def _wait_hostname_resolution():
"""Wait for the hostname resolution of the container. This is known behavior as the cluster
boots up and has been documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-running-container.html#your-algorithms-training-algo-running-container-dist-training
"""
for host in _env.TrainingEnv().hosts:
_dns_lookup(host)
def training_env(resource_config=None,
input_data_config=None,
hyperparameters=None):
resource_config = resource_config or env.read_resource_config()
input_data_config = input_data_config or env.read_input_data_config()
hyperparameters = hyperparameters or env.read_hyperparameters()
return env.TrainingEnv(resource_config=resource_config,
input_data_config=input_data_config,
hyperparameters=hyperparameters)
def training_env():
"""Create a TrainingEnv.
Returns:
TrainingEnv: an instance of TrainingEnv
"""
from sagemaker_containers import _env
return _env.TrainingEnv(resource_config=_env.read_resource_config(),
input_data_config=_env.read_input_data_config(),
hyperparameters=_env.read_hyperparameters())
def training_env(resource_config=None, input_data_config=None, hyperparameters=None):
"""Placeholder docstring"""
resource_config = resource_config or env.read_resource_config()
input_data_config = input_data_config or env.read_input_data_config()
hyperparameters = hyperparameters or env.read_hyperparameters()
return env.TrainingEnv(
resource_config=resource_config,
input_data_config=input_data_config,
hyperparameters=hyperparameters,
)