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Paddle/python/paddle/fluid/dataloader/dataset.py

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2.4 KiB

# Copyright (c) 2020 PaddlePaddle 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.
from __future__ import print_function
import paddle.dataset.common
__all__ = ["Dataset"]
class Dataset(object):
"""
An abstract class to encapsulates methods and behaviors of datasets.
All datasets in map-style(dataset samples can be get by a given key)
should be a subclass of `paddle.io.Dataset`. All subclasses should
implement following methods:
:code:`__getitem__`: get sample from dataset with a given index. This
method is required by reading dataset sample in :code:`paddle.io.DataLoader`.
:code:`__len__`: return dataset sample number. This method is required
by some implements of :code:`paddle.io.BatchSampler`
see :code:`paddle.io.DataLoader`.
Examples:
.. code-block:: python
import numpy as np
from paddle.io import Dataset
# define a random dataset
class RandomDataset(Dataset):
def __init__(self, num_samples):
self.num_samples = num_samples
def __getitem__(self, idx):
image = np.random.random([784]).astype('float32')
label = np.random.randint(0, 9, (1, )).astype('int64')
return image, label
def __len__(self):
return self.num_samples
dataset = RandomDataset(10)
for i in range(len(dataset)):
print(dataset[i])
"""
def __init__(self):
pass
def __getitem__(self, idx):
raise NotImplementedError("'{}' not implement in class "\
"{}".format('__getitem__', self.__class__.__name__))
def __len__(self):
raise NotImplementedError("'{}' not implement in class "\
"{}".format('__len__', self.__class__.__name__))