from abc import ABC
from typing import Callable, List

from pytorch_lightning.callbacks import Callback


class TrainerCallbackHookMixin(ABC):

    # this is just a summary on variables used in this abstract class,
    # the proper values/initialisation should be done in child class
    callbacks: List[Callback] = []
    get_model: Callable = ...

    def on_init_start(self):
        """Called when the trainer initialization begins, model has not yet been set."""
        for callback in self.callbacks:
            callback.on_init_start(self)

    def on_init_end(self):
        """Called when the trainer initialization ends, model has not yet been set."""
        for callback in self.callbacks:
            callback.on_init_end(self)

    def on_fit_start(self):
        """Called when the trainer initialization begins, model has not yet been set."""
        for callback in self.callbacks:
            callback.on_fit_start(self)

    def on_fit_end(self):
        """Called when the trainer initialization begins, model has not yet been set."""
        for callback in self.callbacks:
            callback.on_fit_end(self)

    def on_sanity_check_start(self):
        """Called when the validation sanity check starts."""
        for callback in self.callbacks:
            callback.on_sanity_check_start(self, self.get_model())

    def on_sanity_check_end(self):
        """Called when the validation sanity check ends."""
        for callback in self.callbacks:
            callback.on_sanity_check_end(self, self.get_model())

    def on_epoch_start(self):
        """Called when the epoch begins."""
        for callback in self.callbacks:
            callback.on_epoch_start(self, self.get_model())

    def on_epoch_end(self):
        """Called when the epoch ends."""
        for callback in self.callbacks:
            callback.on_epoch_end(self, self.get_model())

    def on_train_start(self):
        """Called when the train begins."""
        for callback in self.callbacks:
            callback.on_train_start(self, self.get_model())

    def on_train_end(self):
        """Called when the train ends."""
        for callback in self.callbacks:
            callback.on_train_end(self, self.get_model())

    def on_batch_start(self):
        """Called when the training batch begins."""
        for callback in self.callbacks:
            callback.on_batch_start(self, self.get_model())

    def on_batch_end(self):
        """Called when the training batch ends."""
        for callback in self.callbacks:
            callback.on_batch_end(self, self.get_model())

    def on_validation_batch_start(self):
        """Called when the validation batch begins."""
        for callback in self.callbacks:
            callback.on_validation_batch_start(self, self.get_model())

    def on_validation_batch_end(self):
        """Called when the validation batch ends."""
        for callback in self.callbacks:
            callback.on_validation_batch_end(self, self.get_model())

    def on_test_batch_start(self):
        """Called when the test batch begins."""
        for callback in self.callbacks:
            callback.on_test_batch_start(self, self.get_model())

    def on_test_batch_end(self):
        """Called when the test batch ends."""
        for callback in self.callbacks:
            callback.on_test_batch_end(self, self.get_model())

    def on_validation_start(self):
        """Called when the validation loop begins."""
        for callback in self.callbacks:
            callback.on_validation_start(self, self.get_model())

    def on_validation_end(self):
        """Called when the validation loop ends."""
        for callback in self.callbacks:
            callback.on_validation_end(self, self.get_model())

    def on_test_start(self):
        """Called when the test begins."""
        for callback in self.callbacks:
            callback.on_test_start(self, self.get_model())

    def on_test_end(self):
        """Called when the test ends."""
        for callback in self.callbacks:
            callback.on_test_end(self, self.get_model())

    def on_keyboard_interrupt(self):
        """Called when the training is interrupted by KeyboardInterrupt."""
        for callback in self.callbacks:
            callback.on_keyboard_interrupt(self, self.get_model())