Port conflicts in GridSearchCV using Jubakit

wrapper.py

# -*- coding:utf-8 -*-
import numpy as np
from scipy.sparse import issparse
from jubakit.classifier import Classifier, Config, Dataset, Schema
from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.utils import check_random_state

class LinearClassifier(BaseEstimator, ClassifierMixin):

    def __init__(self, method='AROW', regularization_weight=1.0, n_iter=5, 
                 shuffle=True, seed=None, port=None):
        self.method = method
        self.regularization_weight = regularization_weight
        self.n_iter = n_iter
        self.shuffle = shuffle
        self.seed = seed
        self.port = port

    def partial_fit(self, X, y):
        check_random_state(self.seed)
        
        if self.clf_ is None:
            self._launch_classifier()

        dataset = self._load_dataset(X, y)

        for i in range(self.n_iter):
            if self.shuffle:
                dataset = dataset.shuffle(self.seed)
            for _ in self.clf_.train(dataset): pass

        return self
    
    def fit(self, X, y):
        self._launch_classifier()
        return self.partial_fit(X, y)

    def predict(self, X):
        y_dummy = np.zeros(X.shape[0])
        y_pred = np.zeros(X.shape[0])
        
        dataset = self._load_dataset(X, y_dummy)

        for index, _, result in self.clf_.classify(dataset):
            y_pred[index] = result[0][0]
        
        return y_pred

    def decision_function(self, X):
        y_dummy = np.zeros(X.shape[0])
        decisions = np.zeros((X.shape[0], self.classes_.shape[0]))
        
        dataset = self._load_dataset(X, y_dummy)

        for index, _, result in self.clf_.classify(dataset):
            for ret in result:
                i = np.where(self.classes_ == int(ret[0]))
                decisions[index][i] = ret[1]

        return decisions                

    def _launch_classifier(self):
        self.cfg_ = Config(method=self.method,
                        parameter={'regularization_weight': self.regularization_weight})
        self.clf_ = Classifier.run(config=self.cfg_, port=self.port)

    def _load_dataset(self, X, y):
        self.classes_ = np.unique(y)
        if issparse(X):
            return Dataset.from_matrix(X, y)
        else:
            return Dataset.from_array(X, y)

    def stop(self):
        self.clf_.stop()
        self.clf_ = None

    def clear(self):
        self.clf_.clear()

if __name__ == '__main__':
    from sklearn.datasets import load_iris
    from sklearn.grid_search import GridSearchCV
    
    iris = load_iris()
    X = iris.data
    y = iris.target
    
    clf = LinearClassifier()
    parameters = {'method': ['AROW', 'CW'], 
                  'regularization_weight': [0.1, 1, 10]}
    
    print('single thread mode (n_jobs=1)')
    gs = GridSearchCV(clf, parameters)
    gs.fit(X, y)
    print('best_score', gs.best_score_)
    print('best_params', gs.best_params_)
    
    print('multi thread mode (n_jobs=-1)')
    gs = GridSearchCV(clf, parameters, n_jobs=-1)
    gs.fit(X, y)
    print('best_score', gs.best_score_)
    print('best_params', gs.best_params_)

Jubakit cannot launch service with ports that already obtained by scikit-learn.grid_search.GridSearchCV.

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/home/daats/.pyenv/versions/3.5.0/lib/python3.5/site-packages/jubakit/base.py in run(cls=<class 'jubakit.classifier.Classifier'>, config={'parameter': {'regularization_weight': 0.1}, 'm...'unigram', 'global_weight': 'idf', 'key': '*'}]}}, port=None)
    441   def run(cls, config, port=None):
    442     """
    443     Runs a new standalone server and returns the serivce instance to access
    444     the server.
    445     """
--> 446     backend = _ServiceBackend(cls.name(), config, port)
        backend = undefined
        cls.name = <bound method Classifier.name of <class 'jubakit.classifier.Classifier'>>
        config = {'parameter': {'regularization_weight': 0.1}, 'm...'unigram', 'global_weight': 'idf', 'key': '*'}]}}
        port = None
    447     _logger.info('service %s started on port %d', cls.name(), backend.port)
    448 
    449     # Returns the Service instance.
    450     service = cls('127.0.0.1', backend.port)

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/home/daats/.pyenv/versions/3.5.0/lib/python3.5/site-packages/jubakit/base.py in __init__(self=<jubakit.base._ServiceBackend object>, name='classifier', config={'parameter': {'regularization_weight': 0.1}, 'm...'unigram', 'global_weight': 'idf', 'key': '*'}]}}, port=None)
    543       if started:
    544         status = self.get_status()
    545         pid = int(status['pid'])
    546         if pid != self._proc.pid:
    547           self._proc.kill()
--> 548           raise RuntimeError('server cannot be started as port {0} conflicts with external Jubatus process (PID: {1})'.format(self.port, pid))
        self.port = 10000
        pid = 12125
    549 
    550     if not started:
    551       _logger.error('failed to start service')
    552       log = self.stop()

RuntimeError: server cannot be started as port 10000 conflicts with external Jubatus process (PID: 12125)
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