class_docstr: The TFE Converter.
  
  Args:
      config: `Config` to use when constructing the TFE graph.
          Defaults to the current global TFE config.
      protocol: `Protocol` to use when constructing the TFE graph.
          Defaults to the current global TFE protocol.
class_docstr_tok: ["The","TFE","Converter",".","Args",":","config",":","`","Config","`","to","use","when","constructing","the","TFE","graph",".","Defaults","to","the","current","global","TFE","config",".","protocol",":","`","Protocol","`","to","use","when","constructing","the","TFE","graph",".","Defaults","to","the","current","global","TFE","protocol","."]
code: def _build_initializer(self, model_proto) -> None:
      initializers = {}
  
      for initializer in model_proto.graph.initializer:
          name = initializer.name
          shape = initializer.dims
          data_type = TENSOR_TYPE_TO_NP_TYPE[initializer.data_type]
          data = np.frombuffer(initializer.raw_data, dtype=data_type)
          data = data.reshape(shape)
          data = tf.convert_to_tensor(data)
          initializers[name] = data
      return initializers
  
imports: import functools
  from typing import Any
  from typing import List
  from typing import Optional
  from typing import Union
  import numpy
  import onnx
  import tensorflow
  import tf2onnx
  from onnx.mapping import TENSOR_TYPE_TO_NP_TYPE
  from onnx.onnx_ml_pb2 import ModelProto
  from tf2onnx import optimizer
  import tf_encrypted
  from tf_encrypted.config import Config
  from tf_encrypted.config import get_config
  from tf_encrypted.keras import optimizers
  from tf_encrypted.keras.models import BaseModel
  from tf_encrypted.player import Player
  from tf_encrypted.protocol import Protocol
  from tf_encrypted.protocol.protocol import TFETensor
  from .nodes import build_node
label_desc: Use image node_id 3 for calling the Converter obj's underlying member method code with example usage: obj._build_initializer(model_proto) and returns: initializers