docstr: Loads the model from the given path.
docstr_tok: ["Loads","the","model","from","the","given","path","."]
code: def load(self, save_path):
      """Loads the model from the given path."""
      weights_save_path = os.path.join(
          save_path, MODEL_WEIGHTS_FILE_NAME
      )
      device = torch.device(get_torch_device())
      with open_file(weights_save_path, "rb") as f:
          state_dict = torch.load(f, map_location=device)
          self.load_state_dict(update_state_dict(state_dict))
  
imports: import logging
  import os
  from typing import Dict, Tuple, Union
  import numpy
  import torch
  from ludwig.accounting.used_tokens import get_used_tokens_for_ecd
  from ludwig.combiners.combiners import create_combiner
  from ludwig.constants import MODEL_ECD, MODEL_LLM, USED_TOKENS
  from ludwig.globals import MODEL_WEIGHTS_FILE_NAME
  from ludwig.models.base import BaseModel
  from ludwig.schema.model_types.ecd import ECDModelConfig
  from ludwig.utils import output_feature_utils
  from ludwig.utils.augmentation_utils import AugmentationPipelines
  from ludwig.utils.data_utils import clear_data_cache
  from ludwig.utils.fs_utils import open_file
  from ludwig.utils.state_dict_backward_compatibility import update_state_dict
  from ludwig.utils.torch_utils import get_torch_device
label_desc: Use image node_id 10 for calling the ECD obj's underlying member method code with example usage: obj.load(save_path) without return types