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

420 lines
16 KiB
Python

# 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 as: python3
"""Provides authentication support for TensorBoardUploader."""
import datetime
import errno
import json
import os
import requests
import sys
import time
import webbrowser
import google_auth_oauthlib.flow as auth_flows
import grpc
import google.auth
import google.auth.transport.requests
import google.oauth2.credentials
from tensorboard.uploader import util
from tensorboard.util import tb_logging
logger = tb_logging.get_logger()
# OAuth2 scopes used for OpenID Connect:
# https://developers.google.com/identity/protocols/OpenIDConnect#scope-param
OPENID_CONNECT_SCOPES = (
"openid",
"https://www.googleapis.com/auth/userinfo.email",
)
# This config was downloaded from our GCP project at:
# console.cloud.google.com/apis/credentials?project=hosted-tensorboard-prod
# and in b/143316611.
#
# The client "secret" is considered public, as it's distributed to the devices
# where this runs. See:
# https://developers.google.com/identity/protocols/OAuth2?csw=1#installed
#
# See below for the config for another accepted credential.
_INSTALLED_APP_OAUTH_CLIENT_CONFIG = """
{
"installed":{
"client_id":"373649185512-8v619h5kft38l4456nm2dj4ubeqsrvh6.apps.googleusercontent.com",
"project_id":"hosted-tensorboard-prod",
"auth_uri":"https://accounts.google.com/o/oauth2/auth",
"token_uri":"https://oauth2.googleapis.com/token",
"auth_provider_x509_cert_url":"https://www.googleapis.com/oauth2/v1/certs",
"client_secret":"pOyAuU2yq2arsM98Bw5hwYtr",
"redirect_uris":["http://localhost"]
}
}
"""
# These values can be updated with values from the well-known "discovery url":
# https://accounts.google.com/.well-known/openid-configuration
#
# See:
# developers.google.com/identity/openid-connect/openid-connect#discovery
_DEVICE_AUTH_CODE_URI = "https://oauth2.googleapis.com/device/code"
_LIMITED_INPUT_DEVICE_AUTH_GRANT_TYPE = (
"urn:ietf:params:oauth:grant-type:device_code"
)
# This config was downloaded from our GCP project at:
# console.cloud.google.com/apis/credentials?project=hosted-tensorboard-prod
# and in b/262276562.
#
# Note that some of these fields are not really useful for this flow.
# It seems the limited-input device flow is not quite as well supported yet by
# neither the Google python oauth libraries, nor the GCP console, so this config
# does not match what we would need to authenticate this way (starting from the
# fact that it seems to be a config for an "installed" app), but we do use some
# of them (e.g. client_id and client_secret), along with other values defined in
# separate constants for this auth flow.
#
# The client "secret" is considered public, as it's distributed to the devices
# where this runs. See:
# https://developers.google.com/identity/protocols/oauth2/limited-input-device
#
# See above for the config for another accepted credential.
_LIMITED_INPUT_DEVICE_OAUTH_CLIENT_CONFIG = """
{
"installed":{
"client_id":"373649185512-26ojik4u7dt0rdtfdmfnhpajqqh579qd.apps.googleusercontent.com",
"project_id":"hosted-tensorboard-prod",
"auth_uri":"https://accounts.google.com/o/oauth2/auth",
"token_uri":"https://oauth2.googleapis.com/token",
"auth_provider_x509_cert_url":"https://www.googleapis.com/oauth2/v1/certs",
"client_secret":"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"
}
}
"""
# Components of the relative path (within the user settings directory) at which
# to store TensorBoard uploader credentials.
TENSORBOARD_CREDENTIALS_FILEPATH_PARTS = [
"tensorboard",
"credentials",
"uploader-creds.json",
]
class CredentialsStore:
"""Private file store for a `google.oauth2.credentials.Credentials`."""
_DEFAULT_CONFIG_DIRECTORY = object() # Sentinel value.
def __init__(self, user_config_directory=_DEFAULT_CONFIG_DIRECTORY):
"""Creates a CredentialsStore.
Args:
user_config_directory: Optional absolute path to the root directory for
storing user configs, under which to store the credentials file. If not
set, defaults to a platform-specific location. If set to None, the
store is disabled (reads return None; write and clear are no-ops).
