| /cts/tests/autofillservice/src/android/autofillservice/cts/ |
| DatasetTest.java | 25 import android.service.autofill.Dataset;
48 assertThrows(NullPointerException.class, () -> new Dataset.Builder(null));
53 final Dataset.Builder builder = new Dataset.Builder(mPresentation);
60 assertThat(new Dataset.Builder().setValue(mId, mValue).build()).isNotNull();
65 final Dataset.Builder builder = new Dataset.Builder();
72 assertThat(new Dataset.Builder(mPresentation).setValue(mId, mValue, (Pattern) null).build())
78 assertThat(new Dataset.Builder().setValue(mId, mValue, null, mPresentation).build())
84 final Dataset.Builder builder = new Dataset.Builder()
[all...] |
| /external/tensorflow/tensorflow/contrib/data/python/ops/ |
| dataset_ops.py | 31 class Dataset(dataset_ops.Dataset):
34 A `Dataset` can be used to represent an input pipeline as a
39 def __init__(self, dataset):
40 super(Dataset, self).__init__()
41 self._dataset = dataset
63 @deprecation.deprecated(None, "Use `tf.data.Dataset.from_tensors()`.")
65 """Creates a `Dataset` with a single element, comprising the given tensors.
71 A `Dataset`.
73 return Dataset(dataset_ops.TensorDataset(tensors)
[all...] |
| enumerate_ops.py | 15 """Enumerate dataset transformations."""
27 """A transformation that enumerate the elements of a dataset.
34 # contents of a dataset.
39 # structure of elements in the resulting dataset.
49 A `Dataset` transformation function, which can be passed to
50 @{tf.data.Dataset.apply}.
53 def _apply_fn(dataset):
55 return dataset_ops.Dataset.zip((dataset_ops.Dataset.range(start, max_value),
56 dataset))
[all...] |
| /external/tensorflow/tensorflow/contrib/data/python/kernel_tests/ |
| flat_map_dataset_op_test.py | 42 return dataset_ops.Dataset.range(x, x + 5)
44 return dataset_ops.Dataset.range(start, start + 5 * 5, 5).flat_map(map_fn)
57 return dataset_ops.Dataset.range(100).map(map_fn)
59 return dataset_ops.Dataset.range(5).flat_map(flat_map_fn)
73 return dataset_ops.Dataset.from_tensor_slices([defun_fn(x)])
75 return dataset_ops.Dataset.range(100).flat_map(map_fn)
84 return dataset_ops.Dataset.range(5).flat_map(
85 lambda _: dataset_ops.Dataset.from_tensor_slices([test_var]))
99 return dataset_ops.Dataset.range(100).map(map_fn)
101 return dataset_ops.Dataset.range(5).flat_map(flat_map_fn
[all...] |
| concatenate_dataset_op_test.py | 36 return dataset_ops.Dataset.from_tensor_slices(input_components).concatenate(
37 dataset_ops.Dataset.from_tensor_slices(to_concatenate_components))
|
| zip_dataset_op_test.py | 37 dataset_ops.Dataset.from_tensor_slices(component)
40 return dataset_ops.Dataset.zip((datasets[0], (datasets[1], datasets[2])))
|
| /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/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/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)) {}
|
| /external/tensorflow/tensorflow/contrib/eager/python/ |
| datasets_test.py | 25 from tensorflow.python.data import Dataset
40 for t in datasets.Iterator(Dataset.range(4)):
45 iterator = datasets.Iterator(Dataset.range(4))
54 ds = Dataset.range(4)
64 ds = Dataset.zip((Dataset.range(4), Dataset.zip((Dataset.range(4),
65 Dataset.range(4)))))
80 it = datasets.Iterator(Dataset.range(8).map(math_ops.square).filter(even)
[all...] |
| /external/tensorflow/tensorflow/python/data/kernel_tests/ |
| shard_dataset_op_test.py | 28 dataset = dataset_ops.Dataset.range(10).shard(5, 2)
29 iterator = dataset.make_one_shot_iterator()
38 dataset_a = dataset_ops.Dataset.range(10)
39 dataset_b = dataset_ops.Dataset.range(10, 0, -1)
40 dataset = dataset_ops.Dataset.zip((dataset_a, dataset_b)).shard(5, 2)
41 iterator = dataset.make_one_shot_iterator()
50 dataset = dataset_ops.Dataset.range(10).shard(5, 0
[all...] |
| flat_map_dataset_op_test.py | 40 dataset_ops.Dataset.from_tensor_slices(components)
41 .flat_map(lambda x: dataset_ops.Dataset.from_tensors([x]).repeat(x))
58 dataset_ops.Dataset.from_tensor_slices(components)
59 .flat_map(lambda x: dataset_ops.Dataset.from_tensor_slices(x)
60 .flat_map(lambda y: dataset_ops.Dataset.from_tensors(y)
79 dataset_ops.Dataset.from_tensor_slices(components)
80 .flat_map(lambda x: dataset_ops.Dataset.from_tensor_slices(x)
81 .flat_map(lambda y: dataset_ops.Dataset.from_tensors(y)
108 iterator = (dataset_ops.Dataset.range(10)
110 .flat_map(lambda d: dataset_ops.Dataset.from_tensors(d["foo"]
[all...] |
| /external/tensorflow/tensorflow/core/kernels/data/ |
| skip_dataset_op.cc | 17 #include "tensorflow/core/kernels/data/dataset.h"
33 // Create a new RepeatDatasetOp::Dataset, and return it as the output.
