def main():
    '\n    ### Run the experiment\n    '
    experiment.create(name='compressive_transformer', comment='')
    conf = Configs()
    experiment.configs(conf, {'tokenizer': 'character', 'text': 'tiny_shakespeare', 'optimizer.learning_rate': 0.00025, 'optimizer.optimizer': 'AdamW', 'prompt': 'It is', 'prompt_separator': '', 'train_loader': 'sequential_train_loader', 'valid_loader': 'sequential_valid_loader', 'seq_len': 8, 'mem_len': 8, 'epochs': 128, 'batch_size': 32, 'inner_iterations': 25, 'compression_rate': 2})
    experiment.add_pytorch_models({'model': conf.model})
    with experiment.start():
        conf.run()
### Run the experiment
def main():
    '\n    \n    '
    experiment.create(name='compressive_transformer', comment=)
    conf = Configs()
    experiment.configs(conf, {'tokenizer': 'character', 'text': 'tiny_shakespeare', 'optimizer.learning_rate': 0.00025, 'optimizer.optimizer': 'AdamW', 'prompt': 'It is', 'prompt_separator': , 'train_loader': 'sequential_train_loader', 'valid_loader': 'sequential_valid_loader', 'seq_len': 8, 'mem_len': 8, 'epochs': 128, 'batch_size': 32, 'inner_iterations': 25, 'compression_rate': 2})
    experiment.add_pytorch_models({'model': conf.model})
    with experiment.start():
        conf.run()