"""
if user_config_directory is CredentialsStore._DEFAULT_CONFIG_DIRECTORY:
user_config_directory = util.get_user_config_directory()
if user_config_directory is None:
logger.warning(
"Credentials caching disabled - no private config directory found"
)
if user_config_directory is None:
self._credentials_filepath = None
else:
self._credentials_filepath = os.path.join(
user_config_directory, *TENSORBOARD_CREDENTIALS_FILEPATH_PARTS
)
def read_credentials(self):
"""Returns the current `google.oauth2.credentials.Credentials`, or
None."""
if self._credentials_filepath is None:
return None
if os.path.exists(self._credentials_filepath):
return (
google.oauth2.credentials.Credentials.from_authorized_user_file(
self._credentials_filepath
)
)
return None
def write_credentials(self, credentials):
"""Writes a `google.oauth2.credentials.Credentials` to the store."""
if not isinstance(credentials, google.oauth2.credentials.Credentials):
raise TypeError(
"Cannot write credentials of type %s" % type(credentials)
)
if self._credentials_filepath is None:
return
# Make the credential file private if not on Windows; on Windows we rely on
# the default user config settings directory being private since we don't
# have a straightforward way to make an individual file private.
private = os.name != "nt"
util.make_file_with_directories(
self._credentials_filepath, private=private
)
data = {
"refresh_token": credentials.refresh_token,
"token_uri": credentials.token_uri,
"client_id": credentials.client_id,
"client_secret": credentials.client_secret,
"scopes": credentials.scopes,
"type": "authorized_user",
}
with open(self._credentials_filepath, "w") as f:
json.dump(data, f)
def clear(self):
"""Clears the store of any persisted credentials information."""
if self._credentials_filepath is None:
return
try:
os.remove(self._credentials_filepath)
except OSError as e:
if e.errno != errno.ENOENT:
raise
def authenticate_user(
force_console=False,
) -> google.oauth2.credentials.Credentials:
"""Makes the user authenticate to retrieve auth credentials.
The default behavior is to use the [installed app flow](
http://developers.google.com/identity/protocols/oauth2/native-app), in which
a browser is started for the user to authenticate, along with a local web
server. The authentication in the browser would produce a redirect response
to `localhost` with an authorization code that would then be received by the
local web server started here.
The two most notable cases where the default flow is not well supported are:
- When the uploader is run from a colab notebook.
- Then the uploader is run via a remote terminal (SSH).
If any of the following is true, a different auth flow will be used:
- the flag `--auth_force_console` is set to true, or
- a browser is not available, or
- a local web server cannot be started
In this case, a [limited-input device flow](
http://developers.google.com/identity/protocols/oauth2/limited-input-device)
will be used, in which the user is presented with a URL and a short code
that they'd need to use to authenticate and authorize access in a separate
browser or device. The uploader will poll for access until the access is
granted or rejected, or the initiated authorization request expires.
"""
scopes = OPENID_CONNECT_SCOPES
# TODO(b/141721828): make auto-detection smarter, especially for macOS.
if not force_console and os.getenv("DISPLAY"):
try:
client_config = json.loads(_INSTALLED_APP_OAUTH_CLIENT_CONFIG)
flow = auth_flows.InstalledAppFlow.from_client_config(
client_config, scopes=scopes
)
return flow.run_local_server(port=0)
except webbrowser.Error:
sys.stderr.write("Falling back to remote authentication flow...\n")
client_config = json.loads(_LIMITED_INPUT_DEVICE_OAUTH_CLIENT_CONFIG)
flow = _LimitedInputDeviceAuthFlow(client_config, scopes=scopes)
return flow.run()
class _LimitedInputDeviceAuthFlow:
"""OAuth flow to authenticate using the limited-input device flow.
See:
http://developers.google.com/identity/protocols/oauth2/limited-input-device
"""
def __init__(self, client_config, scopes):
# The config is loaded from a json string from the GCP project, which
# comes with an "installed" wrapper layer on the values we need.
self._client_config = client_config["installed"]
self._scopes = scopes
def run(self) -> google.oauth2.credentials.Credentials:
device_response = self._send_device_auth_request()
prompt_message = (
"To sign in with the TensorBoard uploader:\n"
"\n"
"1. On your computer or phone, visit:\n"
"\n"
" {url}\n"
"\n"
"2. Sign in with your Google account, then enter:\n"
"\n"
" {code}\n".format(
url=device_response["verification_url"],
code=device_response["user_code"],
)
)
print(prompt_message)
auth_response = self._poll_for_auth_token(
device_code=device_response["device_code"],
polling_interval=device_response["interval"],
expiration_seconds=device_response["expires_in"],
)
return self._build_credentials(auth_response)
def _send_device_auth_request(self):
params = {
"client_id": self._client_config["client_id"],
"scope": " ".join(self._scopes),
}
r = requests.post(_DEVICE_AUTH_CODE_URI, data=params).json()
if "device_code" not in r:
raise RuntimeError(
"There was an error while contacting Google's authorization "
"server. Please try again later."
