我知道之前曾有人问过这个问题,但我似乎无法让我工作。有人可以帮我吗?
import numpy as np
def load_dataset():
def download(filename, source="http://yaan.lecun.com/exdb/mnist/"):
print ("Downloading ",filename)
import urllib
urllib.urlretrieve(source+filename,filename)
import gzip
def load_mnist_images(filename):
if not os.path.exists(filename):
download(filename)
with gzip.open(filename,"rb") as f:
data=np.frombuffer(f.read(), np.uint8, offset=16)
data = data.reshape(-1,1,28,28)
return data/np.float32(256)
def load_mnist_labels(filename):
if not os.path.exists(filename):
download(filename)
with gzip.open(filename,"rb") as f:
data = np.frombuffer(f.read(), np.uint8, offset=8)
return data
X_train = load_mnist_images("train-images-idx3-ubyte.gz")
y_train = load_mnist_labels("train-labels-idx1-ubyte.gz")
X_test = load_mnist_images("t10k-images-idx3-ubyte.gz")
y_test = load_mnist_labels("t10k-labels-idx1-ubyte.gz")
return X_train, y_train, X_test, y_test
X_train, y_train, X_test, y_test = load_dataset()
import matplotlib
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
plt.show(plt.imshow(X_train[3][0]))
这是我得到的错误:
Traceback (most recent call last):
File "C:\Users\nehad\Desktop\Neha\Non-School\Python\Handwritten Digits
Recognition.py", line 38, in <module>
X_train, y_train, X_test, y_test = load_dataset()
TypeError: cannot unpack non-iterable NoneType object
我是机器学习的新手。我只是想念一些简单的事情吗?我正在为我的学校科学展览尝试“手写数字识别”项目。
谢谢!
答案 0 :(得分:8)
对None
(属于NoneType
)执行多重分配时,会出现此错误。例如:
X_train, y_train, X_test, y_test = None
TypeError:无法解包不可迭代的NoneType对象
因此,如果您得到此提示,则错误很可能是作业的右侧部分与您期望的不一样(没什么)。
答案 1 :(得分:1)
将多个分配拆分/中断为 None 可解决此问题。
例如这不起作用:
test_set_raw, test_set_transformed, train_set_raw, train_set_transformed = None
这确实有效(没有错误):
test_set_raw = None
test_set_transformed = None
train_set_raw = None
train_set_transformed = None
答案 2 :(得分:0)
我认为您的X_train, y_train, X_test, y_test
是在load_mnist_images
函数中定义的,因此没有为您的load_dataset
函数定义。
您应该从X_train = ...
到return X_train, ...
缩进5行,然后您的代码可能会更好。
答案 3 :(得分:-1)
因为load_dataset()返回None。
运行此命令,您将得到相同的错误: X_train,y_train,X_test,y_test =无