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