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[AIRFLOW-1273]AIRFLOW-1273] Add Google Cloud ML version and model ope…
…rators Includes Google Cloud ML hooks for version and model operations, and their unit tests. https://issues.apache.org/jira/browse/AIRFLOW-1273 Closes apache#2379 from N3da/master
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# | ||
# Licensed to the Apache Software Foundation (ASF) under one or more | ||
# contributor license agreements. See the NOTICE file distributed with | ||
# this work for additional information regarding copyright ownership. | ||
# The ASF licenses this file to You 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. | ||
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import logging | ||
import random | ||
import time | ||
from airflow import settings | ||
from airflow.contrib.hooks.gcp_api_base_hook import GoogleCloudBaseHook | ||
from apiclient.discovery import build | ||
from apiclient import errors | ||
from oauth2client.client import GoogleCredentials | ||
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logging.getLogger('GoogleCloudML').setLevel(settings.LOGGING_LEVEL) | ||
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def _poll_with_exponential_delay(request, max_n, is_done_func, is_error_func): | ||
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for i in range(0, max_n): | ||
try: | ||
response = request.execute() | ||
if is_error_func(response): | ||
raise ValueError('The response contained an error: {}'.format(response)) | ||
elif is_done_func(response): | ||
logging.info('Operation is done: {}'.format(response)) | ||
return response | ||
else: | ||
time.sleep((2**i) + (random.randint(0, 1000) / 1000)) | ||
except errors.HttpError as e: | ||
if e.resp.status != 429: | ||
logging.info('Something went wrong. Not retrying: {}'.format(e)) | ||
raise e | ||
else: | ||
time.sleep((2**i) + (random.randint(0, 1000) / 1000)) | ||
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class CloudMLHook(GoogleCloudBaseHook): | ||
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def __init__(self, gcp_conn_id='google_cloud_default', delegate_to=None): | ||
super(CloudMLHook, self).__init__(gcp_conn_id, delegate_to) | ||
self._cloudml = self.get_conn() | ||
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def get_conn(self): | ||
""" | ||
Returns a Google CloudML service object. | ||
""" | ||
credentials = GoogleCredentials.get_application_default() | ||
return build('ml', 'v1', credentials=credentials) | ||
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def create_version(self, project_name, model_name, version_spec): | ||
""" | ||
Creates the Version on Cloud ML. | ||
Returns the operation if the version was created successfully and raises | ||
an error otherwise. | ||
""" | ||
parent_name = 'projects/{}/models/{}'.format(project_name, model_name) | ||
create_request = self._cloudml.projects().models().versions().create( | ||
parent=parent_name, body=version_spec) | ||
response = create_request.execute() | ||
get_request = self._cloudml.projects().operations().get( | ||
name=response['name']) | ||
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return _poll_with_exponential_delay( | ||
request=get_request, | ||
max_n=9, | ||
is_done_func=lambda resp: resp.get('done', False), | ||
is_error_func=lambda resp: resp.get('error', None) is not None) | ||
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def set_default_version(self, project_name, model_name, version_name): | ||
""" | ||
Sets a version to be the default. Blocks until finished. | ||
""" | ||
full_version_name = 'projects/{}/models/{}/versions/{}'.format( | ||
project_name, model_name, version_name) | ||
request = self._cloudml.projects().models().versions().setDefault( | ||
name=full_version_name, body={}) | ||
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try: | ||
response = request.execute() | ||
logging.info('Successfully set version: {} to default'.format(response)) | ||
return response | ||
except errors.HttpError as e: | ||
logging.error('Something went wrong: {}'.format(e)) | ||
raise e | ||
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def list_versions(self, project_name, model_name): | ||
""" | ||
Lists all available versions of a model. Blocks until finished. | ||
""" | ||
result = [] | ||
full_parent_name = 'projects/{}/models/{}'.format( | ||
project_name, model_name) | ||
request = self._cloudml.projects().models().versions().list( | ||
