def construct_model(data_init, model_type, margs, load_model_path,
load_model_complete, n_batch):
import models
margs['data_init'] = data_init
if model_type == 'fcvae1':
model = models.fcvae(**margs)
if model_type == 'cvae1':
model = models.cvae1(**margs)
if load_model_path != None:
print 'Loading existing model at ' + load_model_path
_w = G.ndict.np_loadz(load_model_path + '/weights.ndict.tar.gz')
G.ndict.set_value(model.w, _w, load_model_complete)
G.ndict.set_value(model.w_avg, _w, load_model_complete)
return model
def construct_model(data_init, model_type, margs, load_model_path, load_model_complete, n_batch):
import models
margs["data_init"] = data_init
if model_type == "fcvae1":
model = models.fcvae(**margs)
if model_type == "cvae1":
model = models.cvae1(**margs)
if load_model_path != None:
print "Loading existing model at " + load_model_path
_w = G.ndict.np_loadz(load_model_path + "/weights.ndict.tar.gz")
G.ndict.set_value(model.w, _w, load_model_complete)
G.ndict.set_value(model.w_avg, _w, load_model_complete)
return model
def construct_model(data_init, model_type, margs, load_model_path, load_model_complete, n_batch):
import models
margs['data_init'] = data_init
if model_type == 'fcvae1':
model = models.fcvae(**margs)
if model_type == 'cvae1':
model = models.cvae1(**margs)
if model_type == 'simplecvae1':
import simplemodel
model = simplemodel.simplecvae1(**margs)
if load_model_path != None:
print 'Loading existing model at '+load_model_path
_w = G.ndict.np_loadz(load_model_path+'/weights.ndict.tar.gz')
G.ndict.set_value(model.w, _w, load_model_complete)
G.ndict.set_value(model.w_avg, _w, load_model_complete)
return model