小编Blu*_*482的帖子

我有一个数据框（df）（通常来自excel文件），前9行是这样的：

      Control      Recd_Date/Due_Date                Action        Signature/Requester
0     2000-1703   2000-01-31 00:00:00           OC/OER/OPA/PMS/                 M WEBB
1           NaN   2000-02-29 00:00:00                       NaN              DATA CORP
2     2000-1776   2000-01-02 00:00:00            OC/ORA/OE/DCP/                  G KAN
3           NaN   2000-01-03 00:00:00           OC/ORA/ORO/PNC/              PALM POST
4           NaN                   NaN  FDA/OGROP/ORA/SE-FO/FLA-                    NaN
5           NaN                   NaN                DO/FLA-CB/                    NaN
6     2000-1983   2000-02-02 00:00:00  FDA/OGROP/ORA/CE-FO/CHI-                 M EGAN
7           NaN   2000-02-03 00:00:00                DO/CHI-CB/   BERNSTEIN LIEBHARD &
8           NaN                   NaN                       NaN             LONDON LLP

• Type（df ['Control'] [1]）= float;
• 类型（df ['Recd_Date / Due_Date'] [1]）= datetime.datetime;
• type（df ['Action_Office'] [1]）= float;
• 类型（df ['Signature …

我已经在 tensorflow v2.0 和 v1.12.0（带有tf.enable_eager_execution()）上尝试过这个。显然，如果我numpy()在我的main()函数中使用下面显示的代码片段进行调用，它就可以完美运行。但是，如果我在我的 estimator 模型函数 ie 中使用它，model_fn(features, labels, mode, params)那么它会抱怨'Tensor' object has no attribute 'numpy'.

ndarray = np.ones([3, 3])
tensor = tf.multiply(ndarray, 42)
print(tensor)
print(tensor.numpy())

有没有其他人遇到过类似的问题？对于 tf.estimator 来说似乎是个大问题，不是吗？

我有许多可变长度的二维序列，即列表列表，其中每个子列表都是一个序列。我想在 3d 可视化中投影这些序列/行/子列表，将时间步长作为另一个维度。到目前为止，我未能使用plotly.express.

import plotly.express as px

t = [[ii+1 for ii in range(len(features[i]))] for i in range(len(labels))]
x0 = [[x[0] for x in features[i]] for i in range(len(labels))]
x1 = [[x[1] for x in features[i]] for i in range(len(labels))]

df = pd.DataFrame(dict(
    X=[tii for ti in t for tii in ti],
    Y=[xii for xi in x0 for xii in xi],
    Z=[xii for xi in x1 for xii in xi],
    color=[aa for a in labels for aa in …

我尝试在nltk中使用stanford pos tagger,但它给出了我的错误:

from nltk.tag.stanford import POSTagger
st = POSTagger('/.../models/english-bidirectional-distsim.tagger', '/.../stanford-postagger-full-2014-10-26/stanford-postagger.jar')
st.tag("dogs and cats".split())

线程"main"中的异常java.lang.UnsupportedClassVersionError:edu/stanford/nlp/tagger/maxent/MaxentTagger:java.lang.ClassLoader.defineClass中java.lang.ClassLoader.defineClass1(Native Method)中不支持的major.minor版本52.0 (ClassLoader.java:800)位于java.net.URLClassLoader.defineClass(URLClassLoader.java:449)的java.security.ClassLoader.defineClass(SecureClassLoader.java:142)java.net.URLClassLoader.access $ 100(URLClassLoader.java) :71)java.net.URLClassLoader $ 1.run(URLClassLoader.java:361)java.net.URLClassLoader $ 1.run(URLClassLoader.java:355)java.security.AccessController.doPrivileged(Native Method)at java. net.URLClassLoader.findClass(URLClassLoader.java:354)at java.lang.ClassLoader.loadClass(ClassLoader.java:425)at sun.misc.Launcher $ AppClassLoader.loadClass(Launcher.java:308)at java.lang.ClassLoader .loadClass(ClassLoader.java:358)at sun.launcher.LauncherHelper.checkAndLoadMain(LauncherHelper.java:482)

-------------------------------------------------- ------------------------- OSError Traceback(最近一次调用最后一次)在()----> 1 st.tag("爱自己") .分裂())

/Users/bowang/anaconda/lib/python2.7/site-packages/nltk/tag/stanford.pyc in tag(self,tokens)57 58 def tag(self,tokens):---> 59 return self.tag_sents ([tokens])[0] 60 61 def tag_sents(self,sentences):

/Users/bowang/anaconda/lib/python2.7/site-packages/nltk/tag/stanford.pyc in tag_sents(self,sentences)79#运行标记器并获取输出80 stanpos_output,_stderr = java(self._cmd ,classpath = self._stanford_jar,---> 81 stdout = PIPE,stderr = PIPE)82 stanpos_output = stanpos_output.decode(encoding)83

/Users/bowang/anaconda/lib/python2.7/site-packages/nltk/ 初始化 pyc文件在Java(CMD,类路径,STDIN,STDOUT,标准错误,阻断)158如果p.returncode = 0:159打印(错误.decode(sys.stdout.encoding)) - > …