kopia lustrzana https://github.com/lzzcd001/MeshDiffusion
44 wiersze
1.3 KiB
Python
44 wiersze
1.3 KiB
Python
# coding=utf-8
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# Copyright 2020 The Google Research Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Training and evaluation"""
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from absl import app
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from absl import flags
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from ml_collections.config_flags import config_flags
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import lib.diffusion.trainer as trainer
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import lib.diffusion.evaler as evaler
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FLAGS = flags.FLAGS
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config_flags.DEFINE_config_file(
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"config", None, "diffusion configs", lock_config=False)
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flags.DEFINE_enum("mode", None, ["train", "uncond_gen", "cond_gen"], "Running mode")
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flags.mark_flags_as_required(["config", "mode"])
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def main(argv):
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if FLAGS.mode == 'train':
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trainer.train(FLAGS.config)
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elif FLAGS.mode == 'uncond_gen':
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evaler.uncond_gen(FLAGS.config)
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elif FLAGS.mode == 'cond_gen':
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evaler.cond_gen(FLAGS.config)
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if __name__ == "__main__":
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app.run(main)
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