37 *output = new Dataset(ctx, count, input);
41 class Dataset : public GraphDatasetBase {
43 Dataset(OpKernelContext* ctx, int64 count, const DatasetBase* input)
48 ~Dataset() override { input_->Unref(); }
71 string DebugString() override { return "SkipDatasetOp::Dataset"; }
86 class EmptyIterator : public DatasetIterator<Dataset> {
89 : DatasetIterator<Dataset>(params) {}
108 class FiniteIterator : public DatasetIterator<Dataset> {
[all...] |
| take_dataset_op.cc | 17 #include "tensorflow/core/kernels/data/dataset.h"
34 // Create a new TakeDatasetOp::Dataset, and return it as the output.
37 *output = new Dataset(ctx, count, input);
41 class Dataset : public GraphDatasetBase {
43 Dataset(OpKernelContext* ctx, int64 count, const DatasetBase* input)
48 ~Dataset() override { input_->Unref(); }
72 string DebugString() override { return "TakeDatasetOp::Dataset"; }
87 class EmptyIterator : public DatasetIterator<Dataset> {
90 : DatasetIterator<Dataset>(params) {}
109 class FiniteIterator : public DatasetIterator<Dataset> {
[all...] |
| 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...] |
| 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_;
|
| repeat_dataset_op.cc | 17 #include "tensorflow/core/kernels/data/dataset.h"
34 // Create a new RepeatDatasetOp::Dataset, insert it in the step-local
38 *output = new Dataset(ctx, count, input);
42 class Dataset : public GraphDatasetBase {
44 Dataset(OpKernelContext* ctx, int64 count, const DatasetBase* input)
49 ~Dataset() override { input_->Unref(); }
72 string DebugString() override { return "RepeatDatasetOp::Dataset"; }
87 class EmptyIterator : public DatasetIterator<Dataset> {
90 : DatasetIterator<Dataset>(params) {}
108 class FiniteIterator : public DatasetIterator<Dataset> {
[all...] |
| zip_dataset_op.cc | 17 #include "tensorflow/core/kernels/data/dataset.h"
37 *output = new Dataset(ctx, inputs);
41 class Dataset : public GraphDatasetBase {
43 explicit Dataset(OpKernelContext* ctx,
57 ~Dataset() override {
77 string DebugString() override { return "ZipDatasetOp::Dataset"; }
95 class Iterator : public DatasetIterator<Dataset> {
98 : DatasetIterator<Dataset>(params) {
99 input_impls_.reserve(params.dataset->inputs_.size());
101 for (const auto& input : params.dataset->inputs_)
[all...] |
| /external/tensorflow/tensorflow/contrib/slim/python/slim/data/ |
| dataset.py | 15 """Contains the definition of a Dataset.
17 A Dataset is a collection of several components: (1) a list of data sources
23 Data can be loaded from a dataset specification using a dataset_data_provider:
25 dataset = CreateMyDataset(...)
27 dataset, shuffle=False)
38 class Dataset(object):
39 """Represents a Dataset specification."""
43 """Initializes the dataset.
46 data_sources: A list of files that make up the dataset.
50 num_samples: The number of samples in the dataset
[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...] |
| /packages/experimental/FillService/src/foo/bar/fill/ |
| AuthActivity.java | 9 import android.service.autofill.Dataset;
31 final Dataset dataset; local
41 .addDataset(new Dataset.Builder(presentation1)
47 .addDataset(new Dataset.Builder(presentation2)
54 dataset = null;
59 dataset = new Dataset.Builder(presentation)
74 result.putExtra(AutofillManager.EXTRA_AUTHENTICATION_RESULT, dataset);
|
| /developers/build/prebuilts/gradle/AutofillFramework/kotlinApp/Application/src/main/java/com/example/android/autofillframework/multidatasetservice/ |
| AutofillHelper.kt | 19 import android.service.autofill.Dataset
38 * Wraps autofill data in a [Dataset] object which can then be sent back to the
43 datasetAuth: Boolean): Dataset? {
45 val datasetBuilder: Dataset.Builder
47 datasetBuilder = Dataset.Builder(newRemoteViews(context.packageName, datasetName,
52 datasetBuilder = Dataset.Builder(newRemoteViews(context.packageName, datasetName,
83 val dataset = newDataset(context, autofillFieldMetadata, clientFormData, datasetAuth)
84 dataset?.let(responseBuilder::addDataset)
|
| /developers/samples/android/input/autofill/AutofillFramework/kotlinApp/Application/src/main/java/com/example/android/autofillframework/multidatasetservice/ |
| AutofillHelper.kt | 19 import android.service.autofill.Dataset
38 * Wraps autofill data in a [Dataset] object which can then be sent back to the
43 datasetAuth: Boolean): Dataset? {
45 val datasetBuilder: Dataset.Builder
47 datasetBuilder = Dataset.Builder(newRemoteViews(context.packageName, datasetName,
52 datasetBuilder = Dataset.Builder(newRemoteViews(context.packageName, datasetName,
83 val dataset = newDataset(context, autofillFieldMetadata, clientFormData, datasetAuth)
84 dataset?.let(responseBuilder::addDataset)
|
| /external/icu/icu4j/perf-tests/ |
| Dataset.pm | 9 package Dataset;
14 # Create a new Dataset with the given data.
63 # Return a 99% error based on the t distribution. The dataset
71 # mean+/-error. The new Dataset has no data points.
81 my $result = Dataset->new();
|
