<gh_stars>0
import json
from typing import Union

from torch.utils.tensorboard import SummaryWriter

from emmental.logging.log_writer import LogWriter
from emmental.meta import Meta


class TensorBoardWriter(LogWriter):
    r"""A class for logging to Tensorboard during training process."""

    def __init__(self) -> None:
        super().__init__()

        # Set up tensorboard summary writer
        self.writer = SummaryWriter(Meta.log_path)

    def add_scalar(
        self, name: str, value: Union[float, int], step: Union[float, int]
    ) -> None:
        r"""Log a scalar variable.

        Args:
          name(str): The name of the scalar.
          value(float or int): The value of the scalar.
          step(float or int): The current step.

        """

        self.writer.add_scalar(name, value, step)

    def write_config(self, config_filename: str = "config.yaml") -> None:
        r"""Dump the config to file.

        Args:
          config_filename(str, optional): The config filename,
            defaults to "config.yaml".

        """

        config = json.dumps(Meta.config)
        self.writer.add_text(tag="config", text_string=config)

        super().write_config(config_filename)

    def close(self) -> None:
        r"""Close the tensorboard writer."""

        self.writer.close()

import json
from typing import Union

from torch.utils.tensorboard import SummaryWriter

from emmental.logging.log_writer import LogWriter
from emmental.meta import Meta


class TensorBoardWriter(LogWriter):
    r"""A class for logging to Tensorboard during training process."""

    def __init__(self) -> None:
        super().__init__()

        # Set up tensorboard summary writer
        self.writer = SummaryWriter(Meta.log_path)

    def add_scalar(
        self, name: str, value: Union[float, int], step: Union[float, int]
    ) -> None:
        r"""Log a scalar variable.

        Args:
          name(str): The name of the scalar.
          value(float or int): The value of the scalar.
          step(float or int): The current step.

        """

        self.writer.add_scalar(name, value, step)

    def write_config(self, config_filename: str = "config.yaml") -> None:
        r"""Dump the config to file.

        Args:
          config_filename(str, optional): The config filename,
            defaults to "config.yaml".

        """

        config = json.dumps(Meta.config)
        self.writer.add_text(tag="config", text_string=config)

        super().write_config(config_filename)

    def close(self) -> None:
        r"""Close the tensorboard writer."""

        self.writer.close()
A class for logging to Tensorboard during training process. # Set up tensorboard summary writer Log a scalar variable.          Args:           name(str): The name of the scalar.           value(float or int): The value of the scalar.           step(float or int): The current step. Dump the config to file.          Args:           config_filename(str, optional): The config filename,             defaults to "config.yaml". Close the tensorboard writer.