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feature: Accept user-defined env variables for the entry-point #4175

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merged 1 commit into from
Mar 8, 2024
Merged

feature: Accept user-defined env variables for the entry-point #4175

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8 changes: 4 additions & 4 deletions src/sagemaker/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -766,8 +766,8 @@ def _upload_code(self, key_prefix: str, repack: bool = False) -> None:

def _script_mode_env_vars(self):
"""Returns a mapping of environment variables for script mode execution"""
script_name = None
dir_name = None
script_name = self.env.get(SCRIPT_PARAM_NAME.upper(), "")
dir_name = self.env.get(DIR_PARAM_NAME.upper(), "")
if self.uploaded_code:
script_name = self.uploaded_code.script_name
if self.repacked_model_data or self.enable_network_isolation():
Expand All @@ -783,8 +783,8 @@ def _script_mode_env_vars(self):
else "file://" + self.source_dir
)
return {
SCRIPT_PARAM_NAME.upper(): script_name or str(),
DIR_PARAM_NAME.upper(): dir_name or str(),
SCRIPT_PARAM_NAME.upper(): script_name,
DIR_PARAM_NAME.upper(): dir_name,
CONTAINER_LOG_LEVEL_PARAM_NAME.upper(): to_string(self.container_log_level),
SAGEMAKER_REGION_PARAM_NAME.upper(): self.sagemaker_session.boto_region_name,
}
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29 changes: 29 additions & 0 deletions tests/unit/sagemaker/training_compiler/test_huggingface_pytorch_compiler.py
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Expand Up @@ -718,3 +718,32 @@ def test_register_hf_pytorch_model_auto_infer_framework(
sagemaker_session.create_model_package_from_containers.assert_called_with(
**expected_create_model_package_request
)


def test_accept_user_defined_environment_variables(
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I think we need to update these tests with the another version :
FAILED tests/unit/sagemaker/training_compiler/test_huggingface_pytorch_compiler.py::test_accept_user_defined_environment_variables[4.21.1]
FAILED tests/unit/sagemaker/training_compiler/test_huggingface_pytorch_compiler.py::test_accept_user_defined_environment_variables[4.21]

arg = '4.21.1'
available_options = ['4.6.1', '4.10.2', '4.11.0', '4.12.3', '4.17.0', '4.26.0', ...]
arg_name = 'huggingface version'

    def _validate_arg(arg, available_options, arg_name):
        """Checks if the arg is in the available options, and raises a ``ValueError`` if not."""
        if arg not in available_options:
>           raise ValueError(
                "Unsupported {arg_name}: {arg}. You may need to upgrade your SDK version "
                "(pip install -U sagemaker) for newer {arg_name}s. Supported {arg_name}(s): "
                "{options}.".format(arg_name=arg_name, arg=arg, options=", ".join(available_options))
            )
E           ValueError: Unsupported huggingface version: 4.21.1. You may need to upgrade your SDK version (pip install -U sagemaker) for newer huggingface versions. Supported huggingface version(s): 4.6.1, 4.10.2, 4.11.0, 4.12.3, 4.17.0, 4.26.0, 4.28.1, 4.6, 4.10, 4.11, 4.12, 4.17, 4.26, 4.28.

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I'm not sure I understand. Where is the version picked by the test defined?

I just rebased the pull request.

sagemaker_session,
huggingface_training_compiler_version,
huggingface_training_compiler_pytorch_version,
huggingface_training_compiler_pytorch_py_version,
):
program = "inference.py"
directory = "/opt/ml/model/code"

hf_model = HuggingFaceModel(
model_data="s3://some/data.tar.gz",
role=ROLE,
transformers_version=huggingface_training_compiler_version,
pytorch_version=huggingface_training_compiler_pytorch_version,
py_version=huggingface_training_compiler_pytorch_py_version,
sagemaker_session=sagemaker_session,
env={
"SAGEMAKER_PROGRAM": program,
"SAGEMAKER_SUBMIT_DIRECTORY": directory,
},
image_uri="fakeimage",
)

container_env = hf_model.prepare_container_def("ml.m4.xlarge")["Environment"]

assert container_env["SAGEMAKER_PROGRAM"] == program
assert container_env["SAGEMAKER_SUBMIT_DIRECTORY"] == directory