# YOLOv5 by Ultralytics, GPL-3.0 license
"""
Callback utils
"""


class Callbacks:
    """ "
    Handles all registered callbacks for YOLOv5 Hooks
    """

    _callbacks = {
        "on_pretrain_routine_start": [],
        "on_pretrain_routine_end": [],
        "on_train_start": [],
        "on_train_epoch_start": [],
        "on_train_batch_start": [],
        "optimizer_step": [],
        "on_before_zero_grad": [],
        "on_train_batch_end": [],
        "on_train_epoch_end": [],
        "on_val_start": [],
        "on_val_batch_start": [],
        "on_val_image_end": [],
        "on_val_batch_end": [],
        "on_val_end": [],
        "on_fit_epoch_end": [],  # fit = train + val
        "on_model_save": [],
        "on_train_end": [],
        "teardown": [],
    }

    def __init__(self):
        return

    def register_action(self, hook, name="", callback=None):
        """
        Register a new action to a callback hook

        Args:
            hook        The callback hook name to register the action to
            name        The name of the action
            callback    The callback to fire
        """
        assert hook in self._callbacks, f"hook '{hook}' not found in callbacks {self._callbacks}"
        assert callable(callback), f"callback '{callback}' is not callable"
        self._callbacks[hook].append({"name": name, "callback": callback})

    def get_registered_actions(self, hook=None):
        """ "
        Returns all the registered actions by callback hook

        Args:
            hook The name of the hook to check, defaults to all
        """
        if hook:
            return self._callbacks[hook]
        else:
            return self._callbacks

    def run_callbacks(self, hook, *args, **kwargs):
        """
        Loop through the registered actions and fire all callbacks
        """
        for logger in self._callbacks[hook]:
            # print(f"Running callbacks.{logger['callback'].__name__}()")
            logger["callback"](*args, **kwargs)

    def on_pretrain_routine_start(self, *args, **kwargs):
        """
        Fires all registered callbacks at the start of each pretraining routine
        """
        self.run_callbacks("on_pretrain_routine_start", *args, **kwargs)

    def on_pretrain_routine_end(self, *args, **kwargs):
        """
        Fires all registered callbacks at the end of each pretraining routine
        """
        self.run_callbacks("on_pretrain_routine_end", *args, **kwargs)

    def on_train_start(self, *args, **kwargs):
        """
        Fires all registered callbacks at the start of each training
        """
        self.run_callbacks("on_train_start", *args, **kwargs)

    def on_train_epoch_start(self, *args, **kwargs):
        """
        Fires all registered callbacks at the start of each training epoch
        """
        self.run_callbacks("on_train_epoch_start", *args, **kwargs)

    def on_train_batch_start(self, *args, **kwargs):
        """
        Fires all registered callbacks at the start of each training batch
        """
        self.run_callbacks("on_train_batch_start", *args, **kwargs)

    def optimizer_step(self, *args, **kwargs):
        """
        Fires all registered callbacks on each optimizer step
        """
        self.run_callbacks("optimizer_step", *args, **kwargs)

    def on_before_zero_grad(self, *args, **kwargs):
        """
        Fires all registered callbacks before zero grad
        """
        self.run_callbacks("on_before_zero_grad", *args, **kwargs)

    def on_train_batch_end(self, *args, **kwargs):
        """
        Fires all registered callbacks at the end of each training batch
        """
        self.run_callbacks("on_train_batch_end", *args, **kwargs)

    def on_train_epoch_end(self, *args, **kwargs):
        """
        Fires all registered callbacks at the end of each training epoch
        """
        self.run_callbacks("on_train_epoch_end", *args, **kwargs)

    def on_val_start(self, *args, **kwargs):
        """
        Fires all registered callbacks at the start of the validation
        """
        self.run_callbacks("on_val_start", *args, **kwargs)

    def on_val_batch_start(self, *args, **kwargs):
        """
        Fires all registered callbacks at the start of each validation batch
        """
        self.run_callbacks("on_val_batch_start", *args, **kwargs)

    def on_val_image_end(self, *args, **kwargs):
        """
        Fires all registered callbacks at the end of each val image
        """
        self.run_callbacks("on_val_image_end", *args, **kwargs)

    def on_val_batch_end(self, *args, **kwargs):
        """
        Fires all registered callbacks at the end of each validation batch
        """
        self.run_callbacks("on_val_batch_end", *args, **kwargs)

    def on_val_end(self, *args, **kwargs):
        """
        Fires all registered callbacks at the end of the validation
        """
        self.run_callbacks("on_val_end", *args, **kwargs)

    def on_fit_epoch_end(self, *args, **kwargs):
        """
        Fires all registered callbacks at the end of each fit (train+val) epoch
        """
        self.run_callbacks("on_fit_epoch_end", *args, **kwargs)

    def on_model_save(self, *args, **kwargs):
        """
        Fires all registered callbacks after each model save
        """
        self.run_callbacks("on_model_save", *args, **kwargs)

    def on_train_end(self, *args, **kwargs):
        """
        Fires all registered callbacks at the end of training
        """
        self.run_callbacks("on_train_end", *args, **kwargs)

    def teardown(self, *args, **kwargs):
        """
        Fires all registered callbacks before teardown
        """
        self.run_callbacks("teardown", *args, **kwargs)
