blocks|key|4490325|text|强制zip()求值。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4490326|foo+=+list(zip(...))|code-block|syntax|javascript|4490327|entityMap^0|2|5|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|P|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|D|@]|E|$]]]|L|$]]

Force the <code>zip()</code> to evaluate.

<pre><code>foo = list(zip(...))
</code></pre>

blocks|key|4491329|text|现在回答有点晚了，但以防其他人偶然发现:对于相同的神经网络示例教程，我不得不用一个列表(+zip+(...))包装mnist_loader中的3个zip调用。构造：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4491330|training_data+=+list(zip(training_inputs,+training_results))
(...)
validation_data+=+list(zip(validation_inputs,+va_d[1]))
(...)
test_data+=+list(zip(test_inputs,+te_d[1]))|code-block|syntax|javascript|4491331|然后它成功了。|4491332|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

A bit late now to answer, but in case anyone else stumbles on it: for that same neural net example tutorial, it turned out I had to wrap the 3 zip calls in the mnist_loader with a list(zip(...)) construct:

<pre><code>training_data = list(zip(training_inputs, training_results))
(...)
validation_data = list(zip(validation_inputs, va_d[1]))
(...)
test_data = list(zip(test_inputs, te_d[1]))
</code></pre>

And then it worked.

blocks|key|4491364|text|一些信息|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4491365|这是因为在Python3.x中，zip返回一个生成器对象。这个对象不是一个列表(它更好)，但它的行为像一个列表。您可以尝试像这样遍历它：|offset|length|style|CODE|4491366|for+i+in+zip([1,2,3,4],+['a','b','c','d']):
++++print+i|code-block|syntax|javascript|4491367|快速回答|4491368|请向我们展示错误发生位置周围的代码。但是我想我仍然可以给你一个快速的(不一定是好的)解决方案。|4491369|转动这个|4491370|for+i+in+reversed(range(1,+len(x))):|4491371|如下所示：|4491372|for+i+in+reversed(range(1,+len(list(x))):|4491373|entityMap^0|0|G|3|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|10|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|11|8|@$D|12|E|13|F|G]]|9|@]|A|$]]|$1|H|3|I|5|J|7|14|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|15|8|@]|9|@]|A|$]]|$1|O|3|P|5|6|7|16|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|17|8|@]|9|@]|A|$]]|$1|S|3|T|5|J|7|18|8|@]|9|@]|A|$K|L]]|$1|U|3|V|5|6|7|19|8|@]|9|@]|A|$]]|$1|W|3|X|5|J|7|1A|8|@]|9|@]|A|$K|L]]|$1|Y|3|-4|5|6|7|1B|8|@]|9|@]|A|$]]]|Z|$]]

<h1>Some Info</h1>

This is because in the Python 3.x, <code>zip</code> returns a generator object. This object is not a list (it's better) but it behaves like one. You can try iterating through it like this:

<pre><code>for i in zip([1,2,3,4], ['a','b','c','d']):
 print i
</code></pre>

<h1>The Quick Answer</h1>

Please show us the code surrounding where the error happened.
But I think I can still give you a quick (and not necessarily good) solution.

turn this

<pre><code>for i in reversed(range(1, len(x))):
</code></pre>

into this:

<pre><code>for i in reversed(range(1, len(list(x))):
</code></pre>

blocks|key|4490415|text|在mnist_loader中，压缩结果包含如下所示的list()结构|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4490416|def+load_data_wrapper():++++
++++tr_d,+va_d,+te_d+=+load_data()
++++training_inputs+=+[np.reshape(x,+(784,1))+for+x+in+tr_d[0]]
++++training_results+=+[vectorized_result(y)+for+y+in+tr_d[1]]
++++training_data+=+list(zip(training_inputs,+training_results))
++++validation_inputs+=+[np.reshape(x,(784,+1))for+x+in+va_d[0]]
++++validation_data+=+list(zip(validation_inputs,+va_d[1]))
++++test_inputs+=+[np.reshape(x,+(784,+1))+for+x+in+te_d[0]]
++++test_data+=+list(zip(test_inputs,+te_d[1]))
++++return(training_data,+validation_data,+test_data)|code-block|syntax|javascript|4490417|entityMap^0|Q|6|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|P|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|D|@]|E|$]]]|L|$]]

In mnist_loader wrap your zip results in <code>list()</code> constructs like below

<pre><code>def load_data_wrapper(): 
 tr_d, va_d, te_d = load_data()
 training_inputs = [np.reshape(x, (784,1)) for x in tr_d[0]]
 training_results = [vectorized_result(y) for y in tr_d[1]]
 training_data = list(zip(training_inputs, training_results))
 validation_inputs = [np.reshape(x,(784, 1))for x in va_d[0]]
 validation_data = list(zip(validation_inputs, va_d[1]))
 test_inputs = [np.reshape(x, (784, 1)) for x in te_d[0]]
 test_data = list(zip(test_inputs, te_d[1]))
 return(training_data, validation_data, test_data)
</code></pre>

I'm following a tutorial on neural nets<a href="http://neuralnetworksanddeeplearning.com/chap1.html" rel="noreferrer">1</a>
It's in Python 2.7. I'm using 3.4. This is the line that troubles me:
<code>if test_data: n_test = len(test_data)</code>
I get: <code>TypeError: object of type 'zip' has no len()</code>.
Is there a way to rewrite it so that it works in 3.4?

Python 2 --> 3: object of type 'zip' has no len()

我正在学习一个关于神经网络的教程它在Python2.7中。我用的是3.4。这是让我困扰的一句话：if test_data: n_test = len(test_data)我明白了：TypeError: object of type 'zip' has no len()。有没有办法重写它，让它在3.4中工作？

问Python 2 --> 3：'zip‘类型的对象没有len()
EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问Python 2 --> 3：'zip‘类型的对象没有len()EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问Python 2 --> 3：'zip‘类型的对象没有len()
EN