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">=1.0.0", markers = "python_version < \"3.11\""} +typing-extensions = "*" + +[package.extras] +test = ["pytest (>=6.2)", "virtualenv (>20)"] +toml = ["setuptools (>=42)"] + [[package]] name = "six" version = "1.16.0" @@ -3117,7 +3572,7 @@ files = [ name = "tomli" version = "2.0.1" description = "A lil' TOML parser" -category = "dev" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -3658,4 +4113,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.12" -content-hash = "3267e1b9d0d46a69cace66bf32bde5cb9c78f7958184b1eae96c1e3a498bf388" +content-hash = "599b69c1ca172c6ef1910dab9e016c7090279ef9ef1555fefa245acbe3cf9c5f" diff --git a/pyproject.toml b/pyproject.toml index ec863023..9c13c09c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -29,6 +29,7 @@ openpyxl = "^3.1.2" pycountry = "^22.3.5" wave = ">=0.0.2,<1.0.0" kenlm = {url = "https://github.com/kpu/kenlm/archive/master.zip"} +matplotlib = "3.7.3" [tool.poetry.group.dev.dependencies] pytest = "^7.0.0" diff --git a/src/coral_models/plot.py b/src/coral_models/plot.py new file mode 100644 index 00000000..f59897e3 --- /dev/null +++ b/src/coral_models/plot.py @@ -0,0 +1,45 @@ +"""Functions related to visualization""" + +from pathlib import Path + +from matplotlib import pyplot as plt +from transformers import TrainerState + +DEFAULT_LOSS_TITLE = "ASR Training loss" + + +def plot_training_loss( + trainer_state: TrainerState, + output_path: Path, + title: str = DEFAULT_LOSS_TITLE, + log_scale: bool = False, +) -> None: + """ + Plot the training loss over steps from a trainer's state. + + Args: + trainer_state (TrainerState): + The state object that holds logs and other training related information. + output_path (Path): + The path where the generated plot should be saved. + title (str, optional): + The title for the plot. Defaults to 'ASR TRAINING loss'. + log_scale (bool, optional): + If set to True, the y-axis will be set to logarithmic scale. + Defaults to False. + """ + x = [log["step"] for log in trainer_state.log_history] + y = [log["loss"] for log in trainer_state.log_history] + + fig, ax = plt.subplots() + if log_scale: + ax.set_yscale("log") + + ax.plot(x, y) + + ax.set_xlabel("Steps") + ax.set_ylabel("Loss") + ax.set_title(title) + ax.grid(True) + + fig.savefig(output_path) diff --git a/src/scripts/plot_training_trajectory.py b/src/scripts/plot_training_trajectory.py new file mode 100644 index 00000000..d8c67652 --- /dev/null +++ b/src/scripts/plot_training_trajectory.py @@ -0,0 +1,47 @@ +"""Reads the saved trainer state of a training checkpoint and plots training loss. + +Usage: + python src/scripts/plot_training_trajectory.py\ + +""" + +import logging +from pathlib import Path + +import click +from transformers import TrainerState +from transformers.trainer import TRAINER_STATE_NAME + +from coral_models.plot import plot_training_loss + +EXTENSION = "png" + +logging.basicConfig(level=logging.INFO, format="%(asctime)s | %(message)s") +logger = logging.getLogger(__name__) + + +@click.command() +@click.argument("checkpoint-dir", type=click.Path(exists=True)) +@click.argument("output-dir", type=click.Path(exists=True)) +@click.option( + "--log-scale", + is_flag=True, + default=False, + show_default=True, + help="Whether to produce the plot with log scaled X axis.", +) +def main(checkpoint_dir: str | Path, output_dir: str | Path, log_scale: bool) -> None: + """Reads the saved trainer state of a training checkpoint and plots training curves. + Currently, only a loss curve, loss.png, is produced to the output dir. + """ + checkpoint_dir = Path(checkpoint_dir) + output_dir = Path(output_dir) + + state = TrainerState.load_from_json(checkpoint_dir / TRAINER_STATE_NAME) + + loss_plot_path = output_dir / f"loss.{EXTENSION}" + plot_training_loss(state, loss_plot_path, log_scale=log_scale) + + +if __name__ == "__main__": + main()