# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
"""Input reader builder.

Creates data sources for DetectionModels from an InputReader config. See
input_reader.proto for options.

Note: If users wishes to also use their own InputReaders with the Object
Detection configuration framework, they should define their own builder function
that wraps the build function.
"""

from torch.utils.data import Dataset

from second.builder import dataset_builder
from second.protos import input_reader_pb2


class DatasetWrapper(Dataset):
    """ convert our dataset to Dataset class in pytorch.
    """

    def __init__(self, dataset):
        self._dataset = dataset

    def __len__(self):
        return len(self._dataset)

    def __getitem__(self, idx):
        return self._dataset[idx]

    @property
    def dataset(self):
        return self._dataset


def build(input_reader_config,
          model_config,
          training,
          voxel_generator,
          target_assigner=None,
          ref_dets=None) -> DatasetWrapper:
    """Builds a tensor dictionary based on the InputReader config.

    Args:
        input_reader_config: A input_reader_pb2.InputReader object.

    Returns:
        A tensor dict based on the input_reader_config.

    Raises:
        ValueError: On invalid input reader proto.
        ValueError: If no input paths are specified.
    """
    if not isinstance(input_reader_config, input_reader_pb2.InputReader):
        raise ValueError('input_reader_config not of type '
                         'input_reader_pb2.InputReader.')
    dataset = dataset_builder.build(input_reader_config, model_config,
                                    training, voxel_generator, target_assigner, ref_dets)
    dataset = DatasetWrapper(dataset)
    return dataset