parent=full_parent_name, pageSize=100) | ||
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response = request.execute() | ||
next_page_token = response.get('nextPageToken', None) | ||
result.extend(response.get('versions', [])) | ||
while next_page_token is not None: | ||
next_request = self._cloudml.projects().models().versions().list( | ||
parent=full_parent_name, | ||
pageToken=next_page_token, | ||
pageSize=100) | ||
response = next_request.execute() | ||
next_page_token = response.get('nextPageToken', None) | ||
result.extend(response.get('versions', [])) | ||
time.sleep(5) | ||
return result | ||
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def delete_version(self, project_name, model_name, version_name): | ||
""" | ||
Deletes the given version of a model. Blocks until finished. | ||
""" | ||
full_name = 'projects/{}/models/{}/versions/{}'.format( | ||
project_name, model_name, version_name) | ||
delete_request = self._cloudml.projects().models().versions().delete( | ||
name=full_name) | ||
response = delete_request.execute() | ||
get_request = self._cloudml.projects().operations().get( | ||
name=response['name']) | ||
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return _poll_with_exponential_delay( | ||
request=get_request, | ||
max_n=9, | ||
is_done_func=lambda resp: resp.get('done', False), | ||
is_error_func=lambda resp: resp.get('error', None) is not None) | ||
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def create_model(self, project_name, model): | ||
""" | ||
Create a Model. Blocks until finished. | ||
""" | ||
assert model['name'] is not None and model['name'] is not '' | ||
project = 'projects/{}'.format(project_name) | ||
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request = self._cloudml.projects().models().create( | ||
parent=project, body=model) | ||
return request.execute() | ||
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def get_model(self, project_name, model_name): | ||
""" | ||
Gets a Model. Blocks until finished. | ||
""" | ||
assert model_name is not None and model_name is not '' | ||
full_model_name = 'projects/{}/models/{}'.format( | ||
project_name, model_name) | ||
request = self._cloudml.projects().models().get(name=full_model_name) | ||
try: | ||
return request.execute() | ||
except errors.HttpError as e: | ||
if e.resp.status == 404: | ||
logging.error('Model was not found: {}'.format(e)) | ||
return None | ||
raise e |
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# | ||
# Licensed to the Apache Software Foundation (ASF) under one or more | ||
# contributor license agreements. See the NOTICE file distributed with | ||
# this work for additional information regarding copyright ownership. | ||
# The ASF licenses this file to You 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. | ||
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import logging | ||
from airflow import settings | ||
from airflow.contrib.hooks.gcp_cloudml_hook import CloudMLHook | ||
from airflow.operators import BaseOperator | ||
from airflow.utils.decorators import apply_defaults | ||
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logging.getLogger('GoogleCloudML').setLevel(settings.LOGGING_LEVEL) | ||
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class CloudMLVersionOperator(BaseOperator): | ||
""" | ||
Operator for managing a Google Cloud ML version. | ||
:param model_name: The name of the Google Cloud ML model that the version | ||
belongs to. | ||
:type model_name: string | ||
:param project_name: The Google Cloud project name to which CloudML | ||
model belongs. | ||
:type project_name: string | ||
:param version: A dictionary containing the information about the version. | ||
If the `operation` is `create`, `version` should contain all the | ||
information about this version such as name, and deploymentUrl. | ||
If the `operation` is `get` or `delete`, the `version` parameter | ||
should contain the `name` of the version. | ||
If it is None, the only `operation` possible would be `list`. | ||
:type version: dict | ||
:param gcp_conn_id: The connection ID to use when fetching connection info. | ||
:type gcp_conn_id: string | ||
:param operation: The operation to perform. Available operations are: | ||
'create': Creates a new version in the model specified by `model_name`, | ||
in which case the `version` parameter should contain all the | ||
information to create that version | ||
(e.g. `name`, `deploymentUrl`). | ||
'get': Gets full information of a particular version in the model | ||
