# Copyright 2019 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.
# ==============================================================================
# LINT.IfChange
"""TensorFlow root package"""

import sys as _sys
import importlib as _importlib
import types as _types


# Since TensorFlow Python code now resides in tensorflow_core but TensorFlow
# ecosystem code (e.g. estimator, but also even tensorflow) imports tensorflow
# we need to do forwarding between the two. To do so, we use a lazy loader to
# load and forward the top level modules. We cannot use the LazyLoader defined
# by tensorflow at tensorflow/python/util/lazy_loader.py as to use that we would
# already need to import tensorflow. Hence, we define it inline.
class _LazyLoader(_types.ModuleType):
  """Lazily import a module so that we can forward it."""

  # The lint error here is incorrect.
  def __init__(self, local_name, parent_module_globals, name):
    self._local_name = local_name
    self._parent_module_globals = parent_module_globals
    super(_LazyLoader, self).__init__(name)

  def _load(self):
    """Import the target module and insert it into the parent's namespace."""
    module = _importlib.import_module(self.__name__)
    self._parent_module_globals[self._local_name] = module
    self.__dict__.update(module.__dict__)
    return module

  def __getattr__(self, item):
    module = self._load()
    return getattr(module, item)

  def __dir__(self):
    module = self._load()
    return dir(module)

  def __reduce__(self):
    return __import__, (self.__name__,)


# Forwarding a module is as simple as lazy loading the module from the new path
# and then registering it to sys.modules using the old path
def _forward_module(old_name):
  parts = old_name.split(".")
  parts[0] = parts[0] + "_core"
  local_name = parts[-1]
  existing_name = ".".join(parts)
  _module = _LazyLoader(local_name, globals(), existing_name)
  return _sys.modules.setdefault(old_name, _module)


# This list should contain all modules _immediately_ under tensorflow
_top_level_modules = [
    "tensorflow._api",
    "tensorflow.python",
    "tensorflow.tools",
    "tensorflow.core",
    "tensorflow.compiler",
    "tensorflow.lite",
    "tensorflow.keras",
    "tensorflow.compat",
    "tensorflow.summary",  # tensorboard
    "tensorflow.examples",
]
# Estimator needs to be handled separatedly so we can still allow both
# import tensorflow_estimator and import tensorflow.estimator work
# Only in the second case do we actually need to do forwarding, the first case
# already defines most of the hierarchy and eagerly forwarding would result in
# an import loop.
if "tensorflow_estimator" not in _sys.modules:
  _root_estimator = False
  _top_level_modules.append("tensorflow.estimator")
else:
  _root_estimator = True

# Lazy load all of the _top_level_modules, we don't need their names anymore
for _m in _top_level_modules:
  _forward_module(_m)

# We still need all the names that are toplevel on tensorflow_core
from tensorflow_core import *

_major_api_version = 2

# These should not be visible in the main tf module.
try:
  del core
except NameError:
  pass

try:
  del python
except NameError:
  pass

try:
  del compiler
except NameError:
  pass

try:
  del tools
except NameError:
  pass

try:
  del examples
except NameError:
  pass

# LINT.ThenChange(//tensorflow/virtual_root_template_v1.__init__.py.oss)