code: def get_fit_kwargs(
      model_id: str,
      model_version: Optional[str] = None,
      region: Optional[str] = None,
      inputs: Optional[
          Union[str, Dict, TrainingInput, FileSystemInput]
      ] = None,
      wait: Optional[bool] = None,
      logs: Optional[str] = None,
      job_name: Optional[str] = None,
      experiment_config: Optional[Dict[str, str]] = None,
      tolerate_vulnerable_model: Optional[bool] = None,
      tolerate_deprecated_model: Optional[bool] = None,
      sagemaker_session: Optional[Session] = None,
  ) -> JumpStartEstimatorFitKwargs:
      """Returns kwargs required call `fit` on `sagemaker.estimator.Estimator` object."""
  
      estimator_fit_kwargs: JumpStartEstimatorFitKwargs = (
          JumpStartEstimatorFitKwargs(
              model_id=model_id,
              model_version=model_version,
              region=region,
              inputs=inputs,
              wait=wait,
              logs=logs,
              job_name=job_name,
              experiment_config=experiment_config,
              tolerate_deprecated_model=tolerate_deprecated_model,
              tolerate_vulnerable_model=tolerate_vulnerable_model,
              sagemaker_session=sagemaker_session,
          )
      )
  
      estimator_fit_kwargs = _add_model_version_to_kwargs(
          estimator_fit_kwargs
      )
      estimator_fit_kwargs = _add_region_to_kwargs(estimator_fit_kwargs)
      estimator_fit_kwargs = _add_training_job_name_to_kwargs(
          estimator_fit_kwargs
      )
      estimator_fit_kwargs = _add_fit_extra_kwargs(estimator_fit_kwargs)
  
      return estimator_fit_kwargs
  
imports: from __future__ import absolute_import
  from typing import Dict, List, Optional, Union
  from sagemaker import environment_variables, hyperparameters, image_uris, instance_types, metric_definitions, model_uris, script_uris
  from sagemaker.jumpstart.artifacts import _model_supports_incremental_training, _retrieve_model_package_model_artifact_s3_uri
  from sagemaker.jumpstart.artifacts.resource_names import _retrieve_resource_name_base
  from sagemaker.session import Session
  from sagemaker.async_inference.async_inference_config import AsyncInferenceConfig
  from sagemaker.base_deserializers import BaseDeserializer
  from sagemaker.base_serializers import BaseSerializer
  from sagemaker.debugger.debugger import DebuggerHookConfig, RuleBase, TensorBoardOutputConfig
  from sagemaker.debugger.profiler_config import ProfilerConfig
  from sagemaker.explainer.explainer_config import ExplainerConfig
  from sagemaker.inputs import FileSystemInput, TrainingInput
  from sagemaker.instance_group import InstanceGroup
  from sagemaker.jumpstart.artifacts import _retrieve_estimator_init_kwargs, _retrieve_estimator_fit_kwargs, _model_supports_training_model_uri
  from sagemaker.jumpstart.constants import DEFAULT_JUMPSTART_SAGEMAKER_SESSION, JUMPSTART_DEFAULT_REGION_NAME, JUMPSTART_LOGGER, TRAINING_ENTRY_POINT_SCRIPT_NAME, SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY
  from sagemaker.jumpstart.enums import JumpStartScriptScope
  from sagemaker.jumpstart.factory import model
  from sagemaker.jumpstart.types import JumpStartEstimatorDeployKwargs, JumpStartEstimatorFitKwargs, JumpStartEstimatorInitKwargs, JumpStartKwargs, JumpStartModelDeployKwargs, JumpStartModelInitKwargs
  from sagemaker.jumpstart.utils import add_jumpstart_model_id_version_tags, update_dict_if_key_not_present, resolve_estimator_sagemaker_config_field, verify_model_region_and_return_specs
  from sagemaker.model_monitor.data_capture_config import DataCaptureConfig
  from sagemaker.serverless.serverless_inference_config import ServerlessInferenceConfig
  from sagemaker.utils import name_from_base, format_tags, Tags
  from sagemaker.workflow.entities import PipelineVariable
label_desc: Use image node_id 2 for calling a global function with example usage: get_fit_kwargs(model_id, model_version, region, inputs, wait, logs, job_name, experiment_config, tolerate_vulnerable_model, tolerate_deprecated_model, sagemaker_session) and returns: estimator_fit_kwargs