specified by `model_name`. | ||
The name of the version should be specified in the `version` | ||
parameter. | ||
'list': Lists all available versions of the model specified | ||
by `model_name`. | ||
'delete': Deletes the version specified in `version` parameter from the | ||
model specified by `model_name`). | ||
The name of the version should be specified in the `version` | ||
parameter. | ||
:type operation: string | ||
:param delegate_to: The account to impersonate, if any. | ||
For this to work, the service account making the request must have | ||
domain-wide delegation enabled. | ||
:type delegate_to: string | ||
""" | ||
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template_fields = [ | ||
'_model_name', | ||
'_version', | ||
] | ||
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@apply_defaults | ||
def __init__(self, | ||
model_name, | ||
project_name, | ||
version=None, | ||
gcp_conn_id='google_cloud_default', | ||
operation='create', | ||
delegate_to=None, | ||
*args, | ||
**kwargs): | ||
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super(CloudMLVersionOperator, self).__init__(*args, **kwargs) | ||
self._model_name = model_name | ||
self._version = version | ||
self._gcp_conn_id = gcp_conn_id | ||
self._delegate_to = delegate_to | ||
self._project_name = project_name | ||
self._operation = operation | ||
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def execute(self, context): | ||
hook = CloudMLHook( | ||
gcp_conn_id=self._gcp_conn_id, delegate_to=self._delegate_to) | ||
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if self._operation == 'create': | ||
assert self._version is not None | ||
return hook.create_version(self._project_name, self._model_name, | ||
self._version) | ||
elif self._operation == 'set_default': | ||
return hook.set_default_version( | ||
self._project_name, self._model_name, | ||
self._version['name']) | ||
elif self._operation == 'list': | ||
return hook.list_versions(self._project_name, self._model_name) | ||
elif self._operation == 'delete': | ||
return hook.delete_version(self._project_name, self._model_name, | ||
self._version['name']) | ||
else: | ||
raise ValueError('Unknown operation: {}'.format(self._operation)) | ||
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class CloudMLModelOperator(BaseOperator): | ||
""" | ||
Operator for managing a Google Cloud ML model. | ||
:param model: A dictionary containing the information about the model. | ||
If the `operation` is `create`, then the `model` parameter should | ||
contain all the information about this model such as `name`. | ||
If the `operation` is `get`, the `model` parameter | ||
should contain the `name` of the model. | ||
:type model: dict | ||
:param project_name: The Google Cloud project name to which CloudML | ||
model belongs. | ||
:type project_name: string | ||
:param gcp_conn_id: The connection ID to use when fetching connection info. | ||
:type gcp_conn_id: string | ||
:param operation: The operation to perform. Available operations are: | ||
'create': Creates a new model as provided by the `model` parameter. | ||
'get': Gets a particular model where the name is specified in `model`. | ||
:param delegate_to: The account to impersonate, if any. | ||
For this to work, the service account making the request must have | ||
domain-wide delegation enabled. | ||
:type delegate_to: string | ||
""" | ||
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template_fields = [ | ||
'_model', | ||
] | ||
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@apply_defaults | ||
def __init__(self, | ||
model, | ||
project_name, | ||
gcp_conn_id='google_cloud_default', | ||
operation='create', | ||
delegate_to=None, | ||
*args, | ||
**kwargs): | ||
super(CloudMLModelOperator, self).__init__(*args, **kwargs) | ||
self._model = model | ||
self._operation = operation | ||
self._gcp_conn_id = gcp_conn_id | ||
self._delegate_to = delegate_to | ||
self._project_name = project_name | ||
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def execute(self, context): | ||
hook = CloudMLHook( | ||
gcp_conn_id=self._gcp_conn_id, delegate_to=self._delegate_to) | ||
if self._operation == 'create': | ||
hook.create_model(self._project_name, self._model) | ||
elif self._operation == 'get': | ||
hook.get_model(self._project_name, self._model['name']) | ||
else: | ||
raise ValueError('Unknown operation: {}'.format(self._operation)) |
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