text: # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
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  # 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
  #
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  """
  a simple multilayer perceptron
  """
  from __future__ import absolute_import
  from tvm import relay
  from .init import create_workload
  
  def get_net(batch_size,
              num_classes=10,
              image_shape=(1, 28, 28),
              dtype="float32"):
      """Get network a simple multilayer perceptron.
  
      batch_size : int
          The batch size used in the model
  
      num_classes : int, optional
          Number of claseses
  
      image_shape : tuple, optional
          The input image shape
  
      dtype : str, optional
          The data type
  
      Returns
      -------
      net : relay.Function
          The dataflow.
      """
      data_shape = (batch_size,) + image_shape
      data = relay.var("data",
                       shape=data_shape,
                       dtype=dtype)
      data = relay.nn.batch_flatten(data)
      fc1 = relay.nn.dense(data, relay.var("fc1_weight"), units=128)
      fc1 = relay.nn.bias_add(fc1, relay.var("fc1_bias"), axis=-1)
      act1 = relay.nn.relu(fc1)
      fc2 = relay.nn.dense(act1, relay.var("fc2_weight"), units=64)
      fc2 = relay.nn.bias_add(fc2, relay.var("fc2_bias"), axis=-1)
      act2 = relay.nn.relu(fc2)
      fc3 = relay.nn.dense(act2, relay.var("fc3_weight"), units=num_classes)
      fc3 = relay.nn.bias_add(fc3, relay.var("fc3_bias"), axis=-1)
      mlp = relay.nn.softmax(data=fc3)
      args = relay.ir_pass.free_vars(mlp)
      return relay.Function(args, mlp)
  
  
  def get_workload(batch_size,
                   num_classes=10,
                   image_shape=(1, 28, 28),
                   dtype="float32"):
      """Get benchmark workload for a simple multilayer perceptron.
  
      Parameters
      ----------
      batch_size : int
          The batch size used in the model
  
      num_classes : int, optional
          Number of claseses
  
      image_shape : tuple, optional
          The input image shape
  
      dtype : str, optional
          The data type
  
      Returns
      -------
      net : relay.Function
          The dataflow.
  
      params : dict of str to NDArray
          The parameters.
      """
      net = get_net(batch_size, num_classes, image_shape, dtype)
      return create_workload(net)
  