def run_submission_with_high_level_api(backend, entry_point, capsys,
expected_result):
py_version = ".".join([str(x) for x in sys.version_info[0:3]])
base_image = 'python:{}'.format(py_version)
train_job = TrainJob(entry_point=entry_point,
base_docker_image=base_image,
docker_registry=DOCKER_REGISTRY,
backend=backend,
input_files=["requirements.txt"])
train_job.submit()
captured = capsys.readouterr()
assert expected_result in captured.out
local_data_dir="~/tensorflow_datasets")
model.train()
else:
#using Fairing
GCP_PROJECT = fairing.cloud.gcp.guess_project_name()
DOCKER_REGISTRY = 'gcr.io/{}/fairing-job'.format(GCP_PROJECT)
BuildContext = None
FAIRING_BACKEND = 'KubeflowGKEBackend'
BackendClass = getattr(
importlib.import_module('kubeflow.fairing.backends'),
FAIRING_BACKEND)
data_files = [
'tensorflow_datasets/downloads/ai.stanfor.edu_amaas_sentime_aclImdb_v1xA90oY07YfkP66HhdzDg046Ll8Bf3nAIlC6Rkj0WWP4.tar.gz',
'tensorflow_datasets/downloads/ai.stanfor.edu_amaas_sentime_aclImdb_v1xA90oY07YfkP66HhdzDg046Ll8Bf3nAIlC6Rkj0WWP4.tar.gz.INFO',
'tensorflow_datasets/imdb_reviews/subwords8k/1.0.0/dataset_info.json',
'tensorflow_datasets/imdb_reviews/subwords8k/1.0.0/imdb_reviews-test.tfrecord-00000-of-00001',
'tensorflow_datasets/imdb_reviews/subwords8k/1.0.0/imdb_reviews-train.tfrecord-00000-of-00001',
'tensorflow_datasets/imdb_reviews/subwords8k/1.0.0/imdb_reviews-unsupervised.tfrecord-00000-of-00001',
'tensorflow_datasets/imdb_reviews/subwords8k/1.0.0/label.labels.txt',
'tensorflow_datasets/imdb_reviews/subwords8k/1.0.0/text.text.subwords',
'requirements.txt'
]
train_job = TrainJob(
MovieReviewClassification,
input_files=data_files,
docker_registry=DOCKER_REGISTRY,
backend=BackendClass(build_context_source=BuildContext))
train_job.submit()