|
| 1 | +import logging |
| 2 | +from logging.handlers import RotatingFileHandler |
| 3 | +from pathlib import Path |
| 4 | +import numpy as np |
| 5 | +from pytorch_lightning.cli import LightningCLI |
| 6 | +from pytorch_lightning.loggers import CometLogger |
| 7 | + |
| 8 | +import models |
| 9 | +from srdata import SRData |
| 10 | + |
| 11 | + |
| 12 | +class CustomLightningCLI(LightningCLI): |
| 13 | + def add_arguments_to_parser(self, parser): |
| 14 | + parser.add_argument('--log_level', type=str, default='warning', |
| 15 | + choices=('debug', 'info', 'warning', 'error', 'critical')) |
| 16 | + parser.add_argument('--file_log_level', type=str, default='info', |
| 17 | + choices=('debug', 'info', 'warning', 'error', 'critical')) |
| 18 | + |
| 19 | + # https://lightning.ai/docs/pytorch/LTS/cli/lightning_cli_expert.html#argument-linking |
| 20 | + parser.link_arguments('data.batch_size', 'model.init_args.batch_size') |
| 21 | + parser.link_arguments('data.eval_datasets', 'model.init_args.eval_datasets') |
| 22 | + parser.link_arguments('data.patch_size', 'model.init_args.patch_size') |
| 23 | + parser.link_arguments('data.scale_factor', 'model.init_args.scale_factor') |
| 24 | + |
| 25 | + parser.link_arguments('trainer.check_val_every_n_epoch', 'model.init_args.log_weights_every_n_epochs') |
| 26 | + parser.link_arguments('trainer.check_val_every_n_epoch', 'trainer.callbacks.init_args.every_n_epochs') |
| 27 | + parser.link_arguments('trainer.default_root_dir', 'model.init_args.default_root_dir') |
| 28 | + parser.link_arguments('trainer.default_root_dir', 'trainer.logger.init_args.save_dir') # not working for comet logger |
| 29 | + parser.link_arguments('trainer.default_root_dir', 'trainer.callbacks.init_args.dirpath', |
| 30 | + compute_fn=lambda x: f'{x}/checkpoints') |
| 31 | + parser.link_arguments('trainer.max_epochs', 'model.init_args.max_epochs') |
| 32 | + |
| 33 | + def before_fit(self): |
| 34 | + # setup logging |
| 35 | + default_root_dir = Path(self.config['fit']['trainer']['default_root_dir']) |
| 36 | + default_root_dir.mkdir(parents=True, exist_ok=True) |
| 37 | + |
| 38 | + setup_log( |
| 39 | + level=self.config['fit']['log_level'], |
| 40 | + log_file=default_root_dir / 'run.log', |
| 41 | + file_level=self.config['fit']['file_log_level'], |
| 42 | + logs_to_silence=['PIL'], |
| 43 | + ) |
| 44 | + |
| 45 | + for logger in self.trainer.loggers: |
| 46 | + if isinstance(logger, CometLogger): |
| 47 | + # all code will be under /work when running on docker |
| 48 | + logger.experiment.log_code(folder='/work') |
| 49 | + logger.experiment.log_parameters(self.config.as_dict()) |
| 50 | + logger.experiment.set_model_graph(str(self.model)) |
| 51 | + logger.experiment.log_other( |
| 52 | + 'trainable params', sum(p.numel() for p in self.model.parameters() if p.requires_grad)) |
| 53 | + |
| 54 | + total_params = sum(p.numel() for p in self.model.parameters()) |
| 55 | + logger.experiment.log_other('total params', total_params) |
| 56 | + |
| 57 | + total_loss_params = 0 |
| 58 | + total_loss_trainable_params = 0 |
| 59 | + for loss in self.model._losses: |
| 60 | + if loss.name.find('adaptive') >= 0: |
| 61 | + total_loss_params += sum(p.numel() for p in loss.loss.parameters()) |
| 62 | + total_loss_trainable_params += sum(p.numel()for p in loss.loss.parameters() if p.requires_grad) |
| 63 | + |
| 64 | + if total_loss_params > 0: |
| 65 | + logger.experiment.log_other('loss total params', total_loss_params) |
| 66 | + logger.experiment.log_other('loss trainable params', total_loss_trainable_params) |
| 67 | + |
| 68 | + # assume 4 bytes/number (float on cuda) |
| 69 | + denom = 1024 ** 2. |
| 70 | + input_size = abs(np.prod(self.model.example_input_array.size()) * 4. / denom) |
| 71 | + params_size = abs(total_params * 4. / denom) |
| 72 | + logger.experiment.log_other('input size (MB)', input_size) |
| 73 | + logger.experiment.log_other('params size (MB)', params_size) |
| 74 | + break |
| 75 | + |
| 76 | + def after_fit(self): |
| 77 | + for logger in self.trainer.loggers: |
| 78 | + if isinstance(logger, CometLogger): |
| 79 | + default_root_dir = Path(self.config['fit']['trainer']['default_root_dir']) |
