Python caffe.NCCL屬性代碼示例

本文整理匯總了Python中caffe.NCCL屬性的典型用法代碼示例。如果您正苦於以下問題：Python caffe.NCCL屬性的具體用法？Python caffe.NCCL怎麽用？Python caffe.NCCL使用的例子？那麽, 這裏精選的屬性代碼示例或許可以為您提供幫助。您也可以進一步了解該屬性所在類caffe的用法示例。

在下文中一共展示了caffe.NCCL屬性的8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 NCCL [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()

開發者ID:zhujiagang，項目名稱:DTPP，代碼行數:23，代碼來源:multigpu.py

示例2: solve

# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import NCCL [as 別名]
def solve(proto, snapshot, gpus, timing, uid, rank):
    caffe.set_mode_gpu()
    caffe.set_device(gpus[rank])
    caffe.set_solver_count(len(gpus))
    caffe.set_solver_rank(rank)
    caffe.set_multiprocess(True)

    solver = caffe.SGDSolver(proto)
    if snapshot and len(snapshot) != 0:
        solver.restore(snapshot)

    nccl = caffe.NCCL(solver, uid)
    nccl.bcast()

    if timing and rank == 0:
        time(solver, nccl)
    else:
        solver.add_callback(nccl)

    if solver.param.layer_wise_reduce:
        solver.net.after_backward(nccl)
    solver.step(solver.param.max_iter)

開發者ID:zhujiagang，項目名稱:DTPP，代碼行數:24，代碼來源:multigpu.py

示例3: train_net_multi_gpu

# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import NCCL [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()

開發者ID:po0ya，項目名稱:face-magnet，代碼行數:22，代碼來源:train_multi_gpu.py

示例4: train

# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import NCCL [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()

開發者ID:QinganZhao，項目名稱:Deep-Learning-Based-Structural-Damage-Detection，代碼行數:23，代碼來源:train.py

示例5: solve

# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import NCCL [as 別名]
def solve(proto, gpus, uid, rank, max_iter):
    caffe.set_mode_gpu()
    caffe.set_device(gpus[rank])
    caffe.set_solver_count(len(gpus))
    caffe.set_solver_rank(rank)
    caffe.set_multiprocess(True)

    solver = caffe.SGDSolver(proto)
    if rank == 0:
        # solver.restore(_snapshot)
        solver.net.copy_from(_weights)
    
    solver.net.layers[0].get_gpu_id(gpus[rank])

    nccl = caffe.NCCL(solver, uid)
    nccl.bcast()
    solver.add_callback(nccl)

    if solver.param.layer_wise_reduce:
        solver.net.after_backward(nccl)

    for _ in range(max_iter):
        solver.step(1)

開發者ID:soeaver，項目名稱:caffe-model，代碼行數:25，代碼來源:train_net_multi.py

示例6: train

# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import NCCL [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()

開發者ID:ucloud，項目名稱:uai-sdk，代碼行數:32，代碼來源:train_large_file.py

示例7: solve

# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import NCCL [as 別名]
def solve(proto, roidb, pretrained_model, gpus, uid, rank, output_dir, max_iter,
          reload):
    caffe.set_device(gpus[rank])
    caffe.set_mode_gpu()
    caffe.set_solver_count(len(gpus))

    caffe.set_solver_rank(rank)

    caffe.set_multiprocess(True)
    cfg.GPU_ID = gpus[rank]

    solverW = SolverWrapper(solver_prototxt=proto, roidb=roidb,
                            output_dir=output_dir, gpu_id=rank,
                            pretrained_model=pretrained_model, reload=reload)
    solver = solverW.get_solver()
    nccl = caffe.NCCL(solver, uid)
    nccl.bcast()
    solver.add_callback(nccl)

    if solver.param.layer_wise_reduce:
        solver.net.after_backward(nccl)
    while solver.iter < max_iter:
        solver.step(1)

        if solver.iter % cfg.TRAIN.SNAPSHOT_ITERS == 0 and rank == 0:
            solverW.snapshot()

開發者ID:po0ya，項目名稱:face-magnet，代碼行數:28，代碼來源:train_multi_gpu.py

示例8: solve_step

# 需要導入模塊: import caffe [as 別名]
# 或者: from caffe import NCCL [as 別名]
def solve_step(proto, snapshot, gpus, timing, uid, rank):
    caffe.set_mode_gpu()
    caffe.set_device(gpus[rank])
    caffe.set_solver_count(len(gpus))
    caffe.set_solver_rank(rank)
    caffe.set_multiprocess(True)

    solver = caffe.SGDSolver(proto)
    if snapshot and len(snapshot) != 0:
        solver.restore(snapshot)

    nccl = caffe.NCCL(solver, uid)
    nccl.bcast()

    if timing and rank == 0:
        time(solver, nccl)
    else:
        solver.add_callback(nccl)

    if solver.param.layer_wise_reduce:
        solver.net.after_backward(nccl)

    niter = solver.param.max_iter
    display = solver.param.display
    test_iter = 950
    test_interval = 200
    # 初始化
    train_loss = zeros(int(ceil(niter // display)))
    test_loss = zeros(int(ceil(niter // test_interval)))
    test_acc = zeros(int(ceil(niter // test_interval)))
    # 輔助變量
    _train_loss = 0;
    _test_loss = 0;
    _accuracy = 0;
    _max_accuracy = 0;
    _max_accuracy_iter = 0;
    # 進行解算
    for it in range(niter):
        solver.step(1)


#def train_this(
#        solver,  # solver proto definition
#        snapshot,  # solver snapshot to restore
#        gpus,  # list of device ids
#        timing=False,  # show timing info for compute and communications
#):
 #   train(solver, snapshot, gpus, timing)

#solver = caffe.SGDSolver('/home/zhujiagang/temporal-segment-networks/models/ucf101/gating_three_solver.prototxt')
#solver.restore('/home/zhujiagang/temporal-segment-networks/models/ucf101_split_1_gating_three_iter_200.solverstate')

開發者ID:zhujiagang，項目名稱:DTPP，代碼行數:53，代碼來源:multigpu.py

注：本文中的caffe.NCCL屬性示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。