def initialize(self, kwargs):
super(WeightLayer, self).initialize(kwargs)
req_param(self, ['weight_init', 'lrule_init', 'nin', 'nout'])
opt_param(self, ['accumulate'], False)
opt_param(self, ['batch_norm'], False)
self.weight_init.initialize(self.backend)
self.params = []
self.updates = []
if self.batch_norm:
self.bn = BatchNorm()
kwargs['layer'] = self
self.bn.initialize(kwargs)
def initialize(self, kwargs):
super(WeightLayer, self).initialize(kwargs)
req_param(self, ['nin', 'nout'])
opt_param(self, ['weight_init'], default_weight_init())
opt_param(self, ['lrule_init'], default_lrule_init())
opt_param(self, ['accumulate'], False)
opt_param(self, ['batch_norm'], False)
opt_param(self, ['mempool']) # Used for parallel mode
self.weight_init.initialize(self.backend)
self.params = []
self.updates = []
if self.batch_norm:
self.bn = BatchNorm()
kwargs['layer'] = self
self.bn.initialize(kwargs)
