请问下关于训练报错

Des8302

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请问各位这是代表什么问题？
我之前训练都用 batch 8 都没问题，这次我练新的素材，结果就出现这个报错了
对了，我最近为了尝试Roop ，下载了PYTHON ，好像是3.11版本的，会是造成冲突吗？
而且最近训练时的迭代变慢很多，有时2秒跳一次，有时4-5秒甚至更久才跳2-3次。
Error: 2 root error(s) found.
  (0) Resource exhausted: OOM when allocating tensor with shape[704,1024,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node gradients/Conv2D_42_grad/Conv2DBackpropFilter (defined at C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\ops\__init__.py:55) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

         [[gradients/AddN_27/_369]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

  (1) Resource exhausted: OOM when allocating tensor with shape[704,1024,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node gradients/Conv2D_42_grad/Conv2DBackpropFilter (defined at C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\ops\__init__.py:55) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node gradients/Conv2D_42_grad/Conv2DBackpropFilter:
Pad_42 (defined at C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87)

Input Source operations connected to node gradients/Conv2D_42_grad/Conv2DBackpropFilter:
Pad_42 (defined at C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87)

Original stack trace for 'gradients/Conv2D_42_grad/Conv2DBackpropFilter':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\ModelBase.py", line 193, in __init__
    self.on_initialize()
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 511, in on_initialize
    gpu_G_loss_gvs += [ nn.gradients ( gpu_G_loss, self.src_dst_trainable_weights ) ]
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\ops\__init__.py", line 55, in tf_gradients
    grads = gradients.gradients(loss, vars, colocate_gradients_with_ops=True )
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 172, in gradients
    unconnected_gradients)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 684, in _GradientsHelper
    lambda: grad_fn(op, *out_grads))
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 340, in _MaybeCompile
    return grad_fn()  # Exit early
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 684, in <lambda>
    lambda: grad_fn(op, *out_grads))
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_grad.py", line 606, in _Conv2DGrad
    data_format=data_format)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1131, in conv2d_backprop_filter
    name=name)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper
    attrs=attr_protos, op_def=op_def)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3536, in _create_op_internal
    op_def=op_def)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 1990, in __init__
    self._traceback = tf_stack.extract_stack()

...which was originally created as op 'Conv2D_42', defined at:
  File "threading.py", line 884, in _bootstrap
[elided 3 identical lines from previous traceback]
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\ModelBase.py", line 193, in __init__
    self.on_initialize()
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 390, in on_initialize
    gpu_pred_dst_dst, gpu_pred_dst_dstm = self.decoder(gpu_dst_code)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 179, in forward
    m = self.upscalem0(z)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 60, in forward
    x = self.conv1(x)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 101, in forward
    x = tf.nn.conv2d(x, weight, strides, 'VALID', dilations=dilations, data_format=nn.data_format)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper
    return target(*args, **kwargs)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2279, in conv2d
    name=name)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 972, in conv2d
    data_format=data_format, dilations=dilations, name=name)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper
    attrs=attr_protos, op_def=op_def)

Traceback (most recent call last):
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1375, in _do_call
    return fn(*args)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1360, in _run_fn
    target_list, run_metadata)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1453, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: OOM when allocating tensor with shape[704,1024,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node gradients/Conv2D_42_grad/Conv2DBackpropFilter}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

         [[gradients/AddN_27/_369]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

  (1) Resource exhausted: OOM when allocating tensor with shape[704,1024,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node gradients/Conv2D_42_grad/Conv2DBackpropFilter}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

0 successful operations.
0 derived errors ignored.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Trainer.py", line 129, in trainerThread
    iter, iter_time = model.train_one_iter()
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\ModelBase.py", line 474, in train_one_iter
    losses = self.onTrainOneIter()
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 741, in onTrainOneIter
    src_loss, dst_loss = self.src_dst_train (warped_src, target_src, target_srcm, target_srcm_em, warped_dst, target_dst, target_dstm, target_dstm_em)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 546, in src_dst_train
    self.target_dstm_em:target_dstm_em,
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 968, in run
    run_metadata_ptr)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1191, in _run
    feed_dict_tensor, options, run_metadata)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1369, in _do_run
    run_metadata)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1394, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: OOM when allocating tensor with shape[704,1024,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node gradients/Conv2D_42_grad/Conv2DBackpropFilter (defined at C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\ops\__init__.py:55) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

         [[gradients/AddN_27/_369]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

  (1) Resource exhausted: OOM when allocating tensor with shape[704,1024,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node gradients/Conv2D_42_grad/Conv2DBackpropFilter (defined at C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\ops\__init__.py:55) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node gradients/Conv2D_42_grad/Conv2DBackpropFilter:
Pad_42 (defined at C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87)

