_tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__)) _current_module = _sys.modules[__name__] if not hasattr(_current_module, '__path__'): __path__ = [_tf_api_dir] elif _tf_api_dir not in __path__: __path__.append(_tf_api_dir) # Hook external TensorFlow modules. # Import compat before trying to import summary from tensorboard, so that # reexport_tf_summary can get compat from sys.modules _current_module.compat.v2.compat.v1 = _current_module.compat.v1 try: from tensorboard.summary._tf import summary _current_module.__path__ = ([_module_util.get_parent_dir(summary)] + _current_module.__path__) setattr(_current_module, "summary", summary) except ImportError: _logging.warning( "Limited tf.summary API due to missing TensorBoard installation.") try: from tensorflow_estimator.python.estimator.api._v2 import estimator _current_module.__path__ = ([_module_util.get_parent_dir(estimator)] + _current_module.__path__) setattr(_current_module, "estimator", estimator) except ImportError: pass try:
import logging as _logging import os as _os import sys as _sys from tensorflow.python.tools import module_util as _module_util # pylint: disable=g-bad-import-order # API IMPORTS PLACEHOLDER # Hook external TensorFlow modules. _current_module = _sys.modules[__name__] try: from tensorboard.summary._tf import summary _current_module.__path__ = ( [_module_util.get_parent_dir(summary)] + _current_module.__path__) except ImportError: _logging.warning( "Limited tf.compat.v2.summary API due to missing TensorBoard " "installation.") try: from tensorflow_estimator.python.estimator.api._v2 import estimator _current_module.__path__ = ( [_module_util.get_parent_dir(estimator)] + _current_module.__path__) except ImportError: pass try: from tensorflow.python.keras.api._v2 import keras _current_module.__path__ = (
# Hook external TensorFlow modules. _current_module = _sys.modules[__name__] # Lazy-load estimator. _estimator_module = "tensorflow_estimator.python.estimator.api._v1.estimator" estimator = _LazyLoader("estimator", globals(), _estimator_module) _module_dir = _module_util.get_parent_dir_for_name(_estimator_module) if _module_dir: _current_module.__path__ = [_module_dir] + _current_module.__path__ setattr(_current_module, "estimator", estimator) try: from tensorflow.python.keras.api._v1 import keras _current_module.__path__ = ( [_module_util.get_parent_dir(keras)] + _current_module.__path__) setattr(_current_module, "keras", keras) except ImportError: pass # Explicitly import lazy-loaded modules to support autocompletion. # pylint: disable=g-import-not-at-top if not _six.PY2: import typing as _typing if _typing.TYPE_CHECKING: from tensorflow_estimator.python.estimator.api._v1 import estimator # pylint: enable=g-import-not-at-top from tensorflow.python.platform import flags # pylint: disable=g-import-not-at-top _current_module.app.flags = flags # pylint: disable=undefined-variable
from __future__ import print_function as _print_function import os as _os import sys as _sys from tensorflow.python.tools import module_util as _module_util # pylint: disable=g-bad-import-order # API IMPORTS PLACEHOLDER # Hook external TensorFlow modules. _current_module = _sys.modules[__name__] try: from tensorflow_estimator.python.estimator.api._v1 import estimator _current_module.__path__ = ( [_module_util.get_parent_dir(estimator)] + _current_module.__path__) except ImportError: pass try: from tensorflow.python.keras.api._v1 import keras _current_module.__path__ = ( [_module_util.get_parent_dir(keras)] + _current_module.__path__) except ImportError: pass from tensorflow.python.platform import flags # pylint: disable=g-import-not-at-top app.flags = flags # pylint: disable=undefined-variable
import logging as _logging import os as _os import sys as _sys from tensorflow.python.tools import module_util as _module_util # pylint: disable=g-bad-import-order # API IMPORTS PLACEHOLDER # Hook external TensorFlow modules. _current_module = _sys.modules[__name__] try: from tensorboard.summary._tf import summary _current_module.__path__.append(_module_util.get_parent_dir(summary)) except ImportError: _logging.warning( "Limited tf.compat.v2.summary API due to missing TensorBoard " "installation.") try: from tensorflow_estimator.python.estimator.api._v2 import estimator _current_module.__path__.append(_module_util.get_parent_dir(estimator)) except ImportError: pass try: from tensorflow.python.keras.api._v2 import keras _current_module.__path__.append(_module_util.get_parent_dir(keras)) except ImportError:
