Python 使用Keras和TensorFlow GPU v2.0实现K折叠交叉验证

Python 使用Keras和TensorFlow GPU v2.0实现K折叠交叉验证,python,tensorflow,keras,tensorflow2.0,Python,Tensorflow,Keras,Tensorflow2.0,大家好,我正在学习k折叠交叉验证,第一段代码是构建一个简单的ANN: def buildModel(): # Fitting classifier to the Training set # Create your classifier here model = Sequential() model.add(Dense(units = 6, input_dim = X.shape[1], activation = 'relu')) model.add(D

大家好,我正在学习k折叠交叉验证,第一段代码是构建一个简单的ANN:

def buildModel():
    # Fitting classifier to the Training set
    # Create your classifier here
    model = Sequential()

    model.add(Dense(units = 6, input_dim = X.shape[1], activation = 'relu'))
    model.add(Dense(units = 6, activation = 'relu'))
    model.add(Dense(units = 1, activation = 'sigmoid'))
    model.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
    return model
然后,我在sklearn中使用cross_val_分数验证来运行ANN。 Keras也在我的gpu上运行

from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_val_score

model = KerasClassifier(build_fn = buildModel, batch_size = 10, epochs =100)
accuracies = cross_val_score(estimator = model, X = X_train, y = y_train, cv = 10, n_jobs = -1)
但是如果我把
n_jobs=-1
放在试着使用所有内核上,我会得到一个错误(ps,我有11个特性):

另外,我还在jupyter笔记本上跑步

任何帮助都是非常感激的。
谢谢。

这对您有帮助吗@v、 tralala感谢您的回复,但我已经看到了这些较旧的帖子,它们是针对tensorflow v1和tensorflow v2 config.gpu_选项的。allow_growth=True是不定价的。所以那个修正对我不起作用
Blas GEMM launch failed : a.shape=(10, 11), b.shape=(11, 6), m=10, n=6, k=11
 [[node dense_1/MatMul (defined at C:\Users\Brandon Cardillo\AppData\Roaming\Python\Python37\site-packages\tensorflow_core\python\framework\ops.py:1751) ]] 
 [Op:__inference_keras_scratch_graph_1030]

Function call stack:
keras_scratch_graph