本文整理汇总了Python中activity.Activity.get_acts方法的典型用法代码示例。如果您正苦于以下问题：Python Activity.get_acts方法的具体用法？Python Activity.get_acts怎么用？Python Activity.get_acts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activity.Activity的用法示例。
在下文中一共展示了Activity.get_acts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: validation_data
# 需要导入模块: from activity import Activity [as 别名]
# 或者: from activity.Activity import get_acts [as 别名]
def validation_data(self, contrast=1., small_batch_size = 1000,large_batch_size = 50000):
parameters = self.network.parameters
parameters.batch_size = small_batch_size
orig_time_data = parameters.time_data
orig_keep_spikes = parameters.keep_spikes
#parameters.time_data = True
#parameters.static_data_control = True
parameters.keep_spikes = True
if orig_keep_spikes == False:
self.network.spike_train = ()
nout = parameters.M
for ii in np.arange(self.network.n_layers):
out_dim = nout[ii]
self.network.spike_train += (nw.make_shared((parameters.batch_size,
out_dim,
parameters.num_iterations)),)
small_bs = self.network.parameters.batch_size
batch_size = large_batch_size
if parameters.time_data and not parameters.static_data_control:
data = Time_Data(os.path.join(os.environ['DATA_PATH'],'vanhateren/whitened_images.h5'),
1000,
parameters.batch_size,
parameters.N,
parameters.num_frames,
start=35)
else:
data = Static_Data(os.path.join(os.environ['DATA_PATH'],'vanhateren/whitened_images.h5'),
1000,
parameters.batch_size,
parameters.N,
start=35)
self.network.to_gpu()
activity = Activity(self.network)
self.big_X = np.zeros((batch_size, parameters.N), dtype='float32')
self.big_Y = ()
for layer in range(self.network.n_layers):
self.big_Y += (np.zeros((batch_size, parameters.M[layer]), dtype='float32'),)
for ii in range(batch_size/small_bs):
data.make_X(self.network)
if contrast != 1.:
self.network.X.set_value(self.network.X.get_value() *
np.array(contrast, dtype='float32'))
activity.get_acts()
self.big_X[ii*small_bs:(ii+1)*small_bs,:] = self.network.X.get_value()
for layer in range(self.network.n_layers):
self.big_Y[layer][ii*small_bs:(ii+1)*small_bs,:] = self.network.Y[layer].get_value()
self.network.to_cpu()
self.network.Y = self.big_Y
self.network.X = self.big_X
self.network.parameters.time_data = orig_time_data
self.network.parameters.keep_spikes = orig_keep_spikes