96 lines
2.5 KiB
Python
96 lines
2.5 KiB
Python
import pytest
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from pytorch_lightning import Trainer
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from pytorch_lightning.examples.new_project_templates.lightning_module_template import LightningTemplateModel
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from argparse import Namespace
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from test_tube import Experiment
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from pytorch_lightning.callbacks import ModelCheckpoint
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import numpy as np
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import warnings
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import torch
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import os
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import shutil
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import pdb
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def get_model():
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# set up model with these hyperparams
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root_dir = os.path.dirname(os.path.realpath(__file__))
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hparams = Namespace(**{'drop_prob': 0.2,
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'batch_size': 32,
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'in_features': 28*28,
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'learning_rate': 0.001*8,
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'optimizer_name': 'adam',
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'data_root': os.path.join(root_dir, 'mnist'),
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'out_features': 10,
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'hidden_dim': 1000})
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model = LightningTemplateModel(hparams)
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return model
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def get_exp(debug=True):
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# set up exp object without actually saving logs
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root_dir = os.path.dirname(os.path.realpath(__file__))
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exp = Experiment(debug=debug, save_dir=root_dir, name='tests_tt_dir')
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return exp
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def init_save_dir():
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root_dir = os.path.dirname(os.path.realpath(__file__))
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save_dir = os.path.join(root_dir, 'save_dir')
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if os.path.exists(save_dir):
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shutil.rmtree(save_dir)
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os.makedirs(save_dir, exist_ok=True)
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return save_dir
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def clear_save_dir():
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root_dir = os.path.dirname(os.path.realpath(__file__))
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save_dir = os.path.join(root_dir, 'save_dir')
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if os.path.exists(save_dir):
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shutil.rmtree(save_dir)
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def main():
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save_dir = init_save_dir()
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model = get_model()
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# exp file to get meta
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exp = get_exp(False)
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exp.save()
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# exp file to get weights
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checkpoint = ModelCheckpoint(save_dir)
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trainer = Trainer(
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checkpoint_callback=checkpoint,
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progress_bar=True,
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experiment=exp,
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max_nb_epochs=1,
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train_percent_check=0.1,
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val_percent_check=0.1,
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gpus=[0, 1],
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distributed_backend='ddp',
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use_amp=True
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)
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result = trainer.fit(model)
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# correct result and ok accuracy
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assert result == 1, 'amp + ddp model failed to complete'
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# load trained model
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pdb.set_trace()
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tags_path = exp.get_data_path(exp.name, exp.version)
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tags_path = os.path.join(tags_path, 'meta_tags.csv')
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LightningTemplateModel.load_from_metrics(weights_path=save_dir, tags_csv=tags_path)
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clear_save_dir()
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if __name__ == '__main__':
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main() |