src/sagemaker_training/params.py

# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
#     http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""This module contains string constants representing environment variables
and related parameters.
"""
from __future__ import absolute_import

SAGEMAKER_PREFIX = "sagemaker_"  # type: str
CURRENT_HOST_ENV = "CURRENT_HOST"  # type: str
USER_PROGRAM_PARAM = "sagemaker_program"  # type: str
USER_PROGRAM_ENV = USER_PROGRAM_PARAM.upper()  # type: str
S3_OUTPUT_LOCATION_PARAM = "sagemaker_s3_output"  # type: str
S3_OUTPUT_LOCATION_ENV = S3_OUTPUT_LOCATION_PARAM.upper()  # type: str
S3_ENDPOINT_URL = "S3_ENDPOINT_URL"  # type: str
TRAINING_JOB_ENV = "TRAINING_JOB_NAME"  # type: str
SUBMIT_DIR_PARAM = "sagemaker_submit_directory"  # type: str
SUBMIT_DIR_ENV = SUBMIT_DIR_PARAM.upper()  # type: str
ENABLE_METRICS_PARAM = "sagemaker_enable_cloudwatch_metrics"  # type: str
ENABLE_METRICS_ENV = ENABLE_METRICS_PARAM.upper()  # type: str
LOG_LEVEL_PARAM = "sagemaker_container_log_level"  # type: str
LOG_LEVEL_ENV = LOG_LEVEL_PARAM.upper()  # type: str
JOB_NAME_PARAM = "sagemaker_job_name"  # type: str
JOB_NAME_ENV = JOB_NAME_PARAM.upper()  # type: str
TUNING_METRIC_PARAM = "_tuning_objective_metric"  # type: str
DEFAULT_MODULE_NAME_PARAM = "default_user_module_name"  # type: str
MPI_ENABLED = "sagemaker_mpi_enabled"  # type: str
PARAMETER_SERVER_ENABLED = "sagemaker_parameter_server_enabled"  # type: str
MULTI_WORKER_MIRRORED_STRATEGY_ENABLED = (
    "sagemaker_multi_worker_mirrored_strategy_enabled"
)  # type: str
PYTORCH_XLA_MULTI_WORKER_ENABLED = "sagemaker_pytorch_xla_multi_worker_enabled"  # type: str
REGION_NAME_PARAM = "sagemaker_region"  # type: str
REGION_NAME_ENV = REGION_NAME_PARAM.upper()  # type: str
DEFAULT_INVOCATIONS_ACCEPT_ENV = "SAGEMAKER_DEFAULT_INVOCATIONS_ACCEPT"  # type: str
SAGEMAKER_BIND_TO_PORT_ENV = "SAGEMAKER_BIND_TO_PORT"  # type: str
SAGEMAKER_SAFE_PORT_RANGE_ENV = "SAGEMAKER_SAFE_PORT_RANGE"  # type: str
FRAMEWORK_TRAINING_MODULE_ENV = "SAGEMAKER_TRAINING_MODULE"  # type: str
SAGEMAKER_HYPERPARAMETERS = (
    USER_PROGRAM_PARAM,
    SUBMIT_DIR_PARAM,
    ENABLE_METRICS_PARAM,
    REGION_NAME_PARAM,
    LOG_LEVEL_PARAM,
    JOB_NAME_PARAM,
    DEFAULT_MODULE_NAME_PARAM,
    TUNING_METRIC_PARAM,
    S3_OUTPUT_LOCATION_PARAM,
)  # type: tuple
MPI_PROCESSES_PER_HOST = "sagemaker_mpi_num_of_processes_per_host"  # type: int
MPI_NUM_PROCESSES = "sagemaker_mpi_num_processes"  # type: int
MPI_CUSTOM_OPTIONS = "sagemaker_mpi_custom_mpi_options"  # type: str
SAGEMAKER_NETWORK_INTERFACE_NAME = "sagemaker_network_interface_name"  # type: str
SMDATAPARALLEL_CUSTOM_MPI_OPTIONS = (
    "sagemaker_distributed_dataparallel_custom_mpi_options"
)  # type: str
SM_HP_MP_PARAMETERS = "SM_HP_MP_PARAMETERS"
DISTRIBUTION_INSTANCE_GROUPS = "sagemaker_distribution_instance_groups"  # type: list