| /external/tensorflow/tensorflow/contrib/data/python/kernel_tests/ |
| stats_dataset_ops_test.py | 53 dataset = dataset_ops.Dataset.range(100).map(
56 iterator = dataset.make_initializable_iterator()
79 dataset = dataset_ops.Dataset.range(100).apply(
81 iterator = dataset.make_initializable_iterator()
98 dataset = dataset_ops.Dataset.range(100).apply(
100 iterator = dataset.make_initializable_iterator()
120 dataset = dataset_ops.Dataset.range(100).apply
[all...] |
| scan_dataset_op_test.py | 37 return dataset_ops.Dataset.from_tensors(0).repeat(None).apply(
61 iterator = dataset_ops.Dataset.from_tensors(1).repeat(None).apply(
85 dataset = dataset_ops.Dataset.from_tensors(0).repeat(5).apply(
87 self.assertEqual([None], dataset.output_shapes[0][0].as_list())
88 self.assertIs(None, dataset.output_shapes[0][1].ndims)
89 self.assertEqual([], dataset.output_shapes[1].as_list())
91 iterator = dataset.make_one_shot_iterator()
107 dataset = dataset_ops.Dataset.range(10
[all...] |
| /packages/apps/Contacts/src/com/android/contacts/model/account/ |
| AccountComparator.java | 35 && Objects.equal(a.dataSet, b.dataSet)) {
60 if (a.dataSet != null) {
61 return b.dataSet == null ? 1 : a.dataSet.compareToIgnoreCase(b.dataSet);
69 return GoogleAccountType.ACCOUNT_TYPE.equals(account.type) && account.dataSet == null;
|
| /developers/build/prebuilts/gradle/AutofillFramework/afservice/src/main/java/com/example/android/autofill/service/ |
| AutofillHelper.java | 20 import android.service.autofill.Dataset;
45 * Wraps autofill data in a LoginCredential Dataset object which can then be sent back to the
48 public static Dataset newDataset(Context context,
53 Dataset.Builder datasetBuilder;
55 datasetBuilder = new Dataset.Builder
62 datasetBuilder = new Dataset.Builder
98 Dataset dataset = newDataset(context, autofillFields, local
100 if (dataset != null) {
101 responseBuilder.addDataset(dataset);
[all...] |
| /external/tensorflow/tensorflow/python/data/ops/ |
| iterator_ops.py | 54 """Represents the state of iterating through a `Dataset`."""
61 instead use `Dataset.make_initializable_iterator()` or
62 `Dataset.make_one_shot_iterator()`.
70 each component of an element of this dataset.
72 corresponding to each component of an element of this dataset.
96 The returned iterator is not bound to a particular dataset, and it has
98 `Iterator.make_initializer(dataset)`.
105 dataset_range = Dataset.range(10)
138 each component of an element of this dataset.
140 corresponding to each component of an element of this dataset. I
[all...] |
| /external/tensorflow/tensorflow/core/kernels/data/ |
| stats_dataset_ops.cc | 18 #include "tensorflow/core/kernels/data/dataset.h"
25 // This op defines a `Dataset` that passes through its input elements and
46 *output = new Dataset(ctx, input, std::move(tag));
50 class Dataset : public GraphDatasetBase {
52 explicit Dataset(OpKernelContext* ctx, const DatasetBase* input, string tag)
57 ~Dataset() override { input_->Unref(); }
72 string DebugString() override { return "LatencyStatsDatasetOp::Dataset"; }
86 class Iterator : public DatasetIterator<Dataset> {
89 : DatasetIterator<Dataset>(params),
90 input_impl_(params.dataset->input_->MakeIterator(params.prefix)) {
[all...] |
| cache_dataset_ops.cc | 17 #include "tensorflow/core/kernels/data/dataset.h"
109 input_impl_(params.dataset->input_->MakeIterator(params.prefix)),
110 writer_(params.dataset->env_, params.dataset->filename_),
111 lockfile_(strings::StrCat(params.dataset->filename_, ".lockfile")),
139 if (out_tensors->size() != dataset()->num_tensors_) {
142 dataset()->num_tensors_, " got: ", out_tensors->size());
146 DCHECK_LT(tensor_index, dataset()->num_tensors_);
147 string key = dataset()->FormatName(cur_index_, tensor_index++);
166 if (dataset()->env_->FileExists(lockfile_).ok())
[all...] |
| tensor_dataset_op.cc | 17 #include "tensorflow/core/kernels/data/dataset.h"
31 // Create a new TensorDatasetOp::Dataset, insert it in the step
42 *output = new Dataset(ctx, std::move(components));
46 class Dataset : public GraphDatasetBase {
48 Dataset(OpKernelContext* ctx, std::vector<Tensor> tensors)
67 string DebugString() override { return "TensorDatasetOp::Dataset"; }
87 class Iterator : public DatasetIterator<Dataset> {
90 : DatasetIterator<Dataset>(params), produced_(false) {}
97 *out_tensors = dataset()->tensors_;
|
| scan_dataset_op.cc | 22 #include "tensorflow/core/kernels/data/dataset.h"
66 *output = new Dataset(ctx, input, func_, std::move(initial_state),
72 class Dataset : public GraphDatasetBase {
