def test_solver_load_pretrain():
#Get net prms
nPrms = mec.get_default_net_prms(dbFile, **kwargs)
del nPrms['expStr']
nPrms.baseNetDefProto = 'doublefc-v1_window_fc6'
nPrms = mpu.get_defaults(kwargs, nPrms, False)
nPrms['expStr'] = mec.get_sql_id(dbFile, dArgs, ignoreKeys=['ncpu'])
dPrms = get_data_prms()
nwFn = process_net_prms
ncpu = 0
nwArgs = {'ncpu': ncpu, 'lrAbove': None, 'preTrainNet': None}
solFn = mec.get_default_solver_prms
solArgs = {'dbFile': DEF_DB % 'sol', 'clip_gradients': 10}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=make_net_def,
isLog=True)
if isRun:
exp.make()
exp.run()
return exp
def simple_euler_dof2_dcv2_smallnetv5(isRun=False,
gradClip=10,
stepsize=20000,
base_lr=0.001,
gamma=0.5,
deviceId=0):
posePrms = slu.PosePrms(maxRot=90, simpleRot=True, dof=2)
dPrms = sev2.get_data_prms(lbPrms=posePrms)
nwFn = sev2.process_net_prms
nwArgs = {'ncpu': 0, 'baseNetDefProto': 'smallnet-v5_window_siamese_fc5'}
solFn = mec.get_default_solver_prms
solArgs = {
'dbFile': DEF_DB % 'sol',
'clip_gradients': gradClip,
'stepsize': stepsize,
'base_lr': base_lr,
'gamma': gamma
}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=sev2.make_net_def,
isLog=True)
if isRun:
exp.make(deviceId=deviceId)
exp.run()
return exp
def setup_experiment():
prms = get_mnist_prms()
nwPrms = {'netName': 'MyNet', 'baseNetDefProto': 'trainval.prototxt'}
cPrms = mec.get_caffe_prms(mec.get_default_net_prms,
nwPrms,
mec.get_default_solver_prms,
baseDefDir='./test_data/mnist')
exp = mec.CaffeSolverExperiment(prms, cPrms)
exp.make()
return exp
def setup_experiment():
prms = get_mnist_prms()
nwPrms = {'netName': 'MyNet',
'baseNetDefProto': 'trainval.prototxt'}
cPrms = mec.get_caffe_prms(mec.get_default_net_prms, nwPrms,
mec.get_default_solver_prms,
baseDefDir='./test_data/mnist')
exp = mec.CaffeSolverExperiment(prms, cPrms)
exp.make()
return exp
def scratch_cls_pd36(isRun=False,
nAzBins=18,
nElBins=18,
isLog=True,
gradClip=30,
stepsize=10000,
gamma=0.5,
base_lr=0.001,
deviceId=0,
isDropOut=False,
numDrop=1,
crpSz=240):
dPrms = pep.get_data_prms(anglePreProc='classify',
nAzBins=nAzBins,
nElBins=nElBins)
nwFn = pep.process_net_prms
ncpu = 0
if isDropOut:
if numDrop == 1:
baseProto = 'doublefc-v1_window_fc6_dropout'
else:
baseProto = 'doublefc-v1_window_fc6_double_dropout'
else:
baseProto = 'doublefc-v1_window_fc6'
nwArgs = {
'ncpu': ncpu,
'lrAbove': None,
'preTrainNet': None,
'dataNetDefProto': 'data_layer_pascal_cls',
'baseNetDefProtp': baseProto,
'lossNetDefProto': 'pascal_pose_loss_classify_layers',
'crpSz': crpSz
}
solFn = mec.get_default_solver_prms
solArgs = {
'dbFile': DEF_DB % 'sol',
'clip_gradients': gradClip,
' stepsize': stepsize,
'base_lr': base_lr,
'gamma': gamma
}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=pep.make_net_def,
isLog=isLog)
if isRun:
exp.make(deviceId=deviceId)
exp.run()
return exp
def alexnet_cls_pd36(isRun=False,
nAzBins=18,
nElBins=18,
isLog=True,
gradClip=30,
stepsize=10000,
gamma=0.5,
base_lr=0.001,
deviceId=0,
crpSz=240,
lrAbove=None,
meanFile='',
resumeIter=None):
dPrms = pep.get_data_prms(anglePreProc='classify',
nAzBins=nAzBins,
nElBins=nElBins)
nwFn = pep.process_net_prms
ncpu = 0
preTrainNet = osp.join(cfg.pths.data0,\
'caffe_models/bvlc_reference/bvlc_reference_caffenet_upgraded.caffemodel')
nwArgs = {
'ncpu': ncpu,
'lrAbove': lrAbove,
'preTrainNet': preTrainNet,
'dataNetDefProto': 'data_layer_pascal_cls',
'lossNetDefProto': 'pascal_pose_loss_classify_layers',
