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_forward(self, model_proto, tfe_nodes):
      nodes = model_proto.graph.node
  
      def forward_function(x):
          node_outputs = {}
          for index, input in enumerate(model_proto.graph.input):
              node_outputs[input.name] = x[index]
          for node in nodes:
              inputs = []
              for input in node.input:
                  if input in node_outputs.keys():
                      inputs.append(node_outputs[input])
              with tf.name_scope(node.name + "/forward"):
                  res = tfe_nodes[node.name].forward(inputs)
              for i, output in enumerate(node.output):
                  node_outputs[output] = res[i]
          res = []
          for output in model_proto.graph.output:
              res.append(node_outputs[output.name])
          return res
  
      return forward_function
  
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 5 for calling the Converter obj's underlying member method code with example usage: obj._build_forward(model_proto, tfe_nodes) and returns: forward_function, res