def orth_loss_v2(self, bottom_name):
# self.Python('orth_loss', 'orthLossLayer', loss_weight=1, bottom=[bottom_name], top=[name], name=name)
# , bottom=[bottom+'_MVN']
# save bottom
mainpath = self.bottom
bottom = bottom_name #'NormLayer',
# self.MVN(bottom=[bottom])
layer = "TransposeLayer"
layername = bottom_name+'_' + layer
outputs = [layername]
self.Python(layer, layer, top=outputs, bottom=[bottom], name=layername, phase='TRAIN')
self.Matmul()
outputs = [self.this.name]
self.EuclideanLoss(name=bottom_name+'_euclidean', bottom=outputs, loss_weight=1e-1, phase='TRAIN')
# restore bottom
self.cur = mainpath
python类TRAIN的实例源码
def resnet(n=3, num_output = 16):
"""6n+2, n=3 9 18 coresponds to 20 56 110 layers"""
net_name = "resnet-"
pt_folder = osp.join(osp.abspath(osp.curdir), net_name +str(6*n+2))
name = net_name+str(6*n+2)+'-cifar10'
if n > 18:
# warm up
solver = Solver(solver_name="solver_warm.prototxt", folder=pt_folder, lr_policy=Solver.policy.fixed)
solver.p.base_lr = 0.01
solver.set_max_iter(500)
solver.write()
del solver
solver = Solver(folder=pt_folder)
solver.write()
del solver
builder = Net(name)
builder.Data('cifar-10-batches-py/train', phase='TRAIN', crop_size=32)
builder.Data('cifar-10-batches-py/test', phase='TEST')
builder.resnet_cifar(n, num_output=num_output)
builder.write(folder=pt_folder)
def resnet_orth_v2(n=3):
"""6n+2, n=3 9 18 coresponds to 20 56 110 layers"""
net_name = "resnet-orth-v2"
pt_folder = osp.join(osp.abspath(osp.curdir), net_name +str(6*n+2))
name = net_name+str(6*n+2)+'-cifar10'
if n > 18:
# warm up
solver = Solver(solver_name="solver_warm.prototxt", folder=pt_folder, lr_policy=Solver.policy.fixed)
solver.p.base_lr = 0.01
solver.set_max_iter(500)
solver.write()
del solver
solver = Solver(folder=pt_folder)
solver.write()
del solver
builder = Net(name)
builder.Data('cifar-10-batches-py/train', phase='TRAIN', crop_size=32)
builder.Data('cifar-10-batches-py/test', phase='TEST')
builder.resnet_cifar(n, orth=True, v2=True)
builder.write(folder=pt_folder)
def _get_include(phase):
inc = caffe_pb2.NetStateRule()
if phase == 'train':
inc.phase = caffe_pb2.TRAIN
elif phase == 'test':
inc.phase = caffe_pb2.TEST
else:
raise ValueError("Unknown phase {}".format(phase))
return inc
def include(self, phase='TRAIN'):
if phase is not None:
includes = self.this.include.add()
if phase == 'TRAIN':
includes.phase = caffe_pb2.TRAIN
elif phase == 'TEST':
includes.phase = caffe_pb2.TEST
else:
NotImplementedError
#************************** inplace **************************
def include(self, phase='TRAIN'):
if phase is not None:
includes = self.this.include.add()
if phase == 'TRAIN':
includes.phase = caffe_pb2.TRAIN
elif phase == 'TEST':
includes.phase = caffe_pb2.TEST
else:
NotImplementedError
#************************** inplace **************************
def MVN(self, name=None, bottom=[], normalize_variance=True, across_channels=False, phase='TRAIN'):
if across_channels:
NotImplementedError
if not normalize_variance:
NotImplementedError
self.setup(self.suffix('MVN', name),bottom=bottom, layer_type='MVN')
