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):
Network.__init__(self, "identica")
self.user = User(network=self.name)
self.auth = self.Oauth()
self.api = None
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, *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, 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')