'baseNetDefProto': 'alexnet',
'ipImSz': 227,
'crpSz': crpSz,
'opLrMult': 10,
'meanFile': meanFile
}
solFn = mec.get_default_solver_prms
solArgs = {
'dbFile': DEF_DB % 'sol',
'clip_gradients': gradClip,
' stepsize': stepsize,
'base_lr': base_lr,
'gamma': gamma
}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs,
resumeIter=resumeIter)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=pep.make_net_def,
isLog=isLog)
if isRun:
exp.make(deviceId=deviceId)
exp.run()
return exp
def setup_experiment_finetune():
prms = get_mnist_prms()
preTrainNet = './test_data/mnist/mnist-test_iter_4000.caffemodel'
#preTrainNet = None
baseDefDir ='./test_data/mnist'
nwPrms = {'netName': 'MyNet',
'baseNetDefProto': osp.join(baseDefDir, 'trainval.prototxt'),
'preTrainNet': preTrainNet}
cPrms = mec.get_caffe_prms(mec.get_default_net_prms, nwPrms,
mec.get_default_solver_prms)
exp = mec.CaffeSolverExperiment(prms, cPrms)
exp.make()
return exp
def setup_experiment_finetune():
prms = get_mnist_prms()
preTrainNet = './test_data/mnist/mnist-test_iter_4000.caffemodel'
#preTrainNet = None
baseDefDir = './test_data/mnist'
nwPrms = {
'netName': 'MyNet',
'baseNetDefProto': osp.join(baseDefDir, 'trainval.prototxt'),
'preTrainNet': preTrainNet
}
cPrms = mec.get_caffe_prms(mec.get_default_net_prms, nwPrms,
mec.get_default_solver_prms)
exp = mec.CaffeSolverExperiment(prms, cPrms)
exp.make()
return exp
def torchnet_cls_pd36(isRun=False,
nAzBins=18,
nElBins=18,
isLog=True,
gradClip=30,
stepsize=10000,
gamma=0.5,
base_lr=0.001,
deviceId=0):
dPrms = pep.get_data_prms(anglePreProc='classify',
nAzBins=nAzBins,
nElBins=nElBins)
nwFn = pep.process_net_prms
ncpu = 0
preTrainNet = osp.join(cfg.pths.data0,\
'caffe_models/streetview/pose-l1-torch7.caffemodel')
nwArgs = {
'ncpu': ncpu,
'lrAbove': None,
'preTrainNet': preTrainNet,
'dataNetDefProto': 'data_layer_pascal_cls',
'lossNetDefProto': 'pascal_pose_loss_classify_layers',
'baseNetDefProto': 'pose-l1-torch7',
'ipImSz': 101,
'opLrMult': 10
}
solFn = mec.get_default_solver_prms
solArgs = {
'dbFile': DEF_DB % 'sol',
'clip_gradients': gradClip,
' stepsize': stepsize,
'base_lr': base_lr,
'gamma': gamma
}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=pep.make_net_def,
isLog=isLog)
if isRun:
exp.make(deviceId=deviceId)
exp.run()
return exp
def setup_experiment_demo(debugMode=False, isRun=False):
dPrms = get_data_prms()
nwFn = process_net_prms
ncpu = 0
nwArgs = {'lrAbove': None, 'preTrainNet': None}
solFn = mec.get_default_solver_prms
solArgs = {'dbFile': DEF_DB % 'sol', 'clip_gradients': 10}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=make_net_def,
isLog=True)
if isRun:
exp.make()
exp.run()
return exp
def simple_quat_dof5_dcv2_doublefcv1_l2loss(isRun=False,
gradClip=10,
stepsize=20000,
base_lr=0.001,
gamma=0.5,
deviceId=0,
readSingleGrp=False,
ncpu=0,
resumeIter=None):
posePrms = slu.PosePrms(maxRot=90,
simpleRot=False,
dof=5,
nrmlz=True,
angleType='quat')
dPrms = sev2.get_data_prms(lbPrms=posePrms)
nwFn = sev2.process_net_prms
nwArgs = {
'ncpu': ncpu,
'baseNetDefProto': 'doublefc-v1_window_siamese_fc6',
'lossNetDefProto': 'pose_loss_layers',
'readSingleGrp': readSingleGrp
}
solFn = mec.get_default_solver_prms
solArgs = {
'dbFile': DEF_DB % 'sol',
'clip_gradients': gradClip,
'stepsize': stepsize,
'base_lr': base_lr,
'gamma': gamma
}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs,
