本文整理汇总了Python中keras.layers.Dense.ravel方法的典型用法代码示例。如果您正苦于以下问题：Python Dense.ravel方法的具体用法？Python Dense.ravel怎么用？Python Dense.ravel使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类keras.layers.Dense的用法示例。
在下文中一共展示了Dense.ravel方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: print
# 需要导入模块: from keras.layers import Dense [as 别名]
# 或者: from keras.layers.Dense import ravel [as 别名]
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)