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fix(train): omit input_data_config when no input channels are provided - #6399
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When a ModelTrainer has no input channels specified, _create_training_job_args
serialized an empty list ('input_data_config: []'). Downstream CreatePipeline
rejects an empty InputDataConfig array with ValidationException because the
botocore service model enforces min=1 on InputDataConfig when present.
Omit input_data_config from training_request when final_input_data_config is
empty, allowing the SageMaker API and CreatePipeline to succeed as in v2.
Fixes aws#6156
Signed-off-by: reginaldalfret <reginaldalfret@gmail.com>
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Description
When a
ModelTraineris configured without input channels (such as fine-tuning jobs where data is fetched directly inside the container from Hugging Face Hub or other sources),_create_training_job_argspreviously emitted"input_data_config": [].SageMaker's
CreatePipelinerejects an empty array with:While SageMaker's API accepts an omitted
InputDataConfig, it rejects an empty list due to themin=1constraint in the service model. Under PySDK v2, the key was omitted when no channels were provided.Solution
input_data_configfrom the generated training request dictionary whenfinal_input_data_configis empty.training_request.get("input_data_config")safely in_LocalContainerinstantiation.input_data_configis omitted when empty and included when channels are provided.Fixes #6156