74 Dataset(OpKernelContext* ctx, const DatasetBase* input,
91 ~Dataset() override { input_->Unref(); }
106 string DebugString() override { return "ScanDatasetOp::Dataset"; }
148 class Iterator : public DatasetIterator<Dataset> {
151 : DatasetIterator<Dataset>(params),
152 input_impl_(params.dataset->input_->MakeIterator(params.prefix)),
153 state_(params.dataset->initial_state_) {
[all...] |
| concatenate_dataset_op.cc | 17 #include "tensorflow/core/kernels/data/dataset.h"
34 "input dataset and dataset to concatenate"
38 *output = new Dataset(ctx, input, to_concatenate);
42 class Dataset : public GraphDatasetBase {
44 explicit Dataset(OpKernelContext* ctx, const DatasetBase* input,
59 ~Dataset() override {
78 string DebugString() override { return "ConcatenateDatasetOp::Dataset"; }
94 class Iterator : public DatasetIterator<Dataset> {
97 : DatasetIterator<Dataset>(params)
[all...] |
| /developers/samples/android/input/autofill/AutofillFramework/afservice/src/main/java/com/example/android/autofill/service/data/adapter/ |
| DatasetAdapter.java | 21 import android.service.autofill.Dataset;
53 * Wraps autofill data in a {@link Dataset} object which can then be sent back to the client.
55 public Dataset buildDataset(HashMap<String, FieldTypeWithHeuristics> fieldTypesByAutofillHint,
62 public Dataset buildDatasetForFocusedNode(FilledAutofillField filledAutofillField,
64 Dataset.Builder datasetBuilder = new Dataset.Builder(remoteViews);
74 * Wraps autofill data in a {@link Dataset} object with an IntentSender, which can then be
77 public Dataset buildDataset(HashMap<String, FieldTypeWithHeuristics> fieldTypesByAutofillHint,
80 Dataset.Builder datasetBuilder = new Dataset.Builder(remoteViews)
[all...] |
| /external/icu/icu4c/source/test/perf/perldriver/ |
| Dataset.pm | 12 package Dataset;
17 # Create a new Dataset with the given data.
66 # Return a 99% error based on the t distribution. The dataset
74 # mean+/-error. The new Dataset has no data points.
84 my $result = Dataset->new();
92 # mean+/-error. The new Dataset has no data points.
97 my $result = Dataset->new();
105 # mean+/-error. The new Dataset has no data points.
110 my $result = Dataset->new();
117 # Divides a dataset by a scalar
[all...] |
| /external/icu/icu4j/perf-tests/perldriver/ |
| Dataset.pm | 10 package Dataset;
15 # Create a new Dataset with the given data.
64 # Return a 99% error based on the t distribution. The dataset
72 # mean+/-error. The new Dataset has no data points.
82 my $result = Dataset->new();
90 # mean+/-error. The new Dataset has no data points.
95 my $result = Dataset->new();
103 # mean+/-error. The new Dataset has no data points.
108 my $result = Dataset->new();
115 # Divides a dataset by a scalar
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/utils/ |
| io_utils.py | 36 """Representation of HDF5 dataset to be used instead of a Numpy array.
45 Providing `start` and `end` allows use of a slice of the dataset.
52 dataset: string, name of the HDF5 dataset in the file specified
54 start: int, start of desired slice of the specified dataset
55 end: int, end of desired slice of the specified dataset
59 An array-like HDF5 dataset.
63 def __init__(self, datapath, dataset, start=0, end=None, normalizer=None):
73 self.data = f[dataset]
119 """Gets a numpy-style shape tuple giving the dataset dimensions
[all...] |
| /external/tensorflow/tensorflow/contrib/data/kernels/ |
| ignore_errors_dataset_op.cc | 15 #include "tensorflow/core/framework/dataset.h"
34 *output = new Dataset(ctx, input);
38 class Dataset : public GraphDatasetBase {
40 explicit Dataset(OpKernelContext* ctx, const DatasetBase* input)
45 ~Dataset() override { input_->Unref(); }
60 string DebugString() override { return "IgnoreErrorsDatasetOp::Dataset"; }
72 class Iterator : public DatasetIterator<Dataset> {
75 : DatasetIterator<Dataset>(params),
76 input_impl_(params.dataset->input_->MakeIterator(params.prefix)) {}
|
| /libcore/benchmarks/src/benchmarks/ |
| XmlSerializeBenchmark.java | 36 double[] dataset; field in class:XmlSerializeBenchmark
42 double contChance = dataset[0];
43 double levelUpChance = dataset[1];
44 double levelDownChance = dataset[2];
45 double attributeChance = dataset[3];
46 double writeChance1 = dataset[4];
47 double writeChance2 = dataset[5];
89 dataset = new double[splitted.length];
91 dataset[i] = Double.parseDouble(splitted[i]);
|
| /external/tensorflow/tensorflow/contrib/data/python/ops/ |
| grouping.py | 15 """Grouping dataset transformations."""
