def test_top_level_params_override_job_config():
job = GCPJob(region='us-west1',
scale_tier='BASIC',
job_config={
'trainingInput': {
'region': 'europe-west1',
'scaleTier': 'PREMIUM_1'
},
'labels': {
'test-key': 'test-value'
}
})
request = job.create_request_dict(create_test_pod_spec())
desired = {
'jobId': job._job_name, #pylint:disable=protected-access
'trainingInput': {
'masterConfig': {
'imageUri': 'test-image'
},
'region': 'us-west1',
'scaleTier': 'BASIC'
},
'labels': {
'test-key': 'test-value'
}
}
assert request == desired
def test_fairing_user_agent_in_http_requests_gcpjob_deploy_api(
httpmock, capsys):
with patch('httplib2.Http', new=httpmock) as mock_http: # pylint:disable=unused-variable
job = GCPJob()
job.deploy(create_test_pod_spec())
captured = capsys.readouterr()
expected_pattern = r'HTTPMock url:https://ml.googleapis.* user-agent:kubeflow-fairing/{}'\
.format(fairing.__version__)
print(captured.out)
assert len(re.findall(expected_pattern, captured.out)) > 0 # pylint:disable=len-as-condition
def test_default_params():
job = GCPJob()
request = job.create_request_dict(create_test_pod_spec())
desired = {
'jobId': job._job_name, #pylint:disable=protected-access
'trainingInput': {
'masterConfig': {
'imageUri': 'test-image'
},
'region': 'us-central1'
}
}
assert request == desired
def test_top_level_args():
job = GCPJob(region='us-west1', scale_tier='BASIC')
request = job.create_request_dict(create_test_pod_spec())
desired = {
'jobId': job._job_name, #pylint:disable=protected-access
'trainingInput': {
'masterConfig': {
'imageUri': 'test-image'
},
'region': 'us-west1',
'scaleTier': 'BASIC'
}
}
assert request == desired
def get_training_deployer(self, pod_spec_mutators=None):
"""Creates a deployer to be used with a training job for GCP
:param pod_spec_mutators: list of functions that is used to mutate the podsspec.
(Default value = None)
:returns: job for handle all the k8s' template building for a training
"""
return GCPJob(self._project_id, self._region, self._training_scale_tier)
def test_custom_job_config():
job = GCPJob(job_config={
'trainingInput': {
'scaleTier': 'CUSTOM',
'masterType': 'standard'
}
})
request = job.create_request_dict(create_test_pod_spec())
desired = {
'jobId': job._job_name, #pylint:disable=protected-access
'trainingInput': {
'masterConfig': {
'imageUri': 'test-image'
},
'region': 'us-central1',
'scaleTier': 'CUSTOM',
'masterType': 'standard'
}
}
assert request == desired