def __init__(self, name):
# Call parent's constructor
Net.__init__(self, name)
# Attributes
self._inter_type = self.RECURRENT
self._train_state_buffer = None
self._eval_state_buffer = None
self._state_size = None
self._init_state = None
self._weights = None
self._bias = None
self._weight_initializer = None
self._bias_initializer = None
# For real-time training TODO: BETA
self.repeater_tensors = None # registered in sub-classes
self._grad_tensors = None
self._new_state_tensor = None #
self._gradient_buffer_placeholder = None
self._gradient_buffer_array = None
self._custom_vars = None
# Gate activations should be registered here
self._gate_dict = OrderedDict()
def __init__(self, name):
# Call parent's constructor
Net.__init__(self, name)
# Attributes
self._inter_type = self.RECURRENT
self._state_array = None
self._state_size = None
self._init_state = None
self._kernel = None
self._bias = None
self._weight_initializer = None
self._bias_initializer = None
def __init__(self, mark=None, **kwargs):
# Call parent's initializer
Model.__init__(self, mark)
Net.__init__(self, 'Bamboo_Broad_Net', inter_type=pedia.fork)
assert self._inter_type == pedia.fork
self.outputs = None
# Private fields
self._losses = []
self._metrics = []
self._train_ops = []
self._var_list = []
self._output_list = []
self._branch_index = 0
self._identity_initial = kwargs.get('ientity', False)
def __init__(self, mark=None):
Model.__init__(self, mark)
Net.__init__(self, 'FeedforwardNet')
self.superior = self
self._default_net = self
def __init__(self, mark=None):
Model.__init__(self, mark)
Net.__init__(self, 'FeedforwardNet')
self.outputs = None