Source code for catalyst.utils.plotly

from typing import Dict, List, Optional, Union  # isort:skip
from collections import defaultdict
from pathlib import Path

import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, iplot

from catalyst.utils.tensorboard import SummaryItem, SummaryReader


def _get_tensorboard_scalars(
    logdir: Union[str, Path], metrics: Optional[List[str]], step: str
) -> Dict[str, List]:
    summary_reader = SummaryReader(logdir, types=["scalar"])

    items = defaultdict(list)
    for item in summary_reader:
        if step in item.tag and (
            metrics is None or any(m in item.tag for m in metrics)
        ):
            items[item.tag].append(item)
    return items


def _get_scatter(scalars: List[SummaryItem], name: str) -> go.Scatter:
    xs = [s.step for s in scalars]
    ys = [s.value for s in scalars]
    return go.Scatter(x=xs, y=ys, name=name)


def plot_tensorboard_log(
    logdir: Union[str, Path],
    step: Optional[str] = "batch",
    metrics: Optional[List[str]] = None,
    height: Optional[int] = None,
    width: Optional[int] = None
) -> None:
    init_notebook_mode()
    logdir = Path(logdir)

    logdirs = {
        x.name.replace("_log", ""): x
        for x in logdir.glob("**/*") if x.is_dir() and str(x).endswith("_log")
    }

    scalars_per_loader = {
        key: _get_tensorboard_scalars(inner_logdir, metrics, step)
        for key, inner_logdir in logdirs.items()
    }

    scalars_per_metric = defaultdict(dict)
    for key, value in scalars_per_loader.items():
        for key2, value2 in value.items():
            scalars_per_metric[key2][key] = value2

    for metric_name, metric_logs in scalars_per_metric.items():
        metric_data = []
        for key, value in metric_logs.items():
            try:
                data_ = _get_scatter(value, f"{key}/{metric_name}")
                metric_data.append(data_)
            except:  # noqa: E722
                pass

        layout = go.Layout(
            title=metric_name,
            height=height,
            width=width,
            yaxis=dict(hoverformat=".5f")
        )
        iplot(go.Figure(data=metric_data, layout=layout))


__all__ = ["plot_tensorboard_log"]