from tensorflow_estimator.python.estimator.api._v1 import estimator # pylint: enable=g-import-not-at-top from tensorflow.python.platform import flags # pylint: disable=g-import-not-at-top _current_module.app.flags = flags # pylint: disable=undefined-variable setattr(_current_module, "flags", flags) # Add module aliases from Keras to TF. # Some tf endpoints actually lives under Keras. if hasattr(_current_module, "keras"): # It is possible that keras is a lazily loaded module, which might break when # actually trying to import it. Have a Try-Catch to make sure it doesn't break # when it doing some very initial loading, like tf.compat.v2, etc. try: _layer_package = "keras.api._v1.keras.__internal__.legacy.layers" layers = _LazyLoader("layers", globals(), _layer_package) _module_dir = _module_util.get_parent_dir(layers) if _module_dir: _current_module.__path__ = [_module_dir] + _current_module.__path__ setattr(_current_module, "layers", layers) _legacy_rnn_package = "keras.api._v1.keras.__internal__.legacy.rnn_cell" legacy_rnn = _LazyLoader("legacy_rnn", globals(), _legacy_rnn_package) _module_dir = _module_util.get_parent_dir(legacy_rnn) if _module_dir: _current_module.nn.__path__ = [_module_dir ] + _current_module.nn.__path__ _current_module.nn.rnn_cell = legacy_rnn except ImportError: pass
_current_module = _sys.modules[__name__] if not hasattr(_current_module, '__path__'): __path__ = [_tf_api_dir] elif _tf_api_dir not in __path__: __path__.append(_tf_api_dir) # Hook external TensorFlow modules. # Import compat before trying to import summary from tensorboard, so that # reexport_tf_summary can get compat from sys.modules. Only needed if using # lazy loading. _current_module.compat.v2 # pylint: disable=pointless-statement try: from tensorboard.summary._tf import summary _current_module.__path__ = ( [_module_util.get_parent_dir(summary)] + _current_module.__path__) setattr(_current_module, "summary", summary) except ImportError: _logging.warning( "Limited tf.summary API due to missing TensorBoard installation.") # Load tensorflow-io-gcs-filesystem if enabled # pylint: disable=g-import-not-at-top if (_os.getenv('TF_USE_MODULAR_FILESYSTEM', '0') == 'true' or _os.getenv('TF_USE_MODULAR_FILESYSTEM', '0') == '1'): import tensorflow_io_gcs_filesystem as _tensorflow_io_gcs_filesystem # pylint: enable=g-import-not-at-top # Lazy-load estimator. _estimator_module = "tensorflow_estimator.python.estimator.api._v2.estimator" estimator = _LazyLoader("estimator", globals(), _estimator_module)
# The 'app' module will be imported as part of the placeholder section above. _current_module.app.flags = flags # pylint: disable=undefined-variable setattr(_current_module, "flags", flags) _major_api_version = 1 # Add module aliases from Keras to TF. # Some tf endpoints actually lives under Keras. if hasattr(_current_module, "keras"): # It is possible that keras is a lazily loaded module, which might break when # actually trying to import it. Have a Try-Catch to make sure it doesn't break # when it doing some very initial loading, like tf.compat.v2, etc. try: _layer_package = "keras.api._v1.keras.__internal__.legacy.layers" layers = _LazyLoader("layers", globals(), _layer_package) _module_dir = _module_util.get_parent_dir(layers) if _module_dir: _current_module.__path__ = [_module_dir] + _current_module.__path__ setattr(_current_module, "layers", layers) _legacy_rnn_package = "keras.api._v1.keras.__internal__.legacy.rnn_cell" legacy_rnn = _LazyLoader("legacy_rnn", globals(), _legacy_rnn_package) _current_module.nn.rnn_cell = legacy_rnn except ImportError: pass # Load all plugin libraries from site-packages/tensorflow-plugins if we are # running under pip. # TODO(gunan): Enable setting an environment variable to define arbitrary plugin # directories. # TODO(gunan): Find a better location for this code snippet.