karolmajek/maxdeeplab

1# coding=utf-82# Copyright 2021 The Deeplab2 Authors.3#4# Licensed under the Apache License, Version 2.0 (the "License");5# you may not use this file except in compliance with the License.6# You may obtain a copy of the License at7#8#     http://www.apache.org/licenses/LICENSE-2.09#10# Unless required by applicable law or agreed to in writing, software11# distributed under the License is distributed on an "AS IS" BASIS,12# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.13# See the License for the specific language governing permissions and14# limitations under the License.15 16"""AutoAugment policy file.17 18This file contains found auto-augment policy.19 20Please cite or refer to the following papers for details:21- Ekin D Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V Le.22"Autoaugment: Learning augmentation policies from data." In CVPR, 2019.23 24- Ekin D Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V Le.25"Randaugment: Practical automated data augmentation with a reduced search26space." In CVPR, 2020.27"""28 29# Reduced augmentation operation space.30augmentation_reduced_operations = (31    'AutoContrast', 'Equalize', 'Invert', 'Posterize',32    'Solarize', 'Color', 'Contrast', 'Brightness', 'Sharpness')33 34augmentation_probabilities = [0.0, 0.2, 0.4, 0.6, 0.8, 1.0]35 36 37def convert_policy(policy,38                   search_space=augmentation_reduced_operations,39                   probability_scale=1.0,40                   magnitude_scale=1):41  """Converts policy from a list of numbers."""42  if len(policy) % 6:43    raise ValueError('Policy length must be a multiple of 6.')44  num_policies = len(policy) // 645  policy_list = [[] for _ in range(num_policies)]46  for n in range(num_policies):47    for i in range(2):48      operation_id, prob_id, magnitude = (49          policy[6 * n + i * 3 : 6 * n + (i + 1) * 3])50      policy_name = search_space[operation_id]51      policy_prob = (52          augmentation_probabilities[prob_id] * probability_scale)53      policy_list[n].append((policy_name,54                             policy_prob,55                             magnitude * magnitude_scale))56  return policy_list57 58 59simple_classification_policy = [8, 2, 7, 7, 1, 10,60                                1, 0, 9, 6, 1, 10,61                                8, 1, 9, 5, 1, 9,62                                4, 1, 7, 1, 3, 9,63                                8, 1, 1, 1, 1, 7]64 65# All available policies.66available_policies = {67    'simple_classification_policy_magnitude_scale_0.2': convert_policy(68        simple_classification_policy,69        augmentation_reduced_operations,70        magnitude_scale=0.2),71    'simple_classification_policy': convert_policy(72        simple_classification_policy,73        augmentation_reduced_operations,74        magnitude_scale=1),75}76