本文整理匯總了Python中caffe.log方法的典型用法代碼示例。如果您正苦於以下問題：Python caffe.log方法的具體用法？Python caffe.log怎麽用？Python caffe.log使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類caffe的用法示例。
在下文中一共展示了caffe.log方法的5個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: train
# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import log [as 別名]
def train(
solver, # solver proto definition
snapshot, # solver snapshot to restore
gpus, # list of device ids
timing=False, # show timing info for compute and communications
):
# NCCL uses a uid to identify a session
uid = caffe.NCCL.new_uid()
caffe.init_log()
caffe.log('Using devices %s' % str(gpus))
procs = []
for rank in range(len(gpus)):
p = Process(target=solve_step,
args=(solver, snapshot, gpus, timing, uid, rank))
p.daemon = True
p.start()
procs.append(p)
for p in procs:
p.join() 示例2: train_net_multi_gpu
# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import log [as 別名]
def train_net_multi_gpu(solver_prototxt, roidb, output_dir, pretrained_model,
max_iter, gpus, reload):
"""Train a Fast R-CNN network."""
roidb = filter_roidb(roidb)
uid = caffe.NCCL.new_uid()
caffe.init_log()
caffe.log('Using devices %s' % str(gpus))
procs = []
for rank in range(len(gpus)):
p = Process(target=solve,
args=(
solver_prototxt, roidb, pretrained_model, gpus, uid,
rank,
output_dir, max_iter, reload))
p.daemon = True
p.start()
procs.append(p)
for p in procs:
p.join() 示例3: train
# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import log [as 別名]
def train(
solver, # solver proto definition
snapshot, # solver snapshot to restore
gpus, # list of device ids
timing=False, # show timing info for compute and communications
):
# NCCL uses a uid to identify a session
uid = caffe.NCCL.new_uid()
caffe.init_log()
caffe.log('Using devices %s' % str(gpus))
procs = []
for rank in range(len(gpus)):
p = Process(target=solve,
args=(solver, snapshot, gpus, timing, uid, rank))
p.daemon = True
p.start()
procs.append(p)
for p in procs:
p.join() 示例4: time
# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import log [as 別名]
def time(solver, nccl):
fprop = []
bprop = []
total = caffe.Timer()
allrd = caffe.Timer()
for _ in range(len(solver.net.layers)):
fprop.append(caffe.Timer())
bprop.append(caffe.Timer())
display = solver.param.display
def show_time():
if solver.iter % display == 0:
s = '\n'
for i in range(len(solver.net.layers)):
s += 'forw %3d %8s ' % (i, solver.net._layer_names[i])
s += ': %.2f\n' % fprop[i].ms
for i in range(len(solver.net.layers) - 1, -1, -1):
s += 'back %3d %8s ' % (i, solver.net._layer_names[i])
s += ': %.2f\n' % bprop[i].ms
s += 'solver total: %.2f\n' % total.ms
s += 'allreduce: %.2f\n' % allrd.ms
caffe.log(s)
solver.net.before_forward(lambda layer: fprop[layer].start())
solver.net.after_forward(lambda layer: fprop[layer].stop())
solver.net.before_backward(lambda layer: bprop[layer].start())
solver.net.after_backward(lambda layer: bprop[layer].stop())
solver.add_callback(lambda: total.start(), lambda: (total.stop(), allrd.start()))
solver.add_callback(nccl)
solver.add_callback(lambda: '', lambda: (allrd.stop(), show_time())) 示例5: train
# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import log [as 別名]
def train(
solver, # solver proto definition
snapshot, # solver snapshot to restore
use_cpu, #whether use cpu
gpus, # list of device ids
timing=False, # show timing info for compute and communications
):
caffe.init_log(0,True)
caffe.log('Using devices %s' % str(gpus))
if use_cpu == True:
p = Process(target=cpu_solve,
args=(solver, snapshot, timing))
p.daemon = True
p.start()
p.join()
else:
# NCCL uses a uid to identify a session
uid = caffe.NCCL.new_uid()
procs = []
for rank in range(len(gpus)):
p = Process(target=solve,
args=(solver, snapshot, gpus, timing, uid, rank))
p.daemon = True
p.start()
procs.append(p)
for p in procs:
p.join()