forked from mrq/DL-Art-School
deep_update dicts
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@ -7,6 +7,17 @@ import torch
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from train import Trainer
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from utils import options as option
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import collections.abc
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def deep_update(d, u):
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for k, v in u.items():
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if isinstance(v, collections.abc.Mapping):
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d[k] = deep_update(d.get(k, {}), v)
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else:
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d[k] = v
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return d
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def launch_trainer(opt, opt_path=''):
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rank = opt['gpu_ids'][0]
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@ -18,6 +29,7 @@ def launch_trainer(opt, opt_path=''):
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trainer.init(opt_path, opt, 'none')
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trainer.do_training()
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if __name__ == '__main__':
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"""
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Ad-hoc script (hard coded; no command-line parameters) that spawns multiple separate trainers from a single options
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@ -38,7 +50,7 @@ if __name__ == '__main__':
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all_opts = []
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for i, (mod, mod_dict) in enumerate(modifications.items()):
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nd = copy.deepcopy(opt)
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nd.update(mod_dict)
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deep_update(nd, mod_dict)
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opt['gpu_ids'] = [i]
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nd['name'] = f'{nd["name"]}_{mod}'
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nd['wandb_run_name'] = mod
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