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_node(
      self,
      model_input_shapes,
      model_proto,
      model_initializers,
      model_providers,
  ):
      tfe_nodes = {}
      input_shapes = {}
      for index, input in enumerate(model_proto.graph.input):
          input_shapes[input.name] = model_input_shapes[index]
  
      for node in model_proto.graph.node:
          inputs = []
          for input in node.input:
              if input in model_initializers.keys():
                  inputs.append(model_initializers[input])
              elif input in input_shapes.keys():
                  inputs.append(input_shapes[input])
              else:
                  raise KeyError(
                      "Node "
                      + node.name
                      + " input: "
                      + input
                      + " doesn't found!"
                  )
          tfe_node = build_node(node, inputs, model_providers)
          tfe_nodes[node.name] = tfe_node
          for index, output in enumerate(node.output):
              input_shapes[output] = tfe_node.output_shape[index]
  
      return tfe_nodes, input_shapes.keys()
  
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 4 for calling the Converter obj's underlying member method code with example usage: obj._build_node(model_input_shapes, model_proto, model_initializers, model_providers) and returns: tfe_nodes,  input_shapes