| /external/autotest/client/tests/compilebench/ |
| compilebench-0.6.tar.gz | |
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| api_def_ConcatenateDataset.pbtxt | 3 summary: "Creates a dataset that concatenates `input_dataset` with `another_dataset`."
|
| api_def_ZipDataset.pbtxt | 3 summary: "Creates a dataset that zips together `input_datasets`."
|
| api_def_PrefetchDataset.pbtxt | 7 this dataset.
10 summary: "Creates a dataset that asynchronously prefetches elements from `input_dataset`."
|
| api_def_FlatMapDataset.pbtxt | 7 `other_arguments`, to a Dataset variant that contains elements matching
11 summary: "Creates a dataset that applies `f` to the outputs of `input_dataset`."
14 Dataset variant, and FlatMapDataset will flatten successive results
15 into a single Dataset.
|
| api_def_MapDataset.pbtxt | 3 summary: "Creates a dataset that applies `f` to the outputs of `input_dataset`."
|
| api_def_ScanDataset.pbtxt | 3 summary: "Creates a dataset successively reduces `f` over the elements of `input_dataset`."
|
| api_def_SparseTensorSliceDataset.pbtxt | 3 summary: "Creates a dataset that splits a SparseTensor into elements row-wise."
|
| api_def_TensorDataset.pbtxt | 3 summary: "Creates a dataset that emits `components` as a tuple of tensors once."
|
| api_def_TensorSliceDataset.pbtxt | 3 summary: "Creates a dataset that emits each dim-0 slice of `components` once."
|
| api_def_UniqueDataset.pbtxt | 3 summary: "Creates a dataset that contains the unique elements of `input_dataset`."
|
| api_def_DatasetToSingleElement.pbtxt | 4 name: "dataset"
6 A handle to a dataset that contains a single element.
15 summary: "Outputs the single element from the given dataset."
|
| api_def_ParallelInterleaveDataset.pbtxt | 7 `other_arguments`, to a Dataset variant that contains elements matching
11 summary: "Creates a dataset that applies `f` to the outputs of `input_dataset`."
13 The resulting dataset is similar to the `InterleaveDataset`, with the exception
14 that if retrieving the next value from a dataset would cause the requester to
15 block, it will skip that input dataset. This dataset is especially useful
19 !! WARNING !! This dataset is not deterministic!
|
| api_def_InterleaveDataset.pbtxt | 7 `other_arguments`, to a Dataset variant that contains elements matching
11 summary: "Creates a dataset that applies `f` to the outputs of `input_dataset`."
14 a Dataset variant, and InterleaveDataset will flatten successive
15 results into a single Dataset. Unlike FlatMapDataset,
|
| api_def_MakeIterator.pbtxt | 3 summary: "Makes a new iterator from the given `dataset` and stores it in `iterator`."
6 iterator in `iterator` to the first element of `dataset`.
|
| api_def_ParallelMapDataset.pbtxt | 10 summary: "Creates a dataset that applies `f` to the outputs of `input_dataset`."
12 Unlike a "MapDataset", which applies `f` sequentially, this dataset invokes up
|
| /external/tensorflow/tensorflow/docs_src/api_guides/python/ |
| input_dataset.md | 0 # Dataset Input Pipeline
4 @{tf.data.Dataset} allows you to build complex input pipelines. See the
10 Classes that create a dataset from input files.
18 Static methods in `Dataset` that create new datasets.
20 * @{tf.data.Dataset.from_generator}
21 * @{tf.data.Dataset.from_tensor_slices}
22 * @{tf.data.Dataset.from_tensors}
23 * @{tf.data.Dataset.list_files}
24 * @{tf.data.Dataset.range}
25 * @{tf.data.Dataset.zip
[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...] |
| batching.py | 15 """Batching dataset transformations."""
36 Like `Dataset.padded_batch()`, this transformation combines multiple
37 consecutive elements of the dataset, which might have different
47 # contents of a dataset.
63 number of consecutive elements of this dataset to combine in a
67 resulting `tf.SparseTensor`. Each element of this dataset must
72 A `Dataset` transformation function, which can be passed to
73 @{tf.data.Dataset.apply}.
76 def _apply_fn(dataset):
77 return DenseToSparseBatchDataset(dataset, batch_size, row_shape
[all...] |
| get_single_element.py | 25 def get_single_element(dataset):
26 """Returns the single element in `dataset` as a nested structure of tensors.
28 This function enables you to use a @{tf.data.Dataset} in a stateless
31 as a `Dataset`, and you want to use the transformation at serving time.
41 dataset = (tf.data.Dataset.from_tensor_slices(input_batch)
45 image_batch, label_batch = tf.contrib.data.get_single_element(dataset)
49 dataset: A @{tf.data.Dataset} object containing a single element.
53 element of `dataset`
[all...] |
| /external/tensorflow/tensorflow/contrib/data/ |
| README.md | 12 The `tf.contrib.data.Dataset` class has been renamed to `tf.data.Dataset`, and
17 The arguments accepted by the `Dataset.map()` transformation have changed:
19 * `dataset.map(..., num_threads=T)` is now `dataset.map(num_parallel_calls=T)`.
20 * `dataset.map(..., output_buffer_size=B)` is now
21 `dataset.map(...).prefetch(B)`.
23 Some transformations have been removed from `tf.data.Dataset`, and you must
24 instead apply them using `Dataset.apply()` transformation. The full list of
27 * `dataset.dense_to_sparse_batch(...)` is no
[all...] |
| /external/tensorflow/tensorflow/docs_src/programmers_guide/ |
| datasets.md | 15 * A `tf.data.Dataset` represents a sequence of elements, in which
19 ways to create a dataset:
21 * Creating a **source** (e.g. `Dataset.from_tensor_slices()`) constructs a
22 dataset from
25 * Applying a **transformation** (e.g. `Dataset.batch()`) constructs a dataset
26 from one or more `tf.data.Dataset` objects.
29 dataset. The operation returned by `Iterator.get_next()` yields the next
30 element of a `Dataset` when executed, and typically acts as the interface
32 "one-shot iterator", which is associated with a particular `Dataset` an
[all...] |
| /external/protobuf/benchmarks/ |
| README.md | 15 Wrote dataset: dataset.google_message1_proto3.pb
16 Wrote dataset: dataset.google_message1_proto2.pb
17 Wrote dataset: dataset.google_message2.pb
|
| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| tensor_queue_dataset_test.py | 37 dataset = dataset_ops.Dataset.from_tensor_slices([0, 1, 2])
38 dataset = dataset.apply(
40 self.assertEqual((dtypes.variant, dtypes.int32), dataset.output_types)
42 [x.as_list() for x in dataset.output_shapes])
43 iterator = dataset.make_one_shot_iterator()
52 dataset = dataset_ops.Dataset.from_tensor_slices([0, 1, 2])
53 dataset = dataset.apply
[all...] |
| /external/tensorflow/tensorflow/core/kernels/data/ |
| BUILD | 49 name = "dataset",
51 hdrs = ["dataset.h"],
68 ":dataset",
81 ":dataset",
96 ":dataset",
107 ":dataset",
120 ":dataset",
133 ":dataset",
146 ":dataset",
161 ":dataset",
[all...] |
