class_docstr: Mock class to replicate the context passed into model initialize
code: def __init__(
      self,
      model_pt_file="model.pt",
      model_dir="ts/torch_handler/unit_tests/models/tmp",
      model_file="model.py",
      gpu_id="0",
      model_name="mnist",
      model_yaml_config_file=None,
  ):
      self.manifest = {"model": {}}
      if model_pt_file:
          self.manifest["model"]["serializedFile"] = model_pt_file
  
      if model_file:
          self.manifest["model"]["modelFile"] = model_file
  
      self.system_properties = {"model_dir": model_dir}
  
      if torch.cuda.is_available() and gpu_id:
          self.system_properties["gpu_id"] = gpu_id
  
      self.explain = False
      self.metrics = MetricsStore(uuid.uuid4(), model_name)
      self.model_yaml_config = {}
  
      if model_yaml_config_file:
          self.model_yaml_config = get_yaml_config(
              os.path.join(model_dir, model_yaml_config_file)
          )
  
file_path: serve/ts/torch_handler/unit_tests/test_utils/mock_context.py
imports: import os
  import uuid
  import torch
  from ts.metrics.metrics_store import MetricsStore
  from ts.utils.util import get_yaml_config
label_desc: Use image node_id 1 to create a new MockContext object  with example: obj = MockContext(model_pt_file, model_dir, model_file, gpu_id, model_name, model_yaml_config_file)