PicklingError in when using KerasClassifier for Cross-Validation in Spark
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Though I am able to run the following code perfectly on my local:
`from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_val_score
from keras.models import Sequential
from keras.layers import Dense
def build_classifier():
classifier = Sequential()
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu'))
classifier.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))
classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
return classifier
classifier = KerasClassifier(build_fn = build_classifier, batch_size = 10, epochs = 100)
accuracies = cross_val_score(estimator = classifier, X = X_train, y = y_train, cv = 10, n_jobs = -1)`
I am getting PicklingError : Can't pickle <function build_classifier at 0x7f98f3cbabf8>: attribute lookup build_classifier on __main__ failed
Based on my understanding of the PicklingError when trying to parallelize in Python, it looks like there is some issue with the position where I have defined the function, but I am not able to make it run. How can I troubleshoot this?
keras pyspark
asked Nov 23 '18 at 22:54
saurav shekharsaurav shekhar
379112
add a comment |
Though I am able to run the following code perfectly on my local:
`from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_val_score
from keras.models import Sequential
from keras.layers import Dense
def build_classifier():
classifier = Sequential()
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu'))
classifier.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))
classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
return classifier
classifier = KerasClassifier(build_fn = build_classifier, batch_size = 10, epochs = 100)
accuracies = cross_val_score(estimator = classifier, X = X_train, y = y_train, cv = 10, n_jobs = -1)`
I am getting PicklingError : Can't pickle <function build_classifier at 0x7f98f3cbabf8>: attribute lookup build_classifier on __main__ failed
Based on my understanding of the PicklingError when trying to parallelize in Python, it looks like there is some issue with the position where I have defined the function, but I am not able to make it run. How can I troubleshoot this?
keras pyspark
asked Nov 23 '18 at 22:54
saurav shekharsaurav shekhar
379112
add a comment |
Though I am able to run the following code perfectly on my local:
`from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_val_score
from keras.models import Sequential
from keras.layers import Dense
def build_classifier():
classifier = Sequential()
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu'))
classifier.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))
classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
return classifier
classifier = KerasClassifier(build_fn = build_classifier, batch_size = 10, epochs = 100)
accuracies = cross_val_score(estimator = classifier, X = X_train, y = y_train, cv = 10, n_jobs = -1)`
I am getting PicklingError : Can't pickle <function build_classifier at 0x7f98f3cbabf8>: attribute lookup build_classifier on __main__ failed
Based on my understanding of the PicklingError when trying to parallelize in Python, it looks like there is some issue with the position where I have defined the function, but I am not able to make it run. How can I troubleshoot this?
keras pyspark
asked Nov 23 '18 at 22:54
saurav shekharsaurav shekhar
379112
Though I am able to run the following code perfectly on my local:
`from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_val_score
from keras.models import Sequential
from keras.layers import Dense
def build_classifier():
classifier = Sequential()
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu'))
classifier.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))
classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
return classifier
classifier = KerasClassifier(build_fn = build_classifier, batch_size = 10, epochs = 100)
accuracies = cross_val_score(estimator = classifier, X = X_train, y = y_train, cv = 10, n_jobs = -1)`
I am getting PicklingError : Can't pickle <function build_classifier at 0x7f98f3cbabf8>: attribute lookup build_classifier on __main__ failed
Based on my understanding of the PicklingError when trying to parallelize in Python, it looks like there is some issue with the position where I have defined the function, but I am not able to make it run. How can I troubleshoot this?
keras pyspark
keras pyspark
asked Nov 23 '18 at 22:54
saurav shekharsaurav shekhar
379112
asked Nov 23 '18 at 22:54
saurav shekharsaurav shekhar
379112
edited Nov 25 '18 at 3:12
saurav shekhar
asked Nov 23 '18 at 22:54
saurav shekharsaurav shekhar
379112
asked Nov 23 '18 at 22:54
saurav shekharsaurav shekhar
379112
asked Nov 23 '18 at 22:54
saurav shekharsaurav shekhar
379112
379112
add a comment |
add a comment |
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