laywerrobot/lib/python3.6/site-packages/tensorflow/python/__init__.py
2020-08-27 21:55:39 +02:00

178 lines
6.7 KiB
Python

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