def __init__(self, scen_inst) : Network.__init__(self, scen_inst) ''' For each node in the scenario ''' for node in self._scen_inst.get_nodes() : ''' Add a wireless interface to the node (eth0) ''' node.get('interfaces')['eth0'] = Model(type='wireless', range=20, ssid='wlan0')
def __init__(self, name, hyperparameters=OrderedDict()): Network.__init__(self, name, hyperparameters) # tensors self.label = [] # label tensors self.input, self.output = [], [] # list of tensors self.in_dtype, self.out_dtype = [], [] # list of str dtypes # parameters self.W_params, self.B_params = [], [] # xWh, hWy, xBy params self.V_params, self.U_params = [], [] # xWh, hWy params self.hbias, self.vbias, self.cbias = [], [], [] # bias # flattened version self.W_params_f, self.B_params_f = [], [] # xWh, hWy, xBy params self.V_params_f, self.U_params_f = [], [] # xWh, hWy params self.vbias_f, self.cbias_f = [], [] # sigmas self.vsigmas, self.csigmas = [], [] self.vsigmas_f = [] # parameter masks self.B_params_m, self.U_params_m = [], [] # list of the Uh mask self.cbias_m = []
def __init__(self): Network.__init__(self, learn_rate=0.1)
def __init__(self, sizes): Network.__init__(self, sizes)
def __init__(self, topology, session=None, scope='model'): Network.__init__(self, topology, session=session, scope=scope)
def __init__(self): Network.__init__(self) self._m = 0.
def __init__(self): Network.__init__(self, "twitter") self.user = User(network=self.name) self.auth = self.Oauth() self.api = None
def __init__(self, base_power=0): Network.__init__(self, base_power)
def __init__(self, *args, **kwargs): self.settlement = DateVar() self.transaction_datetime = DateTimeVar() self.transaction_date = DateVar() self.transaction_time = TimeVar() Network.__init__(self, *args, **kwargs)
def __init__(self): Network.__init__(self, "identica") self.user = User(network=self.name) self.auth = self.Oauth() self.api = None
def __init__(self, cond): Network.__init__(self) self._beta = BETA self._satisComCond = cond
def __init__(self): """ intialization of the connection object:""" # creates a debug displays list to be used ot send message self.debug_displays = [] self.__config = config.read() Network.__init__(self)
def __init__(self, weight_parameters, bias_parameters): Network.__init__(self, weight_parameters, bias_parameters)
from network import Network from ops import * class Generator(Network): def __init__(self, input_shape, output_shape, , optimizer_function = tf.train.GradientDescentOptimizer, learning_rate = 0.001, name = 'gen', build = False): Network.__init__(self,[input_shape],output_shape, optimizer_function = optimizer_function, learning_rate = learning_rate, name = name) self.keep_proba = tf.placeholder(tf.float32,name='dropout') self.g_bn_e2 = batch_norm(name='g_bn_e2') self.g_bn_e3 = batch_norm(name='g_bn_e3') self.g_bn_e4 = batch_norm(name='g_bn_e4') self.g_bn_e5 = batch_norm(name='g_bn_e5') self.g_bn_e6 = batch_norm(name='g_bn_e6') self.g_bn_e7 = batch_norm(name='g_bn_e7') self.g_bn_e8 = batch_norm(name='g_bn_e8') self.g_bn_d1 = batch_norm(name='g_bn_d1') self.g_bn_d2 = batch_norm(name='g_bn_d2') self.g_bn_d3 = batch_norm(name='g_bn_d3')
def __init__(self): Network.__init__(self)
def __init__(self, topology, session=None, scope='model', loss='l2'): self.loss_type = loss Network.__init__(self, [topology], session=session, scope=scope)
def __init__(self, scen_inst) : Network.__init__(self, scen_inst) for node_model in self._scen_inst.get_nodes() : node_model.get('interfaces')['eth0'] = Model(type='wireless', range=20, ssid='wlan0')