# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ===========================================================================
"""DSCNN dataset."""
import os
import numpy as np
import mindspore.dataset as de


class NpyDataset():
    '''Dataset from numpy.'''
    def __init__(self, data_dir, data_type, h, w):
        super(NpyDataset, self).__init__()
        self.data = np.load(os.path.join(data_dir, '{}_data.npy'.format(data_type)))
        self.data = np.reshape(self.data, (-1, 1, h, w))
        self.label = np.load(os.path.join(data_dir, '{}_label.npy'.format(data_type)))

    def __len__(self):
        return self.data.shape[0]

    def __getitem__(self, item):
        data = self.data[item]
        label = self.label[item]
        # return data, label
        return data.astype(np.float32), label.astype(np.int32)


def audio_dataset(data_dir, data_type, h, w, batch_size):
    if 'testing' in data_dir:
        shuffle = False
    else:
        shuffle = True
    dataset = NpyDataset(data_dir, data_type, h, w)
    de_dataset = de.GeneratorDataset(dataset, ["feats", "labels"], shuffle=shuffle)
    de_dataset = de_dataset.batch(batch_size, drop_remainder=False)
    return de_dataset