我有如下代码：
dataset = MNIST(path=data_path, download=True, shuffle=True)
if train:
images, labels = dataset.get_train()
else:
images, labels = dataset.get_test()
images, labels = images[:n_examples], labels[:n_examples]
images, labels = iter(images.view(-1, 784) / 255), iter(labels)
但是当我运行它时，它给了我这个错误：
Traceback (most recent call last):
File "C:\Users\Ati\Downloads\Compressed\bindsnet_experiments-
master\experiments\mnist\two_layer_backprop.py", line 135, in <module>
images, labels = dataset.get_train()
AttributeError: 'TorchvisionDatasetWrapper' object has no attribute 'get_train'
我认为因为get_train()已过期，torchvision不支持
但是我测试了将mnist数据转换为图像和标签变量的不同方法
谁知道get_train()无效时我该如何更改
如果有人对此提供帮助，我将不胜感激
答案 0 :(得分：1)
是的，看起来类不再存在于软件包中。
我能够找到您要查找的软件包的源代码：
import os
import functools
import operator
import gzip
import struct
import array
import tempfile
try:
from urllib.request import urlretrieve
except ImportError:
from urllib import urlretrieve # py2
try:
from urllib.parse import urljoin
except ImportError:
from urlparse import urljoin
import numpy
__version__ = '0.2.2'
# `datasets_url` and `temporary_dir` can be set by the user using:
# >>> mnist.datasets_url = 'http://my.mnist.url'
# >>> mnist.temporary_dir = lambda: '/tmp/mnist'
datasets_url = 'http://yann.lecun.com/exdb/mnist/'
temporary_dir = tempfile.gettempdir
class IdxDecodeError(ValueError):
"""Raised when an invalid idx file is parsed."""
pass
def download_file(fname, target_dir=None, force=False):
"""Download fname from the datasets_url, and save it to target_dir,
unless the file already exists, and force is False.
Parameters
----------
fname : str
Name of the file to download
target_dir : str
Directory where to store the file
force : bool
Force downloading the file, if it already exists
Returns
-------
fname : str
Full path of the downloaded file
"""
target_dir = target_dir or temporary_dir()
target_fname = os.path.join(target_dir, fname)
if force or not os.path.isfile(target_fname):
url = urljoin(datasets_url, fname)
urlretrieve(url, target_fname)
return target_fname
def parse_idx(fd):
"""Parse an IDX file, and return it as a numpy array.
Parameters
----------
fd : file
File descriptor of the IDX file to parse
endian : str
Byte order of the IDX file. See [1] for available options
Returns
-------
data : numpy.ndarray
Numpy array with the dimensions and the data in the IDX file
1. https://docs.python.org/3/library/struct.html
#byte-order-size-and-alignment
"""
DATA_TYPES = {0x08: 'B', # unsigned byte
0x09: 'b', # signed byte
0x0b: 'h', # short (2 bytes)
0x0c: 'i', # int (4 bytes)
0x0d: 'f', # float (4 bytes)
0x0e: 'd'} # double (8 bytes)
header = fd.read(4)
if len(header) != 4:
raise IdxDecodeError('Invalid IDX file, '
'file empty or does not contain a full header.')
zeros, data_type, num_dimensions = struct.unpack('>HBB', header)
if zeros != 0:
raise IdxDecodeError('Invalid IDX file, '
'file must start with two zero bytes. '
'Found 0x%02x' % zeros)
try:
data_type = DATA_TYPES[data_type]
except KeyError:
raise IdxDecodeError('Unknown data type '
'0x%02x in IDX file' % data_type)
dimension_sizes = struct.unpack('>' + 'I' * num_dimensions,
fd.read(4 * num_dimensions))
data = array.array(data_type, fd.read())
data.byteswap() # looks like array.array reads data as little endian
expected_items = functools.reduce(operator.mul, dimension_sizes)
if len(data) != expected_items:
raise IdxDecodeError('IDX file has wrong number of items. '
'Expected: %d. Found: %d' % (expected_items,
len(data)))
return numpy.array(data).reshape(dimension_sizes)
def download_and_parse_mnist_file(fname, target_dir=None, force=False):
"""Download the IDX file named fname from the URL specified in dataset_url
and return it as a numpy array.
Parameters
----------
fname : str
File name to download and parse
target_dir : str
Directory where to store the file
force : bool
Force downloading the file, if it already exists
Returns
-------
data : numpy.ndarray
Numpy array with the dimensions and the data in the IDX file
"""
fname = download_file(fname, target_dir=target_dir, force=force)
fopen = gzip.open if os.path.splitext(fname)[1] == '.gz' else open
with fopen(fname, 'rb') as fd:
return parse_idx(fd)
def train_images():
"""Return train images from Yann LeCun MNIST database as a numpy array.
Download the file, if not already found in the temporary directory of
the system.
Returns
-------
train_images : numpy.ndarray
Numpy array with the images in the train MNIST database. The first
dimension indexes each sample, while the other two index rows and
columns of the image
"""
return download_and_parse_mnist_file('train-images-idx3-ubyte.gz')
def test_images():
"""Return test images from Yann LeCun MNIST database as a numpy array.
Download the file, if not already found in the temporary directory of
the system.
Returns
-------
test_images : numpy.ndarray
Numpy array with the images in the train MNIST database. The first
dimension indexes each sample, while the other two index rows and
columns of the image
"""
return download_and_parse_mnist_file('t10k-images-idx3-ubyte.gz')
def train_labels():
"""Return train labels from Yann LeCun MNIST database as a numpy array.
Download the file, if not already found in the temporary directory of
the system.
Returns
-------
train_labels : numpy.ndarray
Numpy array with the labels 0 to 9 in the train MNIST database.
"""
return download_and_parse_mnist_file('train-labels-idx1-ubyte.gz')
def test_labels():
"""Return test labels from Yann LeCun MNIST database as a numpy array.
Download the file, if not already found in the temporary directory of
the system.
Returns
-------
test_labels : numpy.ndarray
Numpy array with the labels 0 to 9 in the train MNIST database.
"""
return download_and_parse_mnist_file('t10k-labels-idx1-ubyte.gz')
您可以将其存储在任何文件中，导入该文件并根据需要使用功能（无需创建MNIST对象）。
希望这会有所帮助。祝你好运。
答案 1 :(得分：0)
from mnist import MNIST
dataset = MNIST('./dir_with_mnist_data_files')
images, labels = dataset.load_training()
我认为应该是dataset.load_training而不是dataset.get_train()。
希望这会有所帮助。祝你好运。