168 lines
6.2 KiB
Python
168 lines
6.2 KiB
Python
from typing import TYPE_CHECKING, Dict, Any, Tuple, Callable, List, Optional, IO, Union
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import sys
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from pathlib import Path
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from spacy import util
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from spacy.errors import Errors
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from spacy.util import registry
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from wasabi import Printer
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import tqdm
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if TYPE_CHECKING:
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from spacy.language import Language # noqa: F401
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def wandb_logger_v1(project_name: str, remove_config_values: List[str] = []):
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try:
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import wandb
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from wandb import init, log, join # test that these are available
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except ImportError:
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err_msg = (
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"The 'wandb' library could not be found - did you install "
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"it? Alternatively, specify the 'ConsoleLogger' in the "
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"'training.logger' config section, instead of the "
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"'WandbLogger'."
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)
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raise ImportError(err_msg)
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console_logger = registry.get("loggers", "spacy.ConsoleLogger.v1")
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console = console_logger(progress_bar=False)
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def setup_logger(
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nlp: "Language", stdout: IO = sys.stdout, stderr: IO = sys.stderr
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) -> Tuple[Callable[[Dict[str, Any]], None], Callable[[], None]]:
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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, stdout, stderr)
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def log_step(info: Optional[Dict[str, Any]]):
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console_log_step(info)
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if info is not None:
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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() -> None:
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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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def setup_table(
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*, cols: List[str], widths: List[int], max_width: int = 13
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) -> Tuple[List[str], List[int], List[str]]:
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final_cols = []
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final_widths = []
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for col, width in zip(cols, widths):
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if len(col) > max_width:
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col = col[: max_width - 3] + "..." # shorten column if too long
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final_cols.append(col.upper())
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final_widths.append(max(len(col), width))
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return final_cols, final_widths, ["r" for _ in final_widths]
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def console_logger_v2(
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progress_bar: bool = False,
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console_output: bool = True,
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output_file: Optional[Union[str, Path]] = None,
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):
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"""The ConsoleLogger.v2 prints out training logs in the console and/or saves them to a jsonl file.
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progress_bar (bool): Whether the logger should print a progress bar tracking the steps till the next evaluation pass.
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console_output (bool): Whether the logger should print the logs on the console.
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output_file (Optional[Union[str, Path]]): The file to save the training logs to.
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"""
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console_logger = registry.get("loggers", "spacy.ConsoleLogger.v3")
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return console_logger(
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progress_bar=None if progress_bar is False else "eval",
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console_output=console_output,
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output_file=output_file,
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)
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def console_logger_v1(progress_bar: bool = False):
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def setup_printer(
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nlp: "Language", stdout: IO = sys.stdout, stderr: IO = sys.stderr
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) -> Tuple[Callable[[Optional[Dict[str, Any]]], None], Callable[[], None]]:
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write = lambda text: print(text, file=stdout, flush=True)
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msg = Printer(no_print=True)
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# ensure that only trainable components are logged
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logged_pipes = [
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name
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for name, proc in nlp.pipeline
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if hasattr(proc, "is_trainable") and proc.is_trainable
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]
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eval_frequency = nlp.config["training"]["eval_frequency"]
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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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loss_cols = [f"Loss {pipe}" for pipe in logged_pipes]
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spacing = 2
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table_header, table_widths, table_aligns = setup_table(
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cols=["E", "#"] + loss_cols + score_cols + ["Score"],
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widths=[3, 6] + [8 for _ in loss_cols] + [6 for _ in score_cols] + [6],
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)
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write(msg.row(table_header, widths=table_widths, spacing=spacing))
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write(msg.row(["-" * width for width in table_widths], spacing=spacing))
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progress = None
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def log_step(info: Optional[Dict[str, Any]]) -> None:
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nonlocal progress
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if info is None:
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# If we don't have a new checkpoint, just return.
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if progress is not None:
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progress.update(1)
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return
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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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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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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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if col != "speed":
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score *= 100
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scores.append("{0:.2f}".format(score))
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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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if progress is not None:
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progress.close()
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write(
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msg.row(data, widths=table_widths, aligns=table_aligns, spacing=spacing)
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)
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if progress_bar:
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# Set disable=None, so that it disables on non-TTY
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progress = tqdm.tqdm(
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total=eval_frequency, disable=None, leave=False, file=stderr
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)
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progress.set_description(f"Epoch {info['epoch']+1}")
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def finalize() -> None:
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pass
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return log_step, finalize
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return setup_printer
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