code: def emit_Gather(self, IR_node):
      raise NotImplementedError()
      W = self.weights_dict[IR_node.name]["weights"]
      if W.ndim == 2:
          vocab_size = W.shape[0]
          output_channels = W.shape[1]
          builder.add_embedding(
              name=IR_node.real_name,
              W=W,
              b=None,
              input_dim=vocab_size,
              output_channels=output_channels,
              has_bias=False,
              input_name=input_name,
              output_name=IR_node.real_name,
          )
      else:
          raise NotImplementedError()
  
imports: from __future__ import division
  import os
  import numpy
  from six import string_types
  from mmdnn.conversion.common.IR.IR_graph import IRGraph, IRGraphNode
  import mmdnn.conversion.common.IR.graph_pb2
  from mmdnn.conversion.common.IR.graph_pb2 import NodeDef, GraphDef, DataType
  from mmdnn.conversion.common.DataStructure.emitter import Emitter
  from mmdnn.conversion.common.utils import *
  from mmdnn.conversion.coreml.coreml_utils import _infer_coreml_input_shape
  from coremltools.models.neural_network import NeuralNetworkBuilder
  from coremltools.models import datatypes
  from coremltools.models import MLModel
  from coremltools.models.utils import save_spec
label_desc: Use image node_id 35 for calling the CoreMLEmitter obj's underlying member method code with example usage: obj.emit_Gather(IR_node) without return types