本文整理汇总了Python中neon.callbacks.callbacks.Callbacks.add_watch_ticker_callback方法的典型用法代码示例。如果您正苦于以下问题：Python Callbacks.add_watch_ticker_callback方法的具体用法？Python Callbacks.add_watch_ticker_callback怎么用？Python Callbacks.add_watch_ticker_callback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neon.callbacks.callbacks.Callbacks的用法示例。
在下文中一共展示了Callbacks.add_watch_ticker_callback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: GRU
# 需要导入模块: from neon.callbacks.callbacks import Callbacks [as 别名]
# 或者: from neon.callbacks.callbacks.Callbacks import add_watch_ticker_callback [as 别名]
output_size = 8
N = 120 # number of memory locations
M = 8 # size of a memory location
# model initialization
layers = [
GRU(hidden_size, init, activation=Tanh(), gate_activation=Logistic()),
Affine(train_set.nout, init, bias=init, activation=Logistic())
]
cost = GeneralizedCostMask(costfunc=CrossEntropyBinary())
model = Model(layers=layers)
optimizer = RMSProp(gradient_clip_value=gradient_clip_value,
stochastic_round=args.rounding)
# configure callbacks
callbacks = Callbacks(model, **args.callback_args)
# we can use the training set as the validation set,
# since the data is tickerally generated
callbacks.add_watch_ticker_callback(train_set)
# train model
model.fit(train_set,
optimizer=optimizer,
num_epochs=args.epochs,
cost=cost,
callbacks=callbacks)