text: # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
  # distributed with this work for additional information
  # regarding copyright ownership.  The ASF licenses this file
  # to you under the Apache License, Version 2.0 (the
  # "License"); you may not use this file except in compliance
  # with the License.  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing,
  # software distributed under the License is distributed on an
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  # KIND, either express or implied.  See the License for the
  # specific language governing permissions and limitations
  # under the License.
  
  """MXNet model zoo for testing purposes."""
  from __future__ import absolute_import
  from . import mlp, vgg, resnet, dqn, inception_v3, squeezenet, dcgan
  import tvm.relay.testing
  
  # mlp
  def mx_mlp():
      num_class = 10
      return mlp.get_symbol(num_class)
  
  
  def relay_mlp():
      num_class = 10
      return tvm.relay.testing.mlp.get_workload(1, num_class)[0]
  
  
  # vgg
  def mx_vgg(num_layers):
      num_class = 1000
      return vgg.get_symbol(num_class, num_layers)
  
  
  def relay_vgg(num_layers):
      num_class = 1000
      return tvm.relay.testing.vgg.get_workload(1, num_class, num_layers=num_layers)[0]
  
  
  # resnet
  def mx_resnet(num_layers):
      num_class = 1000
      return resnet.get_symbol(num_class, num_layers, "3,224,224")
  
  
  def relay_resnet(num_layers):
      num_class = 1000
      return tvm.relay.testing.resnet.get_workload(1, num_class, num_layers=num_layers)[0]
  
  
  # dqn
  mx_dqn = dqn.get_symbol
  
  
  def relay_dqn():
      return tvm.relay.testing.dqn.get_workload(1)[0]
  
  
  # squeezenet
  def mx_squeezenet(version):
      return squeezenet.get_symbol(version=version)
  
  
  def relay_squeezenet(version):
      return tvm.relay.testing.squeezenet.get_workload(1, version=version)[0]
  
  
  # inception
  mx_inception_v3 = inception_v3.get_symbol
  
  
  def relay_inception_v3():
      return tvm.relay.testing.inception_v3.get_workload(1)[0]
  
  
  # dcgan generator
  mx_dcgan = dcgan.get_symbol
  
  
  def relay_dcgan(batch_size):
      return tvm.relay.testing.dcgan.get_workload(batch_size=batch_size)[0]
  