小编Jos*_*hoi的帖子

每当我在Keras上试用LSTM模型时,由于训练时间过长,似乎无法训练模型.

例如,这样的模型每步需要80秒来训练:

def create_model(self):
        inputs = {}
        inputs['input'] = []
        lstm = []
        placeholder = {}
        for tf, v in self.env.timeframes.items():
            inputs[tf] = Input(shape = v['shape'], name = tf)
            lstm.append(LSTM(8)(inputs[tf]))
            inputs['input'].append(inputs[tf])
        account = Input(shape = (3,), name = 'account')
        account_ = Dense(8, activation = 'relu')(account)
        dt = Input(shape = (7,), name = 'dt')
        dt_ = Dense(16, activation = 'relu')(dt)
        inputs['input'].extend([account, dt])

        data = Concatenate(axis = 1)(lstm)
        data = Dense(128, activation = 'relu')(data)
        y = Concatenate(axis = 1)([data, account, dt])
        y …

您如何从网站下载图像并将其保存到Common Lisp中的包文件夹中？我很难在dexador的文档中寻找这样的功能.

提前致谢