| 80 | + last_checkpoint = default_root_dir / 'checkpoints' / 'last.ckpt' |
| 81 | + model_name = self.config['fit']['model']['class_path'].split('.')[-1] |
| 82 | + logger.experiment.log_model(f'{model_name}', f'{last_checkpoint}', overwrite=True) |
| 83 | + logger.experiment.log_asset(f'{default_root_dir / "run.log"}') |
| 84 | + break |
| 85 | + |
| 86 | + |
| 87 | +def cli_main() -> None: |
| 88 | + _ = CustomLightningCLI( |
| 89 | + model_class=models.SRModel, |
| 90 | + subclass_mode_model=True, |
| 91 | + datamodule_class=SRData, |
| 92 | + parser_kwargs={"parser_mode": "omegaconf"}, |
| 93 | + ) |
| 94 | + |
| 95 | + |
| 96 | +def setup_log( |
| 97 | + level: str = 'warning', |
| 98 | + log_file: str | Path = Path('run.log'), |
| 99 | + file_level: str = 'info', |
| 100 | + logs_to_silence: list[str] = [], |
| 101 | + ) -> None: |
| 102 | + """ |
| 103 | + Setup the logging. |
| 104 | +
|
| 105 | + Args: |
| 106 | + log_level (str): stdout log level. Defaults to 'warning'. |
| 107 | + log_file (str | Path): file where the log output should be stored. Defaults to 'run.log'. |
| 108 | + file_log_level (str): file log level. Defaults to 'info'. |
| 109 | + logs_to_silence (list[str]): list of loggers to be silenced. Useful when using log level < 'warning'. Defaults to []. |
| 110 | + """ |
| 111 | + # TODO: fix this according to this |
| 112 | + # https://stackoverflow.com/questions/384076/how-can-i-color-python-logging-output |
| 113 | + # https://www.electricmonk.nl/log/2017/08/06/understanding-pythons-logging-module/ |
| 114 | + |
| 115 | + # convert log levels to int |
| 116 | + int_log_level = { |
| 117 | + 'debug': logging.DEBUG, # 10 |
| 118 | + 'info': logging.INFO, # 20 |
| 119 | + 'warning': logging.WARNING, # 30 |
| 120 | + 'error': logging.ERROR, # 40 |
| 121 | + 'critical': logging.CRITICAL, # 50 |
| 122 | + } |
| 123 | + |
| 124 | + stdout_log_level = int_log_level[level] |
| 125 | + file_log_level = int_log_level[file_level] |
| 126 | + |
| 127 | + # create a handler to log to stderr |
| 128 | + stderr_handler = logging.StreamHandler() |
| 129 | + stderr_handler.setLevel(stdout_log_level) |
| 130 | + |
| 131 | + # create a logging format |
| 132 | + if stdout_log_level >= logging.WARNING: |
| 133 | + stderr_formatter = logging.Formatter('{message}', style='{') |
| 134 | + else: |
| 135 | + stderr_formatter = logging.Formatter( |
| 136 | + # format: |
| 137 | + # <10 = pad with spaces if needed until it reaches 10 chars length |
| 138 | + # .10 = limit the length to 10 chars |
| 139 | + '{name:<10.10} [{levelname:.1}] {message}', style='{') |
| 140 | + stderr_handler.setFormatter(stderr_formatter) |
| 141 | + |
| 142 | + # create a file handler that have size limit |
| 143 | + if isinstance(log_file, str): |
| 144 | + log_file = Path(log_file).expanduser() |
| 145 | + |
| 146 | + file_handler = RotatingFileHandler(log_file, maxBytes=5_000_000, backupCount=5) # ~ 5 MB |
| 147 | + file_handler.setLevel(file_log_level) |
| 148 | + |
| 149 | + # https://docs.python.org/3/library/logging.html#logrecord-attributes |
| 150 | + file_formatter = logging.Formatter( |
| 151 | + '{asctime} - {name:<20.20} {levelname:<8} {message}', datefmt='%Y-%m-%d %H:%M:%S', style='{') |
| 152 | + file_handler.setFormatter(file_formatter) |
| 153 | + |
| 154 | + # add the handlers to the root logger |
| 155 | + logging.basicConfig(handlers=[file_handler, stderr_handler], level=logging.DEBUG) |
| 156 | + |
| 157 | + # change logger level of logs_to_silence to warning |
| 158 | + for other_logger in logs_to_silence: |
| 159 | + logging.getLogger(other_logger).setLevel(logging.WARNING) |
| 160 | + |
| 161 | + # create logger |
| 162 | + logger = logging.getLogger(__name__) |
| 163 | + |
| 164 | + logger.info(f'Saving logs to {log_file.absolute()}') |
| 165 | + logger.info(f'Log level: {logging.getLevelName(stdout_log_level)}') |
| 166 | + |
| 167 | + |
| 168 | +if __name__ == "__main__": |
| 169 | + cli_main() |
| 170 | + # note: it is good practice to implement the CLI in a function and call it in the main if block |
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