# 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
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"""Helper functions to operate on metric values. """

import torch

from pytorch_lightning.utilities.exceptions import MisconfigurationException


def metrics_to_scalars(metrics: dict) -> dict:
    """ Recursively walk through a dictionary of metrics and convert single-item tensors to scalar values. """

    # TODO: this is duplicated in MetricsHolder. should be unified
    new_metrics = {}
    for k, v in metrics.items():
        if isinstance(v, torch.Tensor):
            if v.numel() != 1:
                raise MisconfigurationException(
                    f"The metric `{k}` does not contain a single element"
                    f" thus it cannot be converted to float. Found `{v}`"
                )
            v = v.item()

        if isinstance(v, dict):
            v = metrics_to_scalars(v)

        new_metrics[k] = v

    return new_metrics