DFL常见报错答疑搜集贴，不定时更新

訧哉

aaa2002911 发表于 2021-7-11 13:42
发信息要发全啊，这上面只显示了你选择N然后错误了。什么玩意参数选N了 ...

Running trainer.

Choose one of saved models, or enter a name to create a new model.
[r] : rename
[d] : delete

[0] : 变换脸 - latest
:
0
Loading 变换脸_SAEHD model...

Choose one or several GPU idxs (separated by comma).

[CPU] : CPU
  [0] : GeForce GTX 1050

[0] Which GPU indexes to choose? :
0
Press enter in 2 seconds to override model settings.
[0] Autobackup every N hour ( 0..24 ?:help ) :
0
[n] Write preview history ( y/n ?:help ) :
n
[69] Target iteration : 0
0
[y] Flip faces randomly ( y/n ?:help ) :
y
[8] Batch_size ( ?:help ) : 4
4
[y] Learn mask ( y/n ?:help ) :
y
[n] Eyes priority ( y/n ?:help ) :
n
[y] Place models and optimizer on GPU ( y/n ?:help ) :
y
Error: 'n'
Traceback (most recent call last):
  File "D:\DeepFaceLab\DeepFaceLab_NVIDIA\_internal\DeepFaceLab\mainscripts\Trainer.py", line 55, in trainerThread
    debug=debug,
  File "D:\DeepFaceLab\DeepFaceLab_NVIDIA\_internal\DeepFaceLab\models\ModelBase.py", line 162, in __init__
    self.on_initialize_options()
  File "D:\DeepFaceLab\DeepFaceLab_NVIDIA\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 97, in on_initialize_options
    self.options['lr_dropout']  = io.input_bool ("Use learning rate dropout", default_lr_dropout, help_message="When the face is trained enough, you can enable this option to get extra sharpness and reduce subpixel shake for less amount of iterations.")
  File "D:\DeepFaceLab\DeepFaceLab_NVIDIA\_internal\DeepFaceLab\core\interact\interact.py", line 284, in input_bool
    s = f"[{yn_str[default_value]}] {s} ( y/n"
KeyError: 'n'
大佬救命

wys9808179

请问没有找到 00001.jpg 的面孔，复制时没有面孔怎么解决，谢谢大佬！

alex2527

厉害了，学习了

酷酷sean

感谢，十分感谢，不用一个个找了

shaing

3050ti 4g显存 训练quick96报了两个错，除了爆显存外还有什么问题？
Error: 2 root error(s) found.
  (0) Resource exhausted: OOM when allocating tensor with shape[1024,512,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Conv2D_31 (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:101) ]]
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/Reshape_49_grad/Reshape/_577]]
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[1024,512,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Conv2D_31 (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:101) ]]
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 Conv2D_31:
decoder_dst/upscale1/conv1/weight/read (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:61)
Pad_31 (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87)

Input Source operations connected to node Conv2D_31:
decoder_dst/upscale1/conv1/weight/read (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:61)
Pad_31 (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87)

Original stack trace for 'Conv2D_31':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\ModelBase.py", line 191, in __init__
    self.on_initialize()
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 114, in on_initialize
    gpu_pred_dst_dst, gpu_pred_dst_dstm = self.decoder_dst(gpu_dst_code)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 155, in forward
    x = self.upscale1(x)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 57, in forward
    x = self.conv1(x)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "D:\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 "D:\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 "D:\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 "D:\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 "D:\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 "D:\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 "D:\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()

Traceback (most recent call last):
  File "D:\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 "D:\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 "D:\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[1024,512,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node Conv2D_31}}]]
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/Reshape_49_grad/Reshape/_577]]
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[1024,512,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node Conv2D_31}}]]
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 "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Trainer.py", line 129, in trainerThread
    iter, iter_time = model.train_one_iter()
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\ModelBase.py", line 472, in train_one_iter
    losses = self.onTrainOneIter()
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 276, in onTrainOneIter
    warped_dst, target_dst, target_dstm)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 178, in src_dst_train
    self.target_dstm:target_dstm,
  File "D:\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 "D:\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 "D:\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 "D:\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[1024,512,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Conv2D_31 (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:101) ]]
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/Reshape_49_grad/Reshape/_577]]
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[1024,512,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Conv2D_31 (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:101) ]]
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 Conv2D_31:
decoder_dst/upscale1/conv1/weight/read (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:61)
Pad_31 (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87)

Input Source operations connected to node Conv2D_31:
decoder_dst/upscale1/conv1/weight/read (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:61)
Pad_31 (defined at D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87)

Original stack trace for 'Conv2D_31':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\ModelBase.py", line 191, in __init__
    self.on_initialize()
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 114, in on_initialize
    gpu_pred_dst_dst, gpu_pred_dst_dstm = self.decoder_dst(gpu_dst_code)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 155, in forward
    x = self.upscale1(x)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 57, in forward
    x = self.conv1(x)
  File "D:\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "D:\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 "D:\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 "D:\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 "D:\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 "D:\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 "D:\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 "D:\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()

jdx

谢谢 今天正好学习了

酷酷sean

十分感谢，小白学到了很多

jdx

我是在遮罩模型训练时出现  No segmented faces found.该怎么解决

Loading samples: 100% 1515/1515 [00:09<00:00, 165.28it/s]
Loading samples: 100% 1654/1654 [00:08<00:00, 184.96it/s]
Filtering: 100% 3169/3169 [00:08<00:00, 361.26it/s]
Filtering: 100% 3169/3169 [00:08<00:00, 361.96it/s]
Error: No segmented faces found.
Traceback (most recent call last):
  File "/content/drive/My Drive/DeepFaceLab/DeepFaceLab_Colab/mainscripts/Trainer.py", line 58, in trainerThread
    debug=debug)
  File "/content/drive/My Drive/DeepFaceLab/DeepFaceLab_Colab/models/Model_XSeg/Model.py", line 17, in __init__
    super().__init__(*args, force_model_class_name='XSeg', **kwargs)
  File "/content/drive/My Drive/DeepFaceLab/DeepFaceLab_Colab/models/ModelBase.py", line 191, in __init__
    self.on_initialize()
  File "/content/drive/My Drive/DeepFaceLab/DeepFaceLab_Colab/models/Model_XSeg/Model.py", line 135, in on_initialize
    data_format=nn.data_format)
  File "/content/drive/My Drive/DeepFaceLab/DeepFaceLab_Colab/samplelib/SampleGeneratorFaceXSeg.py", line 32, in __init__
    raise Exception(f"No segmented faces found.")
Exception: No segmented faces found.

wangzixin1

谢谢分享

aaa2002911

shaing 发表于 2021-7-14 17:15
3050ti 4g显存 训练quick96报了两个错，除了爆显存外还有什么问题？
Error: 2 root error(s) found.
  (0)  ...

真不知道，不好意思啊亲，你那个我没遇到