code: def test_jumpstart_model_header():
      header_dict = {
          "model_id": "tensorflow-ic-imagenet-inception-v3-classification-4",
          "version": "1.0.0",
          "min_version": "2.49.0",
          "spec_key": "community_models_specs/tensorflow-ic-imagenet-inception-v3-classification-4/specs_v1.0.0.json",
      }
  
      header1 = JumpStartModelHeader(header_dict)
  
      assert (
          header1.model_id
          == "tensorflow-ic-imagenet-inception-v3-classification-4"
      )
      assert header1.version == "1.0.0"
      assert header1.min_version == "2.49.0"
      assert (
          header1.spec_key
          == "community_models_specs/tensorflow-ic-imagenet-inception-v3-classification-4/specs_v1.0.0.json"
      )
  
      assert header1.to_json() == header_dict
  
      header2 = JumpStartModelHeader(
          {
              "model_id": "pytorch-ic-imagenet-inception-v3-classification-4",
              "version": "1.0.0",
              "min_version": "2.49.0",
              "spec_key": "community_models_specs/tensorflow-ic-imagenet-inception-v3-classification-4/specs_v1.0.0.json",
          }
      )
  
      assert header1 != header2
  
      header3 = copy.deepcopy(header1)
      assert header1 == header3
  
file_path: sagemaker-python-sdk/tests/unit/sagemaker/jumpstart/test_types.py
imports: from __future__ import absolute_import
  import copy
  from sagemaker.jumpstart.types import JumpStartECRSpecs, JumpStartHyperparameter, JumpStartInstanceTypeVariants, JumpStartModelSpecs, JumpStartModelHeader
  from tests.unit.sagemaker.jumpstart.constants import BASE_SPEC
label_desc: Use image node_id 1 for calling a global function with example usage: test_jumpstart_model_header() without return types