96 lines
3.1 KiB
Python
96 lines
3.1 KiB
Python
import logging
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from pathlib import Path
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from typing import Optional
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import torch.nn as nn
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def add_spectral_norm(module):
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if isinstance(module, (nn.Conv2d, nn.ConvTranspose2d)) and not hasattr(module, 'weight_u'):
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return nn.utils.spectral_norm(module)
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else:
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return module
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def setup_logger(
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name: Optional[str] = None,
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level: int = logging.INFO,
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logger_format: str = "%(asctime)s %(name)s %(levelname)s: %(message)s",
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filepath: Optional[str] = None,
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distributed_rank: Optional[int] = None,
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) -> logging.Logger:
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"""Setups logger: name, level, format etc.
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Args:
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name (str, optional): new name for the logger. If None, the standard logger is used.
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level (int): logging level, e.g. CRITICAL, ERROR, WARNING, INFO, DEBUG
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logger_format (str): logging format. By default, `%(asctime)s %(name)s %(levelname)s: %(message)s`
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filepath (str, optional): Optional logging file path. If not None, logs are written to the file.
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distributed_rank (int, optional): Optional, rank in distributed configuration to avoid logger setup for workers.
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If None, distributed_rank is initialized to the rank of process.
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Returns:
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logging.Logger
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For example, to improve logs readability when training with a trainer and evaluator:
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.. code-block:: python
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from ignite.utils import setup_logger
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trainer = ...
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evaluator = ...
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trainer.logger = setup_logger("trainer")
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evaluator.logger = setup_logger("evaluator")
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trainer.run(data, max_epochs=10)
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# Logs will look like
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# 2020-01-21 12:46:07,356 trainer INFO: Engine run starting with max_epochs=5.
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# 2020-01-21 12:46:07,358 trainer INFO: Epoch[1] Complete. Time taken: 00:5:23
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# 2020-01-21 12:46:07,358 evaluator INFO: Engine run starting with max_epochs=1.
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# 2020-01-21 12:46:07,358 evaluator INFO: Epoch[1] Complete. Time taken: 00:01:02
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# ...
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"""
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logger = logging.getLogger(name)
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# don't propagate to ancestors
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# the problem here is to attach handlers to loggers
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# should we provide a default configuration less open ?
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if name is not None:
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logger.propagate = False
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# Remove previous handlers
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if logger.hasHandlers():
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for h in list(logger.handlers):
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logger.removeHandler(h)
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formatter = logging.Formatter(logger_format)
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if distributed_rank is None:
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import ignite.distributed as idist
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distributed_rank = idist.get_rank()
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if distributed_rank > 0:
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logger.addHandler(logging.NullHandler())
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else:
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logger.setLevel(logging.DEBUG)
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ch = logging.StreamHandler()
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ch.setLevel(level)
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ch.setFormatter(formatter)
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logger.addHandler(ch)
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if filepath is not None and Path(filepath).parent.exists():
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fh = logging.FileHandler(filepath)
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fh.setLevel(logging.DEBUG)
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fh.setFormatter(formatter)
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logger.addHandler(fh)
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else:
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logger.warning("not set file logger")
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return logger
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