def main():
if params.gpu_flag is not False:
cuda.init(params.gpu_flag)
print 'fetching data ...'
fetcher = cifar(norm=False)
bo = BO(
train_model, {
'wscale1': (-5, 0),
'wscale2': (-5, 0),
'wscale3': (-5, 0),
'wscale4': (-5, 0),
'wscale5': (-5, 0),
'lr': (-4, -2),
'batchsize': (30, 300),
'momentum': (0.5, 1.0),
'decay': (-4, -2)
})
"""
bo.explore({'wscale1' : [-4],
'wscale2' : [-2],
'wscale3' : [-2],
'wscale4' : [-1],
'wscale5' : [-1],
'lr' : [-3],
'batchsize' : [100],
'momentum' : [0.9],
'decay' : [-3]
})
"""
bo.add_f_args('fetcher', fetcher)
bo.maximize(init_points=params.opt_init_points, n_iter=params.opt_iter)
print bo.res['max']
def main():
if params.gpu_flag is not False:
cuda.init(params.gpu_flag)
print 'fetching data ...'
fetcher = cifar(norm=False)
bo = BO(train_model,
{'wscale1' : (-5, 0),
'wscale2' : (-5, 0),
'wscale3' : (-5, 0),
'wscale4' : (-5, 0),
'wscale5' : (-5, 0),
'lr' : (-4, -2),
'batchsize' : (30, 300),
'momentum' : (0.5, 1.0),
'decay' : (-4, -2)
})
"""
bo.explore({'wscale1' : [-4],
'wscale2' : [-2],
'wscale3' : [-2],
'wscale4' : [-1],
'wscale5' : [-1],
'lr' : [-3],
'batchsize' : [100],
'momentum' : [0.9],
'decay' : [-3]
})
"""
bo.add_f_args('fetcher', fetcher)
bo.maximize(init_points=params.opt_init_points, n_iter=params.opt_iter)
print bo.res['max']
def main():
if params.gpu_flag is not False:
cuda.init(params.gpu_flag)
if params.model_name is False:
model = init_model()
else:
model = load_model(params.model_name)
optimizer = init_optimizer(model)
print 'fetching data ...'
fetcher = cifar(norm=False)
print 'done'
train_and_val(model, optimizer, fetcher)
def main():
if params.gpu_flag is not False:
cuda.init(params.gpu_flag)
if params.model_name is False:
model = init_model()
else:
model = load_model(params.model_name)
optimizer = init_optimizer(model)
print 'fetching data ...'
fetcher = cifar(norm=False)
print 'done'
train_and_val(model, optimizer, fetcher)