src/smallmatter/sm.py [464:514]:
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        def __init__(
            self,
            framework_version: str,  # New arg
            s3_prefix: str,  # New arg
            role: str,
            instance_count: int,
            instance_type: str,
            py_version: str = "py3",  # New kwarg
            image_uri: Optional[str] = None,
            volume_size_in_gb: int = 30,
            volume_kms_key: Optional[str] = None,
            output_kms_key: Optional[str] = None,
            max_runtime_in_seconds: Optional[int] = None,
            base_job_name: Optional[str] = None,
            sagemaker_session: Optional[Session] = None,
            env: Optional[Dict[str, str]] = None,
            tags: Optional[List[Dict[str, Any]]] = None,
            network_config: Optional[NetworkConfig] = None,
        ):
            """This processor executes a Python script in a managed MXNet execution environment.

            Unless ``image_uri`` is specified, the MXNet environment is an
            Amazon-built Docker container that executes functions defined in the supplied
            ``entry_point`` Python script.

            The arguments have the exact same meaning as in ``FrameworkProcessor``.

            .. tip::

                You can find additional parameters for initializing this class at
                :class:`~smallmatter.ds.FrameworkProcessor`.
            """
            super().__init__(
                self.estimator_cls,
                framework_version,
                s3_prefix,
                role,
                instance_count,
                instance_type,
                py_version,
                image_uri,
                volume_size_in_gb,
                volume_kms_key,
                output_kms_key,
                max_runtime_in_seconds,
                base_job_name,
                sagemaker_session,
                env,
                tags,
                network_config,
            )
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src/smallmatter/sm.py [521:571]:
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        def __init__(
            self,
            framework_version: str,  # New arg
            s3_prefix: str,  # New arg
            role: str,
            instance_count: int,
            instance_type: str,
            py_version: str = "py3",  # New kwarg
            image_uri: Optional[str] = None,
            volume_size_in_gb: int = 30,
            volume_kms_key: Optional[str] = None,
            output_kms_key: Optional[str] = None,
            max_runtime_in_seconds: Optional[int] = None,
            base_job_name: Optional[str] = None,
            sagemaker_session: Optional[Session] = None,
            env: Optional[Dict[str, str]] = None,
            tags: Optional[List[Dict[str, Any]]] = None,
            network_config: Optional[NetworkConfig] = None,
        ):
            """This processor executes a Python script in a PyTorch execution environment.

            Unless ``image_uri`` is specified, the PyTorch environment is an
            Amazon-built Docker container that executes functions defined in the supplied
            ``entry_point`` Python script.

            The arguments have the exact same meaning as in ``FrameworkProcessor``.

            .. tip::

                You can find additional parameters for initializing this class at
                :class:`~smallmatter.ds.FrameworkProcessor`.
            """
            super().__init__(
                self.estimator_cls,
                framework_version,
                s3_prefix,
                role,
                instance_count,
                instance_type,
                py_version,
                image_uri,
                volume_size_in_gb,
                volume_kms_key,
                output_kms_key,
                max_runtime_in_seconds,
                base_job_name,
                sagemaker_session,
                env,
                tags,
                network_config,
            )
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