Intelegentny_Pszczelarz/.venv/Lib/site-packages/tensorboard/backend/client_feature_flags.py
2023-06-19 00:49:18 +02:00

64 lines
2.4 KiB
Python

# Copyright 2022 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.
# ==============================================================================
"""Middleware for injecting client-side feature flags into the Context."""
import json
from tensorboard import context
from tensorboard import errors
class ClientFeatureFlagsMiddleware:
"""Middleware for injecting client-side feature flags into the Context.
The client webapp is expected to include a json-serialized version of its
FeatureFlags in the `X-TensorBoard-Feature-Flags` header. This middleware
extracts the header value and converts it into the client_feature_flags
property for the DataProvider's Context object, where client_feature_flags
is a Dict of string keys and arbitrary value types.
"""
def __init__(self, application):
"""Initializes this middleware.
Args:
application: The WSGI application to wrap (see PEP 3333).
"""
self._application = application
def __call__(self, environ, start_response):
possible_feature_flags = environ.get("HTTP_X_TENSORBOARD_FEATURE_FLAGS")
if not possible_feature_flags:
return self._application(environ, start_response)
try:
client_feature_flags = json.loads(possible_feature_flags)
except json.JSONDecodeError:
raise errors.InvalidArgumentError(
"X-TensorBoard-Feature-Flags cannot be JSON decoded."
)
if not isinstance(client_feature_flags, dict):
raise errors.InvalidArgumentError(
"X-TensorBoard-Feature-Flags cannot be decoded to a dict."
)
ctx = context.from_environ(environ).replace(
client_feature_flags=client_feature_flags
)
context.set_in_environ(environ, ctx)
return self._application(environ, start_response)