Chaquopy中不能导入64位Python训练的机器学习模型(32bit与64bit不兼容)

Chaquopy中不能导入64位Python训练的机器学习模型(32bit与64bit不兼容),第1张

概述  我在Chaquopy中利用joblib来load一个在pycharm中写好的AdaBoost模型:fromjoblibimportdump,loadfilename=join(dirname(__file__),'gao1_to_gao2_1.pkl')clf=load(filename)  报错如下:E/AndroidRuntime:FATALEXCEPTION:mainProcess:com.example

  我在Chaquopy中利用joblib来load一个在pycharm中写好的AdaBoost模型:

from joblib import dump, loadfilename = join(dirname(__file__), 'gao1_to_gao2_1.pkl')clf = load(filename)

  报错如下:

E/AndroIDRuntime: FATAL EXCEPTION: main    Process: com.example.NCEPU, PID: 18024    com.chaquo.python.PyException: ValueError: Buffer dtype mismatch, expected 'SIZE_t' but got 'long long'        at <python>.sklearn.tree._tree.Tree.__cinit__(_tree.pyx:607)        at <python>.pickle.load_reduce(pickle.py:1587)        at <python>.pickle.load(pickle.py:1210)        at <python>.joblib.numpy_pickle._unpickle(numpy_pickle.py:504)        at <python>.joblib.numpy_pickle.load(numpy_pickle.py:585)        at <python>.AdaBoost.test(AdaBoost.py:76)        at <python>.chaquopy_java.call(chaquopy_java.pyx:380)        at <python>.chaquopy_java.Java_com_chaquo_python_PyObject_callAttrThrowsNative(chaquopy_java.pyx:352)        at com.chaquo.python.PyObject.callAttrThrowsNative(Native Method)        at com.chaquo.python.PyObject.callAttrThrows(PyObject.java:232)        at com.chaquo.python.PyObject.callAttr(PyObject.java:221)        at com.example.NCEPU.Student.Predict.AdaBoostActivity.callPythonCode(AdaBoostActivity.java:45)        at com.example.NCEPU.Student.Predict.AdaBoostActivity.createList(AdaBoostActivity.java:61)        at com.example.NCEPU.Student.Predict.AdaBoostActivity.lambda$initVIEws$AdaBoostActivity(AdaBoostActivity.java:56)        at com.example.NCEPU.Student.Predict.-$$Lambda$AdaBoostActivity$dJAvP4dDDrPleKcJgBCESW0ea0M.onClick(UnkNown Source:2)        at androID.vIEw.VIEw.performClick(VIEw.java:7192)        at androID.vIEw.VIEw.performClickInternal(VIEw.java:7166)        at androID.vIEw.VIEw.access00(VIEw.java:824)        at androID.vIEw.VIEw$PerformClick.run(VIEw.java:27592)        at androID.os.Handler.handleCallback(Handler.java:888)        at androID.os.Handler.dispatchMessage(Handler.java:100)        at androID.os.Looper.loop(Looper.java:213)        at androID.app.ActivityThread.main(ActivityThread.java:8169)        at java.lang.reflect.Method.invoke(Native Method)        at com.androID.internal.os.RuntimeInit$MethodAndArgsCaller.run(RuntimeInit.java:513)        at com.androID.internal.os.ZygoteInit.main(ZygoteInit.java:1101)

  翻遍stackoverflow发现是因为32位Python不能导入64位训练的模型,于是在Chaquopy中输出一下:

import platformprint(platform.architecture())

输出为:

('32bit', 'windowsPE')

  果然,Chaquopy中Python默认是32位。那没办法,只能用32位Python训练模型然后再导入了。

1.安装32位python

  在官网下载32位的python38,然后安装,这个不再叙述。
  安装后在Pycharm上配置:


  这个时候在pycharm上打印:

import platformprint(platform.architecture())

  输出为:

('32bit', 'windowsPE')

  可以看到当前版本已经是32位了

2.安装skleanr和pandas

  直接在pycharm的Terminal中安装:

pip install sklearn -i https://pypi.douban.com/simplepip install pandas -i https://pypi.douban.com/simple

  安装过程有极大概率会报错,这中间省略了很多细节。。。。因为问题实在太多了,忘记记录了。不过最后是升级了一下pip就OK了。

3.训练模型并保存

这一步是在pycharm中进行的:

clf = AdaBoostClassifIEr(base_estimator=DecisionTreeClassifIEr(max_depth=7, min_samples_leaf=5),                             n_estimators=200,                             algorithm='SAMME', learning_rate=0.5)clf = clf.fit(train_x, train_y)  # 训练模型dump(clf, 'gao1_to_gao2_1.pkl')
4.Chaquopy中加载模型

  gao1_to_gao2_1.pkl放在python文件夹下:

from joblib import dump, loadfilename = join(dirname(__file__), 'gao1_to_gao2_1.pkl')clf = load(filename)
总结

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