)
return r
def _poll_for_auth_token(
self, device_code: str, polling_interval: int, expiration_seconds: int
):
token_uri = self._client_config["token_uri"]
params = {
"client_id": self._client_config["client_id"],
"client_secret": self._client_config["client_secret"],
"device_code": device_code,
"grant_type": _LIMITED_INPUT_DEVICE_AUTH_GRANT_TYPE,
}
expiration_time = time.time() + expiration_seconds
# Error cases documented in
# https://developers.google.com/identity/protocols/oauth2/limited-input-device#step-6:-handle-responses-to-polling-requests
while time.time() < expiration_time:
resp = requests.post(token_uri, data=params)
r = resp.json()
if "access_token" in r:
return r
elif "error" in r and r["error"] == "authorization_pending":
# Not really an error. This is the expected response when the
# user has not yet granted access to this app.
time.sleep(polling_interval)
elif "error" in r and r["error"] == "slow_down":
# We should be polling at the specified interval from the
# previous response, so this error would be unexpected.
# However, it is just a temporary/retryable error, so we can
# poll a bit more slowly.
polling_interval = int(polling_interval * 1.5)
time.sleep(polling_interval)
elif "error" in r and r["error"] == "access_denied":
raise PermissionError("Access was denied by user.")
elif resp.status_code in {400, 401}:
raise ValueError("There must be an error in the request.")
else:
raise RuntimeError(
"An unexpected error occurred while waiting for "
"authorization."
)
raise TimeoutError("Timed out waiting for authorization.")
def _build_credentials(
self, auth_response
) -> google.oauth2.credentials.Credentials:
expiration_datetime = datetime.datetime.utcfromtimestamp(
int(time.time()) + auth_response["expires_in"]
)
return google.oauth2.credentials.Credentials(
auth_response["access_token"],
refresh_token=auth_response["refresh_token"],
id_token=auth_response["id_token"],
token_uri=self._client_config["token_uri"],
client_id=self._client_config["client_id"],
client_secret=self._client_config["client_secret"],
scopes=self._scopes,
expiry=expiration_datetime,
)
class IdTokenAuthMetadataPlugin(grpc.AuthMetadataPlugin):
"""A `gRPC AuthMetadataPlugin` that uses ID tokens.
This works like the existing `google.auth.transport.grpc.AuthMetadataPlugin`
except that instead of always using access tokens, it preferentially uses the
`Credentials.id_token` property if available (and logs an error otherwise).
See http://www.grpc.io/grpc/python/grpc.html#grpc.AuthMetadataPlugin
"""
def __init__(self, credentials, request):
"""Constructs an IdTokenAuthMetadataPlugin.
Args:
credentials (google.auth.credentials.Credentials): The credentials to
add to requests.
request (google.auth.transport.Request): A HTTP transport request object
used to refresh credentials as needed.
"""
super().__init__()
if not isinstance(credentials, google.oauth2.credentials.Credentials):
raise TypeError(
"Cannot get ID tokens from credentials type %s"
% type(credentials)
)
self._credentials = credentials
self._request = request
def __call__(self, context, callback):
"""Passes authorization metadata into the given callback.
Args:
context (grpc.AuthMetadataContext): The RPC context.
callback (grpc.AuthMetadataPluginCallback): The callback that will
be invoked to pass in the authorization metadata.
"""
headers = {}
self._credentials.before_request(
self._request, context.method_name, context.service_url, headers
)
id_token = getattr(self._credentials, "id_token", None)
if id_token:
self._credentials.apply(headers, token=id_token)
else:
logger.error("Failed to find ID token credentials")
# Pass headers as key-value pairs to match CallCredentials metadata.
callback(list(headers.items()), None)
def id_token_call_credentials(credentials):
"""Constructs `grpc.CallCredentials` using
`google.auth.Credentials.id_token`.
Args:
credentials (google.auth.credentials.Credentials): The credentials to use.
Returns:
grpc.CallCredentials: The call credentials.
"""
request = google.auth.transport.requests.Request()
return grpc.metadata_call_credentials(
IdTokenAuthMetadataPlugin(credentials, request)
)