Source code for mxnet.gluon.data.dataset
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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.
# coding: utf-8
# pylint: disable=
"""Dataset container."""
__all__ = ['Dataset', 'ArrayDataset', 'RecordFileDataset']
import os
from ... import recordio, ndarray
[docs]class Dataset(object):
"""Abstract dataset class. All datasets should have this interface.
Subclasses need to override `__getitem__`, which returns the i-th
element, and `__len__`, which returns the total number elements.
.. note:: An mxnet or numpy array can be directly used as a dataset.
"""
def __getitem__(self, idx):
raise NotImplementedError
def __len__(self):
raise NotImplementedError
[docs]class ArrayDataset(Dataset):
"""A dataset of multiple arrays.
The i-th sample is `(x1[i], x2[i], ...)`.
Parameters
----------
*args : one or more arrays
The data arrays.
"""
def __init__(self, *args):
assert len(args) > 0, "Needs at least 1 arrays"
self._length = len(args[0])
self._data = []
for i, data in enumerate(args):
assert len(data) == self._length, \
"All arrays must have the same length. But the first has %s " \
"while the %d-th has %d."%(length, i+1, len(data))
if isinstance(data, ndarray.NDArray) and len(data.shape) == 1:
data = data.asnumpy()
self._data.append(data)
def __getitem__(self, idx):
if len(self._data) == 1:
return self._data[0][idx]
else:
return tuple(data[idx] for data in self._data)
def __len__(self):
return self._length
[docs]class RecordFileDataset(Dataset):
"""A dataset wrapping over a RecordIO (.rec) file.
Each sample is a string representing the raw content of an record.
Parameters
----------
filename : str
Path to rec file.
"""
def __init__(self, filename):
idx_file = os.path.splitext(filename)[0] + '.idx'
self._record = recordio.MXIndexedRecordIO(idx_file, filename, 'r')
def __getitem__(self, idx):
return self._record.read_idx(self._record.keys[idx])
def __len__(self):
return len(self._record.keys)