset()
|