resumeIter=resumeIter)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=sev2.make_net_def,
isLog=True)
if isRun:
exp.make(deviceId=deviceId)
exp.run()
return exp
def test_solver_load_pretrain():
#Get net prms
nPrms = mec.get_default_net_prms(dbFile, **kwargs)
del nPrms['expStr']
nPrms.baseNetDefProto = 'doublefc-v1_window_fc6'
nPrms = mpu.get_defaults(kwargs, nPrms, False)
nPrms['expStr'] = mec.get_sql_id(dbFile, dArgs, ignoreKeys=['ncpu'])
dPrms = get_data_prms()
nwFn = process_net_prms
ncpu = 0
nwArgs = {'ncpu': ncpu, 'lrAbove': None, 'preTrainNet':None}
solFn = mec.get_default_solver_prms
solArgs = {'dbFile': DEF_DB % 'sol', 'clip_gradients': 10}
cPrms = mec.get_caffe_prms(nwFn=nwFn, nwPrms=nwArgs,
solFn=solFn, solPrms=solArgs)
exp = mec.CaffeSolverExperiment(dPrms, cPrms,
netDefFn=make_net_def, isLog=True)
if isRun:
exp.make()
exp.run()
return exp
def setup_experiment_demo(debugMode=False, isRun=False):
posePrms = slu.PosePrms()
dPrms = get_data_prms(lbPrms=posePrms)
nwFn = process_net_prms
if debugMode:
ncpu = 0
else:
ncpu = 2
nwArgs = {'ncpu': ncpu}
solFn = mec.get_default_solver_prms
solArgs = {'dbFile': DEF_DB % 'sol', 'clip_gradients': 10}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=make_net_def,
isLog=True)
if isRun:
exp.make()
exp.run()
return exp
def simple_euler_dof2_dcv2_doublefcv1_diff_no_common_fc(
isRun=False,
gradClip=30,
stepsize=60000,
base_lr=0.001,
gamma=0.1,
deviceId=0,
resumeIter=None):
posePrms = slu.PosePrms(maxRot=90, simpleRot=True, dof=2)
dPrms = sev2.get_data_prms(lbPrms=posePrms)
nwFn = sev2.process_net_prms
nwArgs = {
'ncpu': 0,
'baseNetDefProto': 'doublefc-v1_window_siamese_fc6_diff_no-common-fc'
}
solFn = mec.get_default_solver_prms
solArgs = {
'dbFile': DEF_DB % 'sol',
'clip_gradients': gradClip,
'stepsize': stepsize,
'base_lr': base_lr,
'gamma': gamma
}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs,
resumeIter=resumeIter)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=sev2.make_net_def,
isLog=True)
if isRun:
exp.make(deviceId=deviceId)
exp.run()
return exp
def doublefcv1_dcv2_dof2net_cls_pd36(isRun=False,
nAzBins=18,
nElBins=18,
isLog=True,
gradClip=30,
stepsize=10000,
gamma=0.5,
base_lr=0.001,
deviceId=0,
crpSz=240,
lrAbove=None,
isDropOut=False,
numDrop=1):
'''
isDropout: if dropouts should be used
numDrop : number of dropout layers
'''
#Source net
srcExp = mepg.simple_euler_dof2_dcv2_doublefcv1(gradClip=30,
stepsize=60000,
base_lr=0.001,
gamma=0.1)
srcIter = 182000
preTrainNet = srcExp.get_snapshot_name(srcIter)
#PASCAL Settings
dPrms = pep.get_data_prms(anglePreProc='classify',
nAzBins=nAzBins,
nElBins=nElBins)
nwFn = pep.process_net_prms
ncpu = 0
if isDropOut:
if numDrop == 1:
baseProto = 'doublefc-v1_window_fc6_dropout'
else:
baseProto = 'doublefc-v1_window_fc6_double_dropout'
else:
baseProto = 'doublefc-v1_window_fc6'
nwArgs = {
'ncpu': ncpu,
'lrAbove': lrAbove,
'preTrainNet': preTrainNet,
'dataNetDefProto': 'data_layer_pascal_cls',
'lossNetDefProto': 'pascal_pose_loss_classify_layers',
'baseNetDefProto': baseProto,
'ipImSz': 101,
'crpSz': crpSz,
'opLrMult': 10
}
solFn = mec.get_default_solver_prms
solArgs = {
'dbFile': DEF_DB % 'sol',
'clip_gradients': gradClip,
' stepsize': stepsize,
'base_lr': base_lr,
'gamma': gamma
}
cPrms = mec.get_caffe_prms(nwFn=nwFn,
nwPrms=nwArgs,
solFn=solFn,
solPrms=solArgs)
exp = mec.CaffeSolverExperiment(dPrms,
cPrms,
netDefFn=pep.make_net_def,
isLog=isLog)
if isRun:
exp.make(deviceId=deviceId)
exp.run()
return exp
