def __init__(self, **kwargs):
Model.__init__(self)
Base.__init__(self)
self.metadata = Base.metadata
for name, val in kwargs.iteritems():
self.__setattr__(name, val)
def __init__(self,
batch_size=10,
max_len=30,
lstm_size=20,
vocab_size=10000,
embeddings_dim=20,
keep_probs=0.9,
attention_size=16,
use_embedding=True,
reg="none",
lam=None,
sparse=False,
kwm_lstm_size=10,
learning_rate=0.1):
Model.__init__(self,
batch_size,
max_len,
vocab_size,
embeddings_dim,
use_embedding,
learning_rate=learning_rate)
self.lstm_size = lstm_size
self.attention_size = attention_size
self.reg = reg
self.lam = lam
self.kwm_lstm_size = kwm_lstm_size
self.sparse = sparse
self.keep_probs = keep_probs
self.use_alphas = True
self.build_model()
def __init__(self, name=None, autoconnect=None, **kwargs):
Model.__init__(self)
Base.__init__(self)
self.metadata = Base.metadata
self.name = name
self.autoconnect = autoconnect
def __init__(self, args):
Model.__init__(self, args)
self.model = None
self.build_model()
self.train_loss = []
self.valid_loss_history = []
assert (self.seq_length * self.num_characters == self.input)
def __init__(self, train, column, choices=[], beta0=None, name='Enum model', bounds=None): Model.__init__(self, train) self.choices = choices self.column = column self.name = name self._beta0 = list(beta0) self._bounds = list(bounds)
def __init__(self, form):
Model.__init__(self, form)
self.username = form.get('username', '')
self.password = salted_password(form.get('password', ''))
self.signature = form.get('signature', '这家伙很懒，什么个性签名都没有留下。')
self.user_image = form.get('user_image', '')
self.role = form.get('role', 2)
def __init__(self, lower=[0.01, 50, 100], upper = [0.2, 150, 1000], algo_model=dtlz.dtlz1, algo_num_obj=1, algo_num_decs=1):
Model.__init__(self)
#define upper and lower bounds for dec variables: Mutation rate, no of candidates and no of gens
self.name = 'Tuner Model'
self.lower_bounds = lower
self.upper_bounds = upper
self.no_of_decisions = len(lower)
self.algo_model = algo_model
self.algo_num_obj = algo_num_obj
self.algo_num_decs = algo_num_decs
def __init__(self, lower=[0.01, 50, 100], upper = [0.2, 150, 1000], algo_model=dtlz.dtlz1, algo_num_obj=1, algo_num_decs=1):
Model.__init__(self)
#define upper and lower bounds for dec variables: Mutation rate, no of candidates and no of gens
self.name = 'Tuner Model'
self.lower_bounds = lower
self.upper_bounds = upper
self.no_of_decisions = len(lower)
self.algo_model = algo_model
self.algo_num_obj = algo_num_obj
self.algo_num_decs = algo_num_decs
def __init__(self, name=None, password=None, access=None, **kwargs):
Model.__init__(self)
Base.__init__(self)
self.metadata = Base.metadata
self.name = name
self.password = password
self.access = access
for name, val in kwargs.iteritems():
self.__setattr__(name, val)
def __init__(self, train):
Model.__init__(self, train)
self.bymonth = bymonth = train.groupby('month')
# First of each month and last of last month
dayages = bymonth.first()['dayage'].values
self.dayages = numpy.concatenate([dayages, train.iloc[-1:]['dayage'].values])
self.means = bymonth['count'].mean()
self.nsegments = len(bymonth)
self.nparams = self.nsegments + 1
def __init__(self, model_name):
Model.__init__(self, model_name) # initialize the base class
# then create/override the variable
#self.model_name = "faceDetectionModel"
self.model_name = model_name
self.logger = logging.getLogger(__name__)
try:
self.model = IENetwork(self.model_structure, self.model_weights)
except Exception:
self.logger.exception("The Network could not be initialized. Check that you have the correct model path")
self.load_model()
Model.check_model(self, model_name)
def __init__(self, degree, memory_depth):
# Sanity check
memory_depth = Model._check_degree_and_depth(degree, memory_depth)
# Initialize fields
self.degree = degree
self.memory_depth = memory_depth
self.kernels = Kernels(degree, memory_depth)
self.order_lock = None
self._shadow = None
self._buffer = None
# Call parent's construction methods
Model.__init__(self)
def __init__(self, memory_depth, mark='nn', degree=None, **kwargs):
# Sanity check
if memory_depth < 1: raise ValueError('!! Memory depth should be positive')
# Call parent's construction methods
Model.__init__(self)
# Initialize fields
self.memory_depth = memory_depth
self.D = memory_depth
self.degree = degree
# TODO: compromise
bamboo = kwargs.get('bamboo', False)
bamboo_broad = kwargs.get('bamboo_broad', False)
identity_inital = kwargs.get('identity_initial', False)
if degree is not None:
self.nn = VolterraNet(degree, memory_depth, mark, **kwargs)
elif bamboo:
self.nn = Bamboo(mark=mark, identity=identity_inital)
elif bamboo_broad:
self.nn = Bamboo_Broad(mark=mark, inter_type=pedia.fork, identity=identity_inital)
else: self.nn = Predictor(mark=mark)
def __init__(self, memory_depth, mark='nn', degree=None, **kwargs):
# Sanity check
if memory_depth < 1:
raise ValueError('!! Memory depth should be positive')
# Call parent's construction methods
Model.__init__(self)
# Initialize fields
self.memory_depth = memory_depth
self.D = memory_depth
self.degree = degree
# TODO: compromise
bamboo = kwargs.get('bamboo', False)
nn_class = kwargs.get('nn_class', None)
if nn_class is not None:
self.nn = nn_class(mark=mark)
elif degree is not None:
self.nn = VolterraNet(degree, memory_depth, mark, **kwargs)
elif bamboo:
self.nn = Bamboo(mark=mark)
else:
self.nn = Predictor(mark=mark)
def __init__(self, form):
Model.__init__(self, form)
self.username = form.get('username', '')
self.password = salted_password(form.get('password', ''))
self.note = form.get('note', '')
self.role = form.get('role', 2)
def __init__(self, train): Model.__init__(self, train) dayage = train['dayage'].values self.begin = dayage[0] self.end = dayage[-1] self.mean = train['count'].mean()
def __init__(self, train, name='Unnamed'): self.name = name Model.__init__(self, train)
def __init__(self, app):
Model.__init__(self, app)
def __init__(self, dbpath): Model.__init__(self, dbpath, "proxy_users")
def __init__(self, dbpath): Model.__init__(self, dbpath, "downloads") self.Status = Status
def __init__(self, access=None, **kwargs):
Model.__init__(self)
Base.__init__(self)
self.access = access
def __init__(self):
Model.__init__(self, self.__class__.__name__.lower())
