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| # Copyright 2020 Erik Härkönen. All rights reserved. | |
| # This file is licensed 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 REPRESENTATIONS | |
| # OF ANY KIND, either express or implied. See the License for the specific language | |
| # governing permissions and limitations under the License. | |
| import sys | |
| import argparse | |
| import json | |
| from copy import deepcopy | |
| class Config: | |
| def __init__(self, **kwargs): | |
| self.from_args([]) # set all defaults | |
| self.default_args = deepcopy(self.__dict__) | |
| self.from_dict(kwargs) # override | |
| def __str__(self): | |
| custom = {} | |
| default = {} | |
| # Find non-default arguments | |
| for k, v in self.__dict__.items(): | |
| if k == 'default_args': | |
| continue | |
| in_default = k in self.default_args | |
| same_value = self.default_args.get(k) == v | |
| if in_default and same_value: | |
| default[k] = v | |
| else: | |
| custom[k] = v | |
| config = { | |
| 'custom': custom, | |
| 'default': default | |
| } | |
| return json.dumps(config, indent=4) | |
| def __repr__(self): | |
| return self.__str__() | |
| def from_dict(self, dictionary): | |
| for k, v in dictionary.items(): | |
| setattr(self, k, v) | |
| return self | |
| def from_args(self, args=sys.argv[1:]): | |
| parser = argparse.ArgumentParser(description='GAN component analysis config') | |
| parser.add_argument('--model', dest='model', type=str, default='StyleGAN', help='The network to analyze') # StyleGAN, DCGAN, ProGAN, BigGAN-XYZ | |
| parser.add_argument('--layer', dest='layer', type=str, default='g_mapping', help='The layer to analyze') | |
| parser.add_argument('--class', dest='output_class', type=str, default=None, help='Output class to generate (BigGAN: Imagenet, ProGAN: LSUN)') | |
| parser.add_argument('--est', dest='estimator', type=str, default='ipca', help='The algorithm to use [pca, fbpca, cupca, spca, ica]') | |
| parser.add_argument('--sparsity', type=float, default=1.0, help='Sparsity parameter of SPCA') | |
| parser.add_argument('--video', dest='make_video', action='store_true', help='Generate output videos (MP4s)') | |
| parser.add_argument('--batch', dest='batch_mode', action='store_true', help="Don't open windows, instead save results to file") | |
| parser.add_argument('-b', dest='batch_size', type=int, default=None, help='Minibatch size, leave empty for automatic detection') | |
| parser.add_argument('-c', dest='components', type=int, default=80, help='Number of components to keep') | |
| parser.add_argument('-n', type=int, default=300_000, help='Number of examples to use in decomposition') | |
| parser.add_argument('--use_w', action='store_true', help='Use W latent space (StyleGAN(2))') | |
| parser.add_argument('--sigma', type=float, default=2.0, help='Number of stdevs to walk in visualize.py') | |
| parser.add_argument('--inputs', type=str, default=None, help='Path to directory with named components') | |
| parser.add_argument('--seed', type=int, default=None, help='Seed used in decomposition') | |
| args = parser.parse_args(args) | |
| return self.from_dict(args.__dict__) |