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나는 Keras 주장의 오류에 문제가 발생하고 있는데 누군가가 도와 주실 수 있는지 묻고 싶다 :Keras 신경망 주장 오류
내가 Keras 실행 한 윈 차원 컨볼 루션으로 이전하고이 오류를 본 적이있다.
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-41-c4780c441db5> in <module>()
26
27 model2.fit(x_train_ex, y_train_ex, batch_size=batch_size, nb_epoch=nb_epoch,
---> 28 verbose=1, validation_data=(x_test_ex, y_test_ex))
29 #print(model2.score(x_train_ex, y_train))
30 #print(model2.score(x_test_ex, y_test))
.........(Lots more error messages)
AssertionError:
가 대단히 감사합니다 :
#-----------------BEGIN FUNCTION 1-----------------
def create_model(input_size1, num_labels, conv1_num_filters, conv1_filter_size1, conv2_num_filters, conv2_filter_size1, pool1_1, dropout1, pool2_1, dropout2, neurons1, reg_l2, neurons2, reg_l2_2):
model = Sequential()
model.add(Convolution1D(conv1_num_filters, conv1_filter_size1, init = 'glorot_uniform', border_mode='same',
input_shape=(1, input_size1),
activation = 'relu'))
model.add(MaxPooling1D(pool_length=(pool1_1),border_mode='same'))
model.add(BatchNormalization(epsilon=0.001, mode=0, axis=1, momentum=0.99, weights=None, beta_init='zero', gamma_init='one', gamma_regularizer=None, beta_regularizer=None))
model.add(Convolution1D(conv2_num_filters, conv2_filter_size1, init = 'glorot_uniform', activation = 'relu', border_mode='same'))
model.add(MaxPooling1D(pool_length=(pool1_1),border_mode='same'))
model.add(Dropout(dropout1))
model.add(Flatten())
model.add(BatchNormalization(epsilon=0.001, mode=0, axis=1, momentum=0.99, weights=None, beta_init='zero', gamma_init='one', gamma_regularizer=None, beta_regularizer=None))
model.add(Dense(neurons1, W_regularizer=l2(reg_l2), init = 'glorot_uniform', activation = 'relu'))
model.add(Dropout(dropout2))
model.add(BatchNormalization(epsilon=0.001, mode=0, axis=1, momentum=0.99, weights=None, beta_init='zero', gamma_init='one', gamma_regularizer=None, beta_regularizer=None))
model.add(Dense(neurons2, W_regularizer=l2(reg_l2_2), init = 'glorot_uniform', activation = 'relu'))
model.add(Dense(num_labels, init = 'glorot_uniform', activation = 'tanh'))
sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True) #0.01
model.compile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy'])
print(model.summary())
#exit()
return model
#-----------------END FUNCTION 1-----------------
model2 = create_model(input_size1, num_labels, conv1_num_filters,
conv1_filter_size1, conv2_num_filters,
conv2_filter_size1, pool1_1, dropout1, pool2_1,
dropout2, neurons1, reg_l2, neurons2, reg_l2_2);
x_train_ex = np.expand_dims(x_train, 1)
x_test_ex = np.expand_dims(x_test, 1)
from keras.utils.np_utils import to_categorical
y_train_ex = to_categorical(y_train, len(np.unique(y_train)))
y_test_ex = to_categorical(y_test, len(np.unique(y_train)))
model2.fit(x_train_ex, y_train_ex, batch_size=batch_size, nb_epoch=nb_epoch,
verbose=1, validation_data=(x_test_ex, y_test_ex)
는)
내가 말하는 오류가 발생합니다!
오류 메시지를 편집하지 말고 전체 메시지를 붙여 넣으십시오. –
죄송합니다, 향후에 할 것입니다. –