if phase!='TRAIN':
NotImplementedError
self.include()
def plain_func(self, name, num_output, up=False, **kwargs):
self.conv_bn_relu(name+'_conv0', num_output=num_output, stride=1+int(up), **kwargs)
self.conv_bn_relu(name+'_conv1', num_output=num_output, **kwargs)
# def orth_loss(self, bottom_name):
# # self.Python('orth_loss', 'orthLossLayer', loss_weight=1, bottom=[bottom_name], top=[name], name=name)
# # , bottom=[bottom+'_MVN']
# # save bottom
# mainpath = self.bottom
# bottom = bottom_name #'NormLayer',
# # self.MVN(bottom=[bottom])
# layer = "TransposeLayer"
# layername = bottom_name+'_' + layer
# outputs = [layername]#, bottom_name+'_zerolike']
# self.Python(layer, layer, top=outputs, bottom=[bottom], name=layername, phase='TRAIN')
# self.Matmul()
# # layer="diagLayer"
# # layername = bottom_name+'_' + layer
# # self.Python(layer, layer, top=[layername], name=layername, phase='TRAIN')
# outputs = [self.this.name]#, bottom_name+'_zerolike']
# self.EuclideanLoss(name=bottom_name+'_euclidean', bottom=outputs, loss_weight=1e-3, phase='TRAIN')
# # restore bottom
# self.cur = mainpath
def plain(n=3):
"""6n+2, n=3 9 18 coresponds to 20 56 110 layers"""
net_name = "plain"
pt_folder = osp.join(osp.abspath(osp.curdir), net_name +str(6*n+2))
name = net_name+str(6*n+2)+'-cifar10'
solver = Solver(folder=pt_folder)
solver.write()
del solver
builder = Net(name)
builder.Data('cifar-10-batches-py/train', phase='TRAIN', crop_size=32)
builder.Data('cifar-10-batches-py/test', phase='TEST')
builder.plain_cifar(n, num_output = 16)
builder.write(folder=pt_folder)
def plain_orth(n=3):
"""6n+2, n=3 5 7 9 18 coresponds to 20 56 110 layers"""
net_name = "plain-orth"
pt_folder = osp.join(osp.abspath(osp.curdir), net_name +str(6*n+2))
name = net_name+str(6*n+2)+'-cifar10'
solver = Solver(folder=pt_folder)
solver.write()
del solver
builder = Net(name)
builder.Data('cifar-10-batches-py/train', phase='TRAIN', crop_size=32)
builder.Data('cifar-10-batches-py/test', phase='TEST')
builder.plain_cifar(n, orth=True)
builder.write(folder=pt_folder)
def plain_orth_v1(n=3):
"""6n+2, n=3 5 7 9 18 coresponds to 20 32 44 56 110 layers"""
net_name = "plain-orth-v1-"
pt_folder = osp.join(osp.abspath(osp.curdir), net_name +str(6*n+2))
name = net_name+str(6*n+2)+'-cifar10'
solver = Solver(folder=pt_folder)
solver.write()
del solver
builder = Net(name)
builder.Data('cifar-10-batches-py/train', phase='TRAIN', crop_size=32)
builder.Data('cifar-10-batches-py/test', phase='TEST')
builder.plain_cifar(n, orth=True, inplace=False, num_output = 16)
builder.write(folder=pt_folder)
def acc(n=3):
"""6n+2, n=3 9 18 coresponds to 20 56 110 layers"""
net_name = "plain"
pt_folder = osp.join(osp.abspath(osp.curdir), net_name +str(6*n+2))
name = net_name+str(6*n+2)+'-cifar10'
solver = Solver(folder=pt_folder)
solver.write()
del solver
builder = Net(name)
builder.Data('cifar-10-batches-py/train', phase='TRAIN', crop_size=32)
builder.Data('cifar-10-batches-py/test', phase='TEST')
builder.plain_cifar(n, num_output = 16, inplace=False)
builder.write(folder=pt_folder)
