# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Import core names of TensorFlow.
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Programs that want to build TensorFlow Ops and Graphs without having to import
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the constructors and utilities individually can import this file:
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import tensorflow as tf
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"""
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import ctypes
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import importlib
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import sys
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import traceback
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# TODO(drpng): write up instructions for editing this file in a doc and point to
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# the doc instead.
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# If you want to edit this file to expose modules in public tensorflow API, you
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# need to follow these steps:
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# 1. Consult with tensorflow team and get approval for adding a new API to the
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# public interface.
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# 2. Document the module in the gen_docs_combined.py.
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# 3. Import the module in the main tensorflow namespace by adding an import
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# statement in this file.
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# 4. Sanitize the entry point by making sure that your module does not expose
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# transitively imported modules used for implementation, such as os, sys.
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# go/tf-wildcard-import
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# pylint: disable=wildcard-import,g-bad-import-order,g-import-not-at-top
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import numpy as np
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from tensorflow.python import pywrap_tensorflow
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# Protocol buffers
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from tensorflow.core.framework.graph_pb2 import *
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from tensorflow.core.framework.node_def_pb2 import *
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from tensorflow.core.framework.summary_pb2 import *
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from tensorflow.core.framework.attr_value_pb2 import *
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from tensorflow.core.protobuf.meta_graph_pb2 import TensorInfo
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from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
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from tensorflow.core.protobuf.config_pb2 import *
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from tensorflow.core.protobuf.tensorflow_server_pb2 import *
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from tensorflow.core.util.event_pb2 import *
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# Framework
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from tensorflow.python.framework.framework_lib import * # pylint: disable=redefined-builtin
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from tensorflow.python.framework.versions import *
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from tensorflow.python.framework import config
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from tensorflow.python.framework import errors
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from tensorflow.python.framework import graph_util
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# Session
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from tensorflow.python.client.client_lib import *
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# Ops
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from tensorflow.python.ops.standard_ops import *
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# Namespaces
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from tensorflow.python.ops import initializers_ns as initializers
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# pylint: enable=wildcard-import
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# Bring in subpackages.
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from tensorflow.python import data
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from tensorflow.python import distribute
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from tensorflow.python import keras
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from tensorflow.python.feature_column import feature_column_lib as feature_column
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from tensorflow.python.layers import layers
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from tensorflow.python.module import module
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from tensorflow.python.ops import bitwise_ops as bitwise
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from tensorflow.python.ops import gradient_checker_v2
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from tensorflow.python.ops import image_ops as image
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from tensorflow.python.ops import manip_ops as manip
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from tensorflow.python.ops import metrics
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from tensorflow.python.ops import nn
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from tensorflow.python.ops import ragged
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from tensorflow.python.ops import sets
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from tensorflow.python.ops import stateful_random_ops
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from tensorflow.python.ops.distributions import distributions
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from tensorflow.python.ops.linalg import linalg
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from tensorflow.python.ops.losses import losses
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from tensorflow.python.ops.signal import signal
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from tensorflow.python.profiler import profiler
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from tensorflow.python.saved_model import saved_model
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from tensorflow.python.summary import summary
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from tensorflow.python.user_ops import user_ops
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from tensorflow.python.util import compat
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# Import audio ops to make sure the ops are registered.
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from tensorflow.python.ops import gen_audio_ops as _
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# Import boosted trees ops to make sure the ops are registered (but unused).
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from tensorflow.python.ops import gen_boosted_trees_ops as _gen_boosted_trees_ops
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# Import cudnn rnn ops to make sure their ops are registered.
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from tensorflow.python.ops import gen_cudnn_rnn_ops as _
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# Import the names from python/training.py as train.Name.
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from tensorflow.python.training import training as train
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# Sub-package for performing i/o directly instead of via ops in a graph.
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from tensorflow.python.lib.io import python_io
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# Make some application and test modules available.
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from tensorflow.python.platform import app
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from tensorflow.python.platform import flags
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from tensorflow.python.platform import gfile
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from tensorflow.python.platform import tf_logging as logging
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from tensorflow.python.platform import resource_loader
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from tensorflow.python.platform import sysconfig
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from tensorflow.python.platform import test
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from tensorflow.python.compat import v2_compat
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from tensorflow.python.util.all_util import make_all
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from tensorflow.python.util.tf_export import tf_export
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# Eager execution
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from tensorflow.python.eager.context import executing_eagerly
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from tensorflow.python.eager.remote import connect_to_remote_host
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from tensorflow.python.eager.def_function import function
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from tensorflow.python.framework.ops import enable_eager_execution
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# Necessary for the symbols in this module to be taken into account by
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# the namespace management system (API decorators).
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from tensorflow.python.ops import rnn
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from tensorflow.python.ops import rnn_cell
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# Required due to `rnn` and `rnn_cell` not being imported in `nn` directly
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# (due to a circular dependency issue: rnn depends on layers).
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nn.dynamic_rnn = rnn.dynamic_rnn
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nn.static_rnn = rnn.static_rnn
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nn.raw_rnn = rnn.raw_rnn
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nn.bidirectional_dynamic_rnn = rnn.bidirectional_dynamic_rnn
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nn.static_state_saving_rnn = rnn.static_state_saving_rnn
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nn.rnn_cell = rnn_cell
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# Export protos
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# pylint: disable=undefined-variable
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tf_export(v1=['AttrValue'])(AttrValue)
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tf_export(v1=['ConfigProto'])(ConfigProto)
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tf_export(v1=['Event', 'summary.Event'])(Event)
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tf_export(v1=['GPUOptions'])(GPUOptions)
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tf_export(v1=['GraphDef'])(GraphDef)
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tf_export(v1=['GraphOptions'])(GraphOptions)
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tf_export(v1=['HistogramProto'])(HistogramProto)
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tf_export(v1=['LogMessage'])(LogMessage)
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tf_export(v1=['MetaGraphDef'])(MetaGraphDef)
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tf_export(v1=['NameAttrList'])(NameAttrList)
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tf_export(v1=['NodeDef'])(NodeDef)
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tf_export(v1=['OptimizerOptions'])(OptimizerOptions)
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tf_export(v1=['RunMetadata'])(RunMetadata)
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tf_export(v1=['RunOptions'])(RunOptions)
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tf_export(v1=['SessionLog', 'summary.SessionLog'])(SessionLog)
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tf_export(v1=['Summary', 'summary.Summary'])(Summary)
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tf_export(v1=['summary.SummaryDescription'])(SummaryDescription)
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tf_export(v1=['SummaryMetadata'])(SummaryMetadata)
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tf_export(v1=['summary.TaggedRunMetadata'])(TaggedRunMetadata)
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tf_export(v1=['TensorInfo'])(TensorInfo)
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# pylint: enable=undefined-variable
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# Special dunders that we choose to export:
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_exported_dunders = set([
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'__version__',
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'__git_version__',
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'__compiler_version__',
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'__cxx11_abi_flag__',
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'__monolithic_build__',
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])
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# Expose symbols minus dunders, unless they are whitelisted above.
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# This is necessary to export our dunders.
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__all__ = [s for s in dir() if s in _exported_dunders or not s.startswith('_')]
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