# coding=utf-8
#
# Copyright 2020 Heinrich Heine University Duesseldorf
#
# 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.
import numpy as np
from torch.utils.data import Dataset

class TensorListDataset(Dataset):
    def __init__(self, *data):
        size = data[0].shape[0]
        # for element in data:
        #     if isinstance(element, dict):
        #         assert all(size == tensor.size(0) for name, tensor in element.items()) # dict of tensors
        #     elif isinstance(element, list):
        #         assert size == len(element) 
        #     else:
        #         assert size == element.size(0) # tensor
        self.size = size
        self.data = data

    def __getitem__(self, index):
        result = []
        for element in self.data:
            if isinstance(element, dict):
                result.append({k: v[index] for k, v in element.items()})
            else:
                result.append(element[index])
        # print(result)
        return tuple(result)

    def __len__(self):
        return self.size
    
# class TensorListDataset(Dataset):
#     r"""Dataset wrapping tensors, tensor dicts and tensor lists.

#     Arguments:
#         *data (Tensor or dict or list of Tensors): tensors that have the same size
#         of the first dimension.
#     """

#     def __init__(self, *data):
#         if isinstance(data[0], dict):
#             size = list(data[0].values())[0].size(0)
#         elif isinstance(data[0], list):
#             size = data[0][0].size(0)
#         else:
#             size = data[0].size(0)
#         for element in data:
#             if isinstance(element, dict):
#                 assert all(size == tensor.size(0) for name, tensor in element.items()) # dict of tensors
#             elif isinstance(element, list):
#                 assert all(size == tensor.size(0) for tensor in element) # list of tensors
#             else:
#                 assert size == element.size(0) # tensor
#         self.size = size
#         self.data = data

#     def __getitem__(self, index):
#         result = []
#         for element in self.data:
#             if isinstance(element, dict):
#                 result.append({k: v[index] for k, v in element.items()})
#             elif isinstance(element, list):
#                 result.append(v[index] for v in element)
#             else:
#                 result.append(element[index])
#         return tuple(result)

#     def __len__(self):
#         return self.size
