def __init__(self,
project_id=None,
region=None,
training_scale_tier=None,
job_config=None,
use_stream_logs=False):
"""Creates an instance of GCPManagedBackend
:param project_id: Google Cloud project ID to use.
:param region: region in which the job has to be deployed.
Ref: https://cloud.google.com/compute/docs/regions-zones/
:param training_scale_tier: machine type to use for the job.
Ref: https://cloud.google.com/ml-engine/docs/tensorflow/machine-types
:param job_config: Custom job configuration options. If an option is specified
in the job_config and as a top-level parameter, the parameter overrides
the value in the job_config.
Ref: https://cloud.google.com/ml-engine/reference/rest/v1/projects.jobs
:param use_stream_logs: If true, when deploying a job, output the job stream
log until the job ends.
"""
super(GCPManagedBackend, self).__init__()
self._project_id = project_id or gcp.guess_project_name()
self._region = region or 'us-central1'
self._training_scale_tier = training_scale_tier or 'BASIC'
self._job_config = job_config
self._use_stream_logs = use_stream_logs
def __init__(self,
registry=None,
image_name=None,
base_image=constants.DEFAULT_BASE_IMAGE,
push=True,
preprocessor=None,
dockerfile_path=None):
self.registry = registry
self.image_name = image_name
self.push = push
if self.registry is None:
# TODO(r2d4): Add more heuristics here...
# If no push and no registry provided, use any registry name
if not self.push:
self.registry = 'local/fairing-image'
else:
self.registry = 'gcr.io/{}'.format(gcp.guess_project_name())
self.base_image = base_image
self.dockerfile_path = dockerfile_path
self.preprocessor = preprocessor
self.image_tag = None
self.docker_client = None
def test_guess_project_name_application_default_file(tmp_path):
creds_file = tmp_path / 'credentials'
project_id = 'test_project'
with creds_file.open('w') as f:
json.dump({'project_id': project_id}, f)
assert guess_project_name(str(creds_file)) == project_id
def __init__(self, model_dir, model_name, version_name, project_id=None,
**deploy_kwargs):
self._project_id = project_id or guess_project_name()
self._model_dir = model_dir
self._model_name = model_name
self._version_name = version_name
self._deploy_kwargs = deploy_kwargs
self._ml = discovery.build('ml', 'v1')
self._ml._http = http_utils.configure_http_instance(self._ml._http) #pylint:disable=protected-access
# Set default deploy kwargs
if 'runtime_version' not in self._deploy_kwargs:
self._deploy_kwargs['runtime_version'] = '1.13'
if 'python_version' not in self._deploy_kwargs:
self._deploy_kwargs['python_version'] = '3.5'
def __init__(self, project_id=None, region=None, scale_tier=None,
job_config=None, use_stream_logs=False):
"""
:param project_id: Google Cloud project ID to use.
:param region: region in which the job has to be deployed.
Ref: https://cloud.google.com/compute/docs/regions-zones/
:param scale_tier: machine type to use for the job.
Ref: https://cloud.google.com/ml-engine/docs/tensorflow/machine-types
:param job_config: Custom job configuration options. If an option is specified
in the job_config and as a top-level parameter, the parameter overrides
the value in the job_config.
Ref: https://cloud.google.com/ml-engine/reference/rest/v1/projects.jobs
:param use_stream_logs: If true, when deploying a job, output the job stream
log until the job ends.
"""
self._project_id = project_id or guess_project_name()
self._region = region or 'us-central1'
self._job_config = job_config or {}
self.scale_tier = scale_tier
self._ml = discovery.build('ml', 'v1')
self._ml._http = http_utils.configure_http_instance(self._ml._http) #pylint:disable=protected-access
self._use_stream_logs = use_stream_logs
def __init__(self, project_id=None, region=None, training_scale_tier=None):
super(GCPManagedBackend, self).__init__()
self._project_id = project_id or gcp.guess_project_name()
self._region = region or 'us-central1'
self._training_scale_tier = training_scale_tier or 'BASIC'
def prepare(self, context_filename): # pylint:disable=arguments-differ
if self.gcp_project is None:
self.gcp_project = gcp.guess_project_name()
self.uploaded_context_url = self.upload_context(context_filename)
def test_guess_project_name_google_auth(tmp_path): #pylint:disable=unused-argument
project_id = 'test_project'
with patch('google.auth.default', return_value=(None, project_id)):
assert guess_project_name() == project_id
