本文整理匯總了Python中keras.layers.Dense.ravel方法的典型用法代碼示例。如果您正苦於以下問題：Python Dense.ravel方法的具體用法？Python Dense.ravel怎麽用？Python Dense.ravel使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類keras.layers.Dense的用法示例。
在下文中一共展示了Dense.ravel方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: print
# 需要導入模塊: from keras.layers import Dense [as 別名]
# 或者: from keras.layers.Dense import ravel [as 別名]
outputs=preds)
model.compile(loss='binary_crossentropy',
optimizer='nadam',
metrics=['acc'])
#model.summary()
print(STAMP)
early_stopping =EarlyStopping(monitor='val_loss', patience=3)
bst_model_path = STAMP + '.h5'
model_checkpoint = ModelCheckpoint(bst_model_path, save_best_only=True, save_weights_only=True)
hist = model.fit([data_1_train, data_2_train], labels_train, \
validation_data=([data_1_val, data_2_val], labels_val, weight_val), \
epochs=200, batch_size=2048, shuffle=True, \
class_weight=class_weight, callbacks=[early_stopping, model_checkpoint])
model.load_weights(bst_model_path)
bst_val_score = min(hist.history['val_loss'])
########################################
## make the submission
########################################
print('Start making the submission before fine-tuning')
preds = model.predict([test_data_1, test_data_2], batch_size=8192, verbose=1)
preds += model.predict([test_data_2, test_data_1], batch_size=8192, verbose=1)
preds /= 2
submission = pd.DataFrame({'test_id':test_ids, 'is_duplicate':preds.ravel()})
submission.to_csv('%.4f_'%(bst_val_score)+STAMP+'.csv', index=False)