# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Any, Optional, Union

from torch import Tensor
from torch.nn import Module
from torch.optim import Optimizer

import pytorch_lightning as pl
from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin
from pytorch_lightning.utilities import GradClipAlgorithmType
from pytorch_lightning.utilities.exceptions import MisconfigurationException


class IPUPrecisionPlugin(PrecisionPlugin):

    def __init__(self, precision: int) -> None:
        super().__init__()
        self.precision = precision

    def backward(
        self,
        model: 'pl.LightningModule',
        closure_loss: Tensor,
        optimizer: Optimizer,
        opt_idx: int,
        should_accumulate: bool,
        *args: Any,
        **kwargs: Any,
    ) -> Tensor:
        # IPU internally manages bwd step.
        return closure_loss

    def clip_gradients(
        self,
        optimizer: Optimizer,
        clip_val: Union[int, float],
        gradient_clip_algorithm: GradClipAlgorithmType = GradClipAlgorithmType.NORM,
        model: Optional[Module] = None
    ) -> None:
        """Clips the gradients"""
        if clip_val is None:
            return

        clip_val = float(clip_val)
        if clip_val <= 0:
            return

        raise MisconfigurationException("IPUs currently do not support clipping gradients.")