Input Source operations connected to node gradients/Conv2D_42_grad/Conv2DBackpropFilter:
Pad_42 (defined at C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87)

Original stack trace for 'gradients/Conv2D_42_grad/Conv2DBackpropFilter':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\ModelBase.py", line 193, in __init__
    self.on_initialize()
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 511, in on_initialize
    gpu_G_loss_gvs += [ nn.gradients ( gpu_G_loss, self.src_dst_trainable_weights ) ]
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\ops\__init__.py", line 55, in tf_gradients
    grads = gradients.gradients(loss, vars, colocate_gradients_with_ops=True )
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 172, in gradients
    unconnected_gradients)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 684, in _GradientsHelper
    lambda: grad_fn(op, *out_grads))
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 340, in _MaybeCompile
    return grad_fn()  # Exit early
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 684, in <lambda>
    lambda: grad_fn(op, *out_grads))
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_grad.py", line 606, in _Conv2DGrad
    data_format=data_format)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1131, in conv2d_backprop_filter
    name=name)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper
    attrs=attr_protos, op_def=op_def)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3536, in _create_op_internal
    op_def=op_def)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 1990, in __init__
    self._traceback = tf_stack.extract_stack()

...which was originally created as op 'Conv2D_42', defined at:
  File "threading.py", line 884, in _bootstrap
[elided 3 identical lines from previous traceback]
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\ModelBase.py", line 193, in __init__
    self.on_initialize()
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 390, in on_initialize
    gpu_pred_dst_dst, gpu_pred_dst_dstm = self.decoder(gpu_dst_code)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 179, in forward
    m = self.upscalem0(z)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 60, in forward
    x = self.conv1(x)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 101, in forward
    x = tf.nn.conv2d(x, weight, strides, 'VALID', dilations=dilations, data_format=nn.data_format)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper
    return target(*args, **kwargs)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2279, in conv2d
    name=name)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 972, in conv2d
    data_format=data_format, dilations=dilations, name=name)
  File "C:\Users\des83\Desktop\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper
    attrs=attr_protos, op_def=op_def)

lknet

虚拟内存设置大一点,素材分辨率改为和模型分辨率一致.

Des8302

lknet 发表于 2023-7-21 15:21
虚拟内存设置大一点,素材分辨率改为和模型分辨率一致.

Current iteration: 5789                               ==
==                                                           ==
==---------------------- Model Options ----------------------==
==                                                           ==
==            resolution: 128                                ==
==             face_type: wf                                 ==
==     models_opt_on_gpu: False                              ==
==                 archi: liae-ud                            ==
==               ae_dims: 256                                ==
==                e_dims: 64                                 ==
==                d_dims: 64                                 ==
==           d_mask_dims: 22                                 ==
==       masked_training: True                               ==
==       eyes_mouth_prio: False                              ==
==           uniform_yaw: False                              ==
==             adabelief: False                              ==
==            lr_dropout: n                                  ==
==           random_warp: False                              ==
==       true_face_power: 0.0                                ==
==      face_style_power: 0.0                                ==
==        bg_style_power: 0.0                                ==
==               ct_mode: rct                                ==
==              clipgrad: False                              ==
==              pretrain: False                              ==
==       autobackup_hour: 1                                  ==
== write_preview_history: False                              ==
==           target_iter: 0                                  ==
==       random_src_flip: False                              ==
==       random_dst_flip: False                              ==
==            batch_size: 6                                  ==
==             gan_power: 0.0                                ==
==        gan_patch_size: 32                                 ==
==              gan_dims: 16                                 ==
==                                                           ==
==----------------------- Running On ------------------------==
==                                                           ==
==          Device index: 0                                  ==
==                  Name: NVIDIA GeForce RTX 3060 Laptop GPU ==
==                  VRAM: 4.62GB                             ==

谷谷

显存爆了OOM
降BS

ronld

Des8302 发表于 2023-7-21 15:42
Current iteration: 5789                               ==
==                                       ...

你这是笔记本的3060，换ICE版本试试，BS降到4即便能跑，估计没跑成笔记本就废了

Des8302

ronld 发表于 2023-7-21 20:28
你这是笔记本的3060，换ICE版本试试，BS降到4即便能跑，估计没跑成笔记本就废了 ...

我其他的bs8跑得动，只是最近迭代都变得很慢，我有点担心会不会是我的显卡开始要废了

ronld

Des8302 发表于 2023-7-24 13:31
我其他的bs8跑得动，只是最近迭代都变得很慢，我有点担心会不会是我的显卡开始要废了 ...

这是废的前兆，别尝试着回到原来的速度，那是回光返照