text: #   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
  #
  # Licensed 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.
  
  import paddle
  
  op_real_in_out_name = {
      "conv2d": [["Input", "Filter"], ["Output"]],
      "depthwise_conv2d": [["Input", "Filter"], ["Output"]],
      "pool2d": [["X"], ["Out"]],
      "elementwise_add": [["X", "Y"], ["Out"]],
      "softmax": [["X"], ["Out"]],
      "relu": [["X"], ["Out"]],
      "relu6": [["X"], ["Out"]],
      "leaky_relu": [["X"], ["Out"]],
      "prelu": [["X"], ["Out"]],
      "tanh": [["X"], ["Out"]],
      "batch_norm": [["X"], ["Y"]],
      "sigmoid": [["X"], ["Out"]],
      "swish": [["X"], ["Out"]],
  }
  
  supported_quant_layers_map = {
      'Conv2D': paddle.nn.Conv2D,
      'Linear': paddle.nn.Linear,
      'AdaptiveAvgPool2D': paddle.nn.AdaptiveAvgPool2D,
      'AdaptiveMaxPool2D': paddle.nn.AdaptiveMaxPool2D,
      'AvgPool2D': paddle.nn.AvgPool2D,
      'MaxPool2D': paddle.nn.MaxPool2D,
      'Hardswish': paddle.nn.Hardswish,
      'LeakyReLU': paddle.nn.LeakyReLU,
      'PReLU': paddle.nn.PReLU,
      'ReLU': paddle.nn.ReLU,
      'ReLU6': paddle.nn.ReLU6,
      'Sigmoid': paddle.nn.Sigmoid,
      'Softmax': paddle.nn.Softmax,
      'Swish': paddle.nn.Swish,
      'Tanh': paddle.nn.Tanh,
      'Hardswish': paddle.nn.Hardswish,
      'BatchNorm': paddle.nn.BatchNorm,
      'GroupNorm': paddle.nn.GroupNorm,
      'LayerNorm': paddle.nn.LayerNorm,
  }
  
  fake_quantize_dequantize_types = [
      "fake_quantize_dequantize_abs_max",
      "fake_quantize_dequantize_channel_wise_abs_max",
      "fake_quantize_dequantize_moving_average_abs_max"
  ]
  
  out_scale_layers_list = (
      paddle.nn.Conv2D, paddle.nn.Linear, paddle.nn.MaxPool2D,
      paddle.nn.BatchNorm, paddle.nn.BatchNorm2D, paddle.nn.SyncBatchNorm,
      paddle.nn.LeakyReLU, paddle.nn.PReLU, paddle.nn.ReLU, paddle.nn.ReLU6,
      paddle.nn.Sigmoid, paddle.nn.Softmax, paddle.nn.Tanh, paddle.nn.Swish)
  