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Local mode pass training env var #411

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Merged
merged 4 commits into from
Sep 28, 2018
Merged

Local mode pass training env var #411

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34d12ed
Pass some SageMaker Training environment variables in Local Mode
laurenyu Sep 27, 2018
e5ace75
Merge branch 'master' into local-mode-pass-training-env-var
laurenyu Sep 27, 2018
bf9f56b
update changelog
laurenyu Sep 27, 2018
d96b960
Use boto_region_name instead of boto_session.region_name
laurenyu Sep 27, 2018
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5 changes: 5 additions & 0 deletions CHANGELOG.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,11 @@
CHANGELOG
=========

1.11.1dev
=========

* enhancement: Local Mode: add training environment variables for AWS region and job name

1.11.0
======

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19 changes: 14 additions & 5 deletions src/sagemaker/local/image.py
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Expand Up @@ -34,9 +34,13 @@
import sagemaker
from sagemaker.utils import get_config_value

CONTAINER_PREFIX = "algo"
CONTAINER_PREFIX = 'algo'
DOCKER_COMPOSE_FILENAME = 'docker-compose.yaml'

# Environment variables to be set during training
REGION_ENV_NAME = 'AWS_REGION'
TRAINING_JOB_NAME_ENV_NAME = 'TRAINING_JOB_NAME'

logger = logging.getLogger(__name__)
logger.setLevel(logging.WARNING)

Expand Down Expand Up @@ -102,7 +106,12 @@ def train(self, input_data_config, hyperparameters):
self.write_config_files(host, hyperparameters, input_data_config)
shutil.copytree(data_dir, os.path.join(self.container_root, host, 'input', 'data'))

compose_data = self._generate_compose_file('train', additional_volumes=volumes)
training_env_vars = {
REGION_ENV_NAME: self.sagemaker_session.boto_session.region_name,
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there are cases in which boto_session can be None. I would add an if guard here.

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talked offline - changed to use sagemaker_session.boto_region_name

TRAINING_JOB_NAME_ENV_NAME: json.loads(hyperparameters.get(sagemaker.model.JOB_NAME_PARAM_NAME)),
}
compose_data = self._generate_compose_file('train', additional_volumes=volumes,
additional_env_vars=training_env_vars)
compose_command = self._compose()

_ecr_login_if_needed(self.sagemaker_session.boto_session, self.image)
Expand Down Expand Up @@ -149,7 +158,6 @@ def serve(self, model_dir, environment):
logger.info('creating hosting dir in {}'.format(self.container_root))

volumes = self._prepare_serving_volumes(model_dir)
env_vars = ['{}={}'.format(k, v) for k, v in environment.items()]

# If the user script was passed as a file:// mount it to the container.
if sagemaker.estimator.DIR_PARAM_NAME.upper() in environment:
Expand All @@ -161,7 +169,7 @@ def serve(self, model_dir, environment):
_ecr_login_if_needed(self.sagemaker_session.boto_session, self.image)

self._generate_compose_file('serve',
additional_env_vars=env_vars,
additional_env_vars=environment,
additional_volumes=volumes)
compose_command = self._compose()
self.container = _HostingContainer(compose_command)
Expand Down Expand Up @@ -384,7 +392,8 @@ def _generate_compose_file(self, command, additional_volumes=None, additional_en
if aws_creds is not None:
environment.extend(aws_creds)

environment.extend(additional_env_vars)
additional_env_var_list = ['{}={}'.format(k, v) for k, v in additional_env_vars.items()]
environment.extend(additional_env_var_list)

if command == 'train':
optml_dirs = {'output', 'output/data', 'input'}
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10 changes: 7 additions & 3 deletions tests/unit/test_image.py
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Expand Up @@ -49,12 +49,14 @@
}
]
HYPERPARAMETERS = {'a': 1,
'b': 'bee',
'sagemaker_submit_directory': json.dumps('s3://my_bucket/code')}
'b': json.dumps('bee'),
'sagemaker_submit_directory': json.dumps('s3://my_bucket/code'),
'sagemaker_job_name': json.dumps('my-job')}

LOCAL_CODE_HYPERPARAMETERS = {'a': 1,
'b': 2,
'sagemaker_submit_directory': json.dumps('file:///tmp/code')}
'sagemaker_submit_directory': json.dumps('file:///tmp/code'),
'sagemaker_job_name': json.dumps('my-job')}


@pytest.fixture()
Expand Down Expand Up @@ -244,6 +246,8 @@ def test_train(_download_folder, _cleanup, popen, _stream_output, LocalSession,
for h in sagemaker_container.hosts:
assert config['services'][h]['image'] == image
assert config['services'][h]['command'] == 'train'
assert 'AWS_REGION={}'.format(REGION) in config['services'][h]['environment']
assert 'TRAINING_JOB_NAME=my-job' in config['services'][h]['environment']

# assert that expected by sagemaker container output directories exist
assert os.path.exists(os.path.join(sagemaker_container.container_root, 'output'))
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