35 This transformation maps each consecutive element in a dataset to a key
48 reduce_func: A function mapping a key and a dataset of up to `window_size`
49 consecutive elements matching that key to another dataset.
60 A `Dataset` transformation function, which can be passed to
61 @{tf.data.Dataset.apply}.
80 def _apply_fn(dataset):
81 """Function from `Dataset` to `Dataset` that applies the transformation."""
82 return GroupByWindowDataset(dataset, key_func, reduce_func
[all...] |
| shuffle_ops.py | 30 class _ShuffleAndRepeatDataset(dataset_ops.Dataset):
31 """A `Dataset` that fuses `shuffle` and `repeat`."""
38 """See `Dataset.map()` for details."""
89 """Shuffles and repeats a Dataset returning a new permutation for each epoch.
91 `dataset.apply(tf.contrib.data.shuffle_and_repeat(buffer_size, count))`
95 `dataset.shuffle(buffer_size, reshuffle_each_iteration=True).repeat(count)`
97 The difference is that the latter dataset is not serializable. So,
105 number of times the dataset should be repeated. The default behavior
106 (if `count` is `None` or `-1`) is for the dataset be repeated
113 A `Dataset` transformation function, which can be passed t
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/ |
| datasets.py | 49 """An iterator producing tf.Tensor objects from a tf.data.Dataset."""
51 def __init__(self, dataset):
52 """Creates a new iterator over the given dataset.
56 dataset = tf.data.Dataset.range(4)
57 for x in Iterator(dataset):
65 dataset: A `tf.data.Dataset` object.
74 "tf.data.Dataset.make_iterator or "
75 "tf.data.Dataset.make_one_shot_iterator for graph construction"
[all...] |
| /external/tensorflow/tensorflow/contrib/slim/python/slim/data/ |
| README.md | 11 a dataset is represented so it can be read and interpreted and (2) instruction
12 for providing the data to consumers of the dataset.
19 # Dataset Specification
21 TF-Slim defines a dataset to be a set of files (that may or may not be encoded)
23 predefined set of entities or `items`. For example, a dataset might be stored
30 [dataset](https://www.tensorflow.org/code/tensorflow/contrib/slim/python/slim/data/dataset.py)
31 is a tuple that encapsulates the following elements of a dataset specification:
33 * `data_sources`: A list of file paths that together make up the dataset
39 class which is used to decode the content of the read dataset files
[all...] |
| dataset_data_provider.py | 15 """A DataProvider that provides data from a Dataset.
31 slim.datasets.pascal_voc.Dataset(),
54 dataset,
69 dataset: An instance of the Dataset class.
79 record_key: The item name to use for the dataset record keys in the
84 ValueError: If `record_key` matches one of the items in the dataset.
87 dataset.data_sources,
88 reader_class=dataset.reader,
98 items = dataset.decoder.list_items(
[all...] |
| /developers/build/prebuilts/gradle/RecyclerView/Application/src/main/java/com/example/android/recyclerview/ |
| CustomAdapter.java | 61 * Initialize the dataset of the Adapter.
63 * @param dataSet String[] containing the data to populate views to be used by RecyclerView.
65 public CustomAdapter(String[] dataSet) {
66 mDataSet = dataSet;
87 // Get element from your dataset at this position and replace the contents of the view
93 // Return the size of your dataset (invoked by the layout manager)
|
| /developers/samples/android/ui/views/RecyclerView/Application/src/main/java/com/example/android/recyclerview/ |
| CustomAdapter.java | 61 * Initialize the dataset of the Adapter.
63 * @param dataSet String[] containing the data to populate views to be used by RecyclerView.
65 public CustomAdapter(String[] dataSet) {
66 mDataSet = dataSet;
87 // Get element from your dataset at this position and replace the contents of the view
93 // Return the size of your dataset (invoked by the layout manager)
|
| /development/samples/browseable/RecyclerView/src/com.example.android.recyclerview/ |
| CustomAdapter.java | 61 * Initialize the dataset of the Adapter.
63 * @param dataSet String[] containing the data to populate views to be used by RecyclerView.
65 public CustomAdapter(String[] dataSet) {
66 mDataSet = dataSet;
87 // Get element from your dataset at this position and replace the contents of the view
93 // Return the size of your dataset (invoked by the layout manager)
|
| /packages/apps/Contacts/src/com/android/contacts/list/ |
| ContactListFilter.java | 62 private static final String KEY_DATA_SET = "filter.dataSet";
67 public final String dataSet;
71 public ContactListFilter(int filterType, String accountType, String accountName, String dataSet,
76 this.dataSet = dataSet;
85 String dataSet, Drawable icon) {
87 accountName, dataSet, icon);
91 String dataSet) {
93 accountName, dataSet, /* icon */ null);
98 /* accountType= */ null, /* accountName= */ null, /* dataSet= */ null, icon)
[all...] |
