EVOLUTION-MANAGER

Edit File: __init__.py

# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Experimental API for building input pipelines. This module contains experimental `Dataset` sources and transformations that can be used in conjunction with the `tf.data.Dataset` API. Note that the `tf.data.experimental` API is not subject to the same backwards compatibility guarantees as `tf.data`, but we will provide deprecation advice in advance of removing existing functionality. See [Importing Data](https://tensorflow.org/guide/datasets) for an overview. @@AutoShardPolicy @@Counter @@CheckpointInputPipelineHook @@CsvDataset @@DatasetStructure @@DistributeOptions @@MapVectorizationOptions @@OptimizationOptions @@Optional @@OptionalStructure @@RaggedTensorStructure @@RandomDataset @@Reducer @@SparseTensorStructure @@SqlDataset @@StatsAggregator @@StatsOptions @@Structure @@TFRecordWriter @@TensorArrayStructure @@TensorStructure @@ThreadingOptions @@assert_cardinality @@bucket_by_sequence_length @@bytes_produced_stats @@cardinality @@choose_from_datasets @@copy_to_device @@dense_to_ragged_batch @@dense_to_sparse_batch @@distribute @@enumerate_dataset @@from_variant @@get_next_as_optional @@get_single_element @@get_structure @@group_by_reducer @@group_by_window @@ignore_errors @@latency_stats @@load @@make_batched_features_dataset @@make_csv_dataset @@make_saveable_from_iterator @@map_and_batch @@map_and_batch_with_legacy_function @@parallel_interleave @@parse_example_dataset @@prefetch_to_device @@rejection_resample @@sample_from_datasets @@save @@scan @@shuffle_and_repeat @@snapshot @@take_while @@to_variant @@unbatch @@unique @@AUTOTUNE @@INFINITE_CARDINALITY @@UNKNOWN_CARDINALITY """ from __future__ import absolute_import from __future__ import division from __future__ import print_function # pylint: disable=unused-import from tensorflow.python.data.experimental import service from tensorflow.python.data.experimental.ops.batching import dense_to_ragged_batch from tensorflow.python.data.experimental.ops.batching import dense_to_sparse_batch from tensorflow.python.data.experimental.ops.batching import map_and_batch from tensorflow.python.data.experimental.ops.batching import map_and_batch_with_legacy_function from tensorflow.python.data.experimental.ops.batching import unbatch from tensorflow.python.data.experimental.ops.cardinality import assert_cardinality from tensorflow.python.data.experimental.ops.cardinality import cardinality from tensorflow.python.data.experimental.ops.cardinality import INFINITE as INFINITE_CARDINALITY from tensorflow.python.data.experimental.ops.cardinality import UNKNOWN as UNKNOWN_CARDINALITY from tensorflow.python.data.experimental.ops.counter import Counter from tensorflow.python.data.experimental.ops.distribute_options import AutoShardPolicy from tensorflow.python.data.experimental.ops.distribute_options import DistributeOptions from tensorflow.python.data.experimental.ops.enumerate_ops import enumerate_dataset from tensorflow.python.data.experimental.ops.error_ops import ignore_errors from tensorflow.python.data.experimental.ops.get_single_element import get_single_element from tensorflow.python.data.experimental.ops.grouping import bucket_by_sequence_length from tensorflow.python.data.experimental.ops.grouping import group_by_reducer from tensorflow.python.data.experimental.ops.grouping import group_by_window from tensorflow.python.data.experimental.ops.grouping import Reducer from tensorflow.python.data.experimental.ops.interleave_ops import choose_from_datasets from tensorflow.python.data.experimental.ops.interleave_ops import parallel_interleave from tensorflow.python.data.experimental.ops.interleave_ops import sample_from_datasets from tensorflow.python.data.experimental.ops.io import load from tensorflow.python.data.experimental.ops.io import save from tensorflow.python.data.experimental.ops.iterator_ops import CheckpointInputPipelineHook from tensorflow.python.data.experimental.ops.iterator_ops import make_saveable_from_iterator from tensorflow.python.data.experimental.ops.optimization_options import MapVectorizationOptions from tensorflow.python.data.experimental.ops.optimization_options import OptimizationOptions from tensorflow.python.data.experimental.ops.parsing_ops import parse_example_dataset from tensorflow.python.data.experimental.ops.prefetching_ops import copy_to_device from tensorflow.python.data.experimental.ops.prefetching_ops import prefetch_to_device from tensorflow.python.data.experimental.ops.random_ops import RandomDataset from tensorflow.python.data.experimental.ops.readers import CsvDataset from tensorflow.python.data.experimental.ops.readers import make_batched_features_dataset from tensorflow.python.data.experimental.ops.readers import make_csv_dataset from tensorflow.python.data.experimental.ops.readers import SqlDataset from tensorflow.python.data.experimental.ops.resampling import rejection_resample from tensorflow.python.data.experimental.ops.scan_ops import scan from tensorflow.python.data.experimental.ops.shuffle_ops import shuffle_and_repeat from tensorflow.python.data.experimental.ops.snapshot import snapshot from tensorflow.python.data.experimental.ops.stats_aggregator import StatsAggregator from tensorflow.python.data.experimental.ops.stats_ops import bytes_produced_stats from tensorflow.python.data.experimental.ops.stats_ops import latency_stats from tensorflow.python.data.experimental.ops.stats_options import StatsOptions from tensorflow.python.data.experimental.ops.take_while_ops import take_while from tensorflow.python.data.experimental.ops.threading_options import ThreadingOptions from tensorflow.python.data.experimental.ops.unique import unique from tensorflow.python.data.experimental.ops.writers import TFRecordWriter from tensorflow.python.data.ops.dataset_ops import AUTOTUNE from tensorflow.python.data.ops.dataset_ops import DatasetSpec as DatasetStructure from tensorflow.python.data.ops.dataset_ops import from_variant from tensorflow.python.data.ops.dataset_ops import get_structure from tensorflow.python.data.ops.dataset_ops import to_variant from tensorflow.python.data.ops.iterator_ops import get_next_as_optional from tensorflow.python.data.ops.optional_ops import Optional from tensorflow.python.data.ops.optional_ops import OptionalSpec as OptionalStructure from tensorflow.python.data.util.structure import _RaggedTensorStructure as RaggedTensorStructure from tensorflow.python.data.util.structure import _SparseTensorStructure as SparseTensorStructure from tensorflow.python.data.util.structure import _TensorArrayStructure as TensorArrayStructure from tensorflow.python.data.util.structure import _TensorStructure as TensorStructure from tensorflow.python.framework.type_spec import TypeSpec as Structure # pylint: enable=unused-import from tensorflow.python.util.all_util import remove_undocumented _allowed_symbols = [ "service", ] remove_undocumented(__name__, _allowed_symbols)