run.py

import os

import dotenv
import hydra
from hydra.core.config_store import ConfigStore
from omegaconf import DictConfig
from rich.traceback import install

# load environment variables from `.env` file if it exists
# recursively searches for `.env` in all folders starting from work dir

dotenv.load_dotenv(override=True, verbose=True)
install(show_locals=False, extra_lines=1, word_wrap=True, width=350)


def collect_config_store():
    from mlproject.configs.config_tree import Config, base_callbacks, wandb_callbacks
    from mlproject.configs.datamodules import (
        InstagramImageTextMultiModalDataModuleConfig,
    )
    from mlproject.configs.hydra import add_hydra_configs
    from mlproject.configs.loggers import (
        TensorboardLoggerConfig,
        WeightsAndBiasesLoggerConfig,
    )
    from mlproject.configs.mode import BaseMode
    from mlproject.configs.models import CLIPImageTextMultiModalDatasetConfig
    from mlproject.configs.optimizers import AdamWOptimizerConfig
    from mlproject.configs.trainers import (
        BaseTrainer,
        DDPTrainer,
        DPTrainer,
        MPSTrainer,
    )

    config_store = ConfigStore.instance()
    ###################################################################################
    config_store.store(name="config", node=Config)
    ###################################################################################
    config_store.store(
        group="callbacks",
        name="base",
        node=base_callbacks,
    )

    config_store.store(
        group="callbacks",
        name="wandb",
        node=wandb_callbacks,
    )
    ###################################################################################
    config_store.store(
        group="logger",
        name="wandb",
        node=dict(wandb_logger=WeightsAndBiasesLoggerConfig()),
    )

    config_store.store(
        group="logger", name="tb", node=dict(logger=TensorboardLoggerConfig())
    )

    config_store.store(
        group="logger",
        name="wandb+tb",
        node=dict(
            tensorboard_logger=TensorboardLoggerConfig(),
            wandb_logger=WeightsAndBiasesLoggerConfig(),
        ),
    )
    ###################################################################################
    config_store.store(
        group="model",
        name="clip-image-text",
        node=CLIPImageTextMultiModalDatasetConfig,
    )
    ###################################################################################
    config_store.store(
        group="datamodule",
        name="InstagramImageTextMultiModal",
        node=InstagramImageTextMultiModalDataModuleConfig,
    )
    ###################################################################################
    config_store.store(group="trainer", name="base", node=BaseTrainer)
    config_store.store(group="trainer", name="gpu-dp", node=DPTrainer)
    config_store.store(group="trainer", name="gpu-ddp", node=DDPTrainer)
    config_store.store(group="trainer", name="mps", node=MPSTrainer)
    ###################################################################################
    config_store = add_hydra_configs(config_store)
    ###################################################################################
    config_store.store(
        group="mode",
        name="base",
        node=BaseMode(),
    )
    ###################################################################################
    config_store.store(group="optimizer", name="AdamW", node=AdamWOptimizerConfig)

    return config_store


config_store = collect_config_store()


@hydra.main(version_base=None, config_name="config")
def main(config: DictConfig):

    # Imports can be nested inside @hydra.main to optimize tab completion
    # https://github.com/facebookresearch/hydra/issues/934
    from mlproject.base import utils
    from mlproject.train_eval import train_eval

    # A couple of optional utilities:
    # - disabling python warnings
    # - forcing debug-friendly configuration
    # - verifying experiment name is set when running in experiment mode
    # You can safely get rid of this line if you don't want those
    utils.extras(config)
    os.environ["WANDB_PROGRAM"] = config.code_dir

    return train_eval(config)


if __name__ == "__main__":
    main()