mirror of
https://github.com/explosion/spaCy.git
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104 lines
3.6 KiB
Python
104 lines
3.6 KiB
Python
from typing import Dict, Any, Tuple, Callable, List
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from ..util import registry
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from .. import util
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from ..errors import Errors
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from wasabi import msg
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@registry.loggers("spacy.ConsoleLogger.v1")
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def console_logger():
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def setup_printer(
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nlp: "Language",
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) -> Tuple[Callable[[Dict[str, Any]], None], Callable]:
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# we assume here that only components are enabled that should be trained & logged
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logged_pipes = nlp.pipe_names
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score_weights = nlp.config["training"]["score_weights"]
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score_cols = [col for col, value in score_weights.items() if value is not None]
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score_widths = [max(len(col), 6) for col in score_cols]
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loss_cols = [f"Loss {pipe}" for pipe in logged_pipes]
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loss_widths = [max(len(col), 8) for col in loss_cols]
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table_header = ["E", "#"] + loss_cols + score_cols + ["Score"]
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table_header = [col.upper() for col in table_header]
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table_widths = [3, 6] + loss_widths + score_widths + [6]
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table_aligns = ["r" for _ in table_widths]
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msg.row(table_header, widths=table_widths)
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msg.row(["-" * width for width in table_widths])
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def log_step(info: Dict[str, Any]):
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try:
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losses = [
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"{0:.2f}".format(float(info["losses"][pipe_name]))
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for pipe_name in logged_pipes
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]
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except KeyError as e:
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raise KeyError(
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Errors.E983.format(
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dict="scores (losses)",
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key=str(e),
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keys=list(info["losses"].keys()),
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)
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) from None
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scores = []
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for col in score_cols:
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score = info["other_scores"].get(col, 0.0)
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try:
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score = float(score)
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if col != "speed":
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score *= 100
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scores.append("{0:.2f}".format(score))
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except TypeError:
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err = Errors.E916.format(name=col, score_type=type(score))
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raise ValueError(err) from None
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data = (
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[info["epoch"], info["step"]]
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+ losses
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+ scores
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+ ["{0:.2f}".format(float(info["score"]))]
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)
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msg.row(data, widths=table_widths, aligns=table_aligns)
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def finalize():
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pass
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return log_step, finalize
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return setup_printer
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@registry.loggers("spacy.WandbLogger.v1")
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def wandb_logger(project_name: str, remove_config_values: List[str] = []):
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import wandb
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console = console_logger()
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def setup_logger(
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nlp: "Language",
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) -> Tuple[Callable[[Dict[str, Any]], None], Callable]:
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config = nlp.config.interpolate()
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config_dot = util.dict_to_dot(config)
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for field in remove_config_values:
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del config_dot[field]
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config = util.dot_to_dict(config_dot)
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wandb.init(project=project_name, config=config, reinit=True)
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console_log_step, console_finalize = console(nlp)
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def log_step(info: Dict[str, Any]):
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console_log_step(info)
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score = info["score"]
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other_scores = info["other_scores"]
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losses = info["losses"]
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wandb.log({"score": score})
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if losses:
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wandb.log({f"loss_{k}": v for k, v in losses.items()})
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if isinstance(other_scores, dict):
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wandb.log(other_scores)
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def finalize():
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console_finalize()
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wandb.join()
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return log_step, finalize
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return setup_logger
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