Compatibility with GridSearchCV and n_jobs > 1

[rth]

Issue reported by @gkjegan,

I started using pysofia and got the following error. Not sure how to resolve. Can you please help? PermissionError: [Errno 13] Permission denied: 'C:\\Users\\gkjeg\\AppData\\Local\\Temp\\tmp9i54w65j' The error trace

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\externals\joblib\_parallel_backends.py in apply_async(self, func, callback)
    109     def apply_async(self, func, callback=None):
    110         """Schedule a func to be run"""
--> 111         result = ImmediateResult(func)
    112         if callback:
    113             callback(result)

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\externals\joblib\_parallel_backends.py in __init__(self, batch)

    330         # Don't delay the application, to avoid keeping the input
    331         # arguments in memory
--> 332         self.results = batch()
    333 
    334     def get(self):

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\externals\joblib\parallel.py in __call__(self)
    129 
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
    132 
    133     def __len__(self):
C:\ProgramData\Anaconda3\lib\site-packages\sklearn\externals\joblib\parallel.py in <listcomp>(.0)
    129
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
    132 
    133     def __len__(self):

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\cross_validation.py in _fit_and_score(estimator, X, y, scorer, train, test, verbose, parameters, fit_params, return_train_score, return_parameters, error_score)
   1673             estimator.fit(X_train, **fit_params)
   1674         else:
-> 1675             estimator.fit(X_train, y_train, **fit_params)
   1676 
   1677     except Exception as e:

C:\ProgramData\Anaconda3\lib\site-packages\pysofia\compat.py in fit(self, X, y, query_id)
     26         self.coef_ = svm_train(X, y, query_id, self.alpha, n_samples, n_features,
     27             learner_type.sgd_svm, loop_type.rank, eta_type.basic_eta,
---> 28             max_iter=self.max_iter)
     29         return self

C:\ProgramData\Anaconda3\lib\site-packages\pysofia\sofia_ml.py in svm_train(X, y, b, alpha, n_samples, n_features, learner, loop, eta, max_iter, step_probability)

     98 
     99         with tempfile.NamedTemporaryFile() as f:
--> 100             datasets.dump_svmlight_file(X, y, f.name, query_id=b)
    101             w = _sofia_ml.train(f.name, n_features, alpha, max_iter, False,
    102                                 learner.value, loop.value, eta.value, step_probability)

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\datasets\svmlight_format.py in dump_svmlight_file(X, y, f, zero_based, comment, query_id, multilabel)

    478         _dump_svmlight(X, y, f, multilabel, one_based, comment, query_id)
    479     else:
--> 480         with open(f, "wb") as f:
    481             _dump_svmlight(X, y, f, multilabel, one_based, comment, query_id)

PermissionError: [Errno 13] Permission denied: 'C:\\Users\\gkjeg\\AppData\\Local\\Temp\\tmp9i54w65j'

[rth]

@gkjegan Thanks for reporting this issue. I imagine you are using GridSearchCV from scikit-learn with n_jobs parameter larger than 1?

Could you please provide a sample of code that raised this exception. Also please provide the output of the following commands,

import platform; print(platform.platform())
import sys; print("Python", sys.version)
import numpy; print("NumPy", numpy.__version__)
import scipy; print("SciPy", scipy.__version__)
import sklearn; print("Scikit-Learn", sklearn.__version__)
import pysofia; print("PySofia", pysofia.__version__)

Thanks.

[gkjegan]

Hi Roman,

Thanks for the response. here is the output

Windows-10-10.0.15063-SP0 Python 3.6.3 |Anaconda, Inc.| (default, Oct 15 2017, 03:27:45) [MSC v.1900 64 bit (AMD64)] NumPy 1.13.3 SciPy 0.19.1 Scikit-Learn 0.19.1 PySofia 0.9

I am trying just same as example

%pylab inline from sklearn import cross_validation from pysofia.compat import RankSVM, RankSVMCV

scores = cross_validation.cross_val_score(RankSVM(max_iter=200), X, y) print(scores) print(np.mean(scores))

Regards,

Jegan GK

On Thu, Nov 30, 2017 at 9:11 AM, Roman Yurchak notifications@github.com wrote:

@gkjegan https://github.com/gkjegan Thanks for reporting this issue. I imagine you are using GridSearchCV from scikit-learn with n_jobs parameter larger than 1?

Could you please provide a sample of code that raised this exception. Also please provide the output of the following commands,

import platform; print(platform.platform())import sys; print("Python", sys.version)import numpy; print("NumPy", numpy.version)import scipy; print("SciPy", scipy.version)import sklearn; print("Scikit-Learn", sklearn.version)import pysofia; print("PySofia", pysofia.version)

Thanks.

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