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# 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.
# ==============================================================================
"""TensorBoard is a webapp for understanding TensorFlow runs and graphs."""
from tensorboard import lazy as _lazy
from tensorboard import version as _version
# TensorBoard public API.
__all__ = [
"__version__",
"errors",
"notebook",
"program",
"summary",
]
# Please be careful when changing the structure of this file.
#
# The lazy imports in this file must use `importlib.import_module`, not
# `import tensorboard.foo` or `from tensorboard import foo`, or it will
# be impossible to reload the TensorBoard module without breaking these
# top-level public APIs. This has to do with the gory details of
# Python's module system. Take `tensorboard.notebook` as an example:
#
# - When the `tensorboard` module (that's us!) is initialized, its
# `notebook` attribute is initialized to a new LazyModule. The
# actual `tensorboard.notebook` submodule is not loaded.
#
# - When the `tensorboard.notebook` submodule is first loaded, Python
# _reassigns_ the `notebook` attribute on the `tensorboard` module
# object to point to the underlying `tensorboard.notebook` module
# object, rather than its former LazyModule value. This occurs
# whether the module is loaded via the lazy module or directly as an
# import:
#
# - import tensorboard; tensorboard.notebook.start(...) # one way
# - from tensorboard import notebook # other way; same effect
#
# - When the `tensorboard` module is reloaded, its `notebook`
# attribute is once again bound to a (new) LazyModule, while the
# `tensorboard.notebook` module object is unaffected and still
# exists in `sys.modules`. But then...
#
# - When the new LazyModule is forced, it must resolve to the existing
# `tensorboard.notebook` module object rather than itself (which
# just creates a stack overflow). If the LazyModule load function
# uses `import tensorboard.notebook; return tensorboard.notebook`,
# then the first statement will do _nothing_ because the
# `tensorboard.notebook` module is already loaded, and the second
# statement will return the LazyModule itself. The same goes for the
# `from tensorboard import notebook` form. We need to ensure that
# the submodule is loaded and then pull the actual module object out
# of `sys.modules`... which is exactly what `importlib` handles for
# us.
#
# See <https://github.com/tensorflow/tensorboard/issues/1989> for
# additional discussion.
@_lazy.lazy_load("tensorboard.errors")
def errors():
import importlib
return importlib.import_module("tensorboard.errors")
@_lazy.lazy_load("tensorboard.notebook")
def notebook():
import importlib
return importlib.import_module("tensorboard.notebook")
@_lazy.lazy_load("tensorboard.program")
def program():
import importlib
return importlib.import_module("tensorboard.program")
@_lazy.lazy_load("tensorboard.summary")
def summary():
import importlib
return importlib.import_module("tensorboard.summary")
def load_ipython_extension(ipython):
"""IPython API entry point.
Only intended to be called by the IPython runtime.
See:
https://ipython.readthedocs.io/en/stable/config/extensions/index.html
"""
notebook._load_ipython_extension(ipython)
__version__ = _version.VERSION
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