[COMMON]
base_job_prefix = SM-NeMo-ASR-PIPELINE-

[INPUT]
input_data_s3_uri = s3://sm-nemo-bucket/data

[PIPELINE]
name = NeMoASRPipeline-Example
enable_caching = False
expire_after = T48H

[PREPROCESSING]
instance_type = ml.g4dn.xlarge
instance_count = 1

[TRAINING]
framework_version = None
py_version = None
instance_type = ml.p3.2xlarge
instance_count = 1
experiment_name = train-exp

[EVALUATION]
instance_type = ml.g4dn.xlarge
instance_count = 1
experiment_name = eval-exp

[MODEL_REGISTER]
model_package_group_name = NeMoASRModelPackageGroup-Example
model_approval_status_default = PendingManualApproval
inference_instances = ["ml.p3.2xlarge"]
transform_instances = ["ml.p3.2xlarge"]

[DEPLOY]
processing_instance_type = ml.m5.xlarge
processing_instance_count = 1
processing_framework_version = 1.0-1
instance_type = ml.g4dn.xlarge
initial_instance_count = 1
model_server_workers = 1
framework_version = 1.12.1
py_version = py38