小白求助！训练没有预览是什么情况

a13570273863 · 发表于 2024-3-6 01:15:23

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模型名字: WF 320 DF-UD_SAEHD

               当前迭代: 237912

----------------------模型选项----------------------

         resolution: 320
         face_type: wf
   models_opt_on_gpu: True
               archi: df-ud
            ae_dims: 256
            e_dims: 64
            d_dims: 64
         d_mask_dims: 22
   masked_training: True
         uniform_yaw: True
         lr_dropout: y
         random_warp: False
         gan_power: 0.1
   true_face_power: 0.1
   face_style_power: 0.0
      bg_style_power: 0.0
            ct_mode: none
            clipgrad: True
            pretrain: False
   autobackup_hour: 0
write_preview_history: False
         target_iter: 0
         random_flip: True
         batch_size: 4
   eyes_mouth_prio: True
         adabelief: True
   random_src_flip: True
   random_dst_flip: True
      gan_patch_size: 80
            gan_dims: 32
      blur_out_mask: False
   random_hsv_power: 0.0

----------------------运行信息----------------------

               设备编号: 0
               设备名称: NVIDIA GeForce RTX 3070
               显存大小: 5.32GB

Error: 2 root error(s) found.
  (0) Resource exhausted: failed to allocate memory
      [[node sub_19 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:487) ]]
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. This isn't available when running in Eager mode.

      [[concat_17/concat/_1715]]
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. This isn't available when running in Eager mode.

  (1) Resource exhausted: failed to allocate memory
      [[node sub_19 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:487) ]]
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. This isn't available when running in Eager mode.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node sub_19:
mul_5 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:448)
mul_10 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:456)

Input Source operations connected to node sub_19:
mul_5 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:448)
mul_10 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:456)

Original stack trace for 'sub_19':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
debug=debug)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
self.on_initialize()
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 487, in on_initialize
gpu_dst_loss += tf.reduce_mean ( 10*tf.square(  gpu_target_dst_masked_opt- gpu_pred_dst_dst_masked_opt ), axis=[1,2,3])
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1367, in binary_op_wrapper
return func(x, y, name=name)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 206, in wrapper
return target(*args, **kwargs)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 548, in subtract
return gen_math_ops.sub(x, y, name)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 10653, in sub
"Sub", x=x, y=y, name=name)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_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 "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3569, in _create_op_internal
op_def=op_def)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 2045, in __init__
self._traceback = tf_stack.extract_stack_for_node(self._c_op)

Traceback (most recent call last):
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1375, in _do_call
return fn(*args)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1360, in _run_fn
target_list, run_metadata)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_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: failed to allocate memory
      [[{{node sub_19}}]]
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. This isn't available when running in Eager mode.

      [[concat_17/concat/_1715]]
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. This isn't available when running in Eager mode.

  (1) Resource exhausted: failed to allocate memory
      [[{{node sub_19}}]]
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. This isn't available when running in Eager mode.

0 successful operations.
0 derived errors ignored.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 131, in trainerThread
iter, iter_time = model.train_one_iter()
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 480, in train_one_iter
losses = self.onTrainOneIter()
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 774, 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 "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 584, in src_dst_train
self.target_dstm_em:target_dstm_em,
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 968, in run
run_metadata_ptr)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1191, in _run
feed_dict_tensor, options, run_metadata)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1369, in _do_run
run_metadata)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_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)  # pylint: disable=no-value-for-parameter
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: failed to allocate memory
      [[node sub_19 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:487) ]]
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. This isn't available when running in Eager mode.

      [[concat_17/concat/_1715]]
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. This isn't available when running in Eager mode.

  (1) Resource exhausted: failed to allocate memory
      [[node sub_19 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:487) ]]
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. This isn't available when running in Eager mode.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node sub_19:
mul_5 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:448)
mul_10 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:456)

Input Source operations connected to node sub_19:
mul_5 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:448)
mul_10 (defined at E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:456)

Original stack trace for 'sub_19':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
debug=debug)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
self.on_initialize()
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 487, in on_initialize
gpu_dst_loss += tf.reduce_mean ( 10*tf.square(  gpu_target_dst_masked_opt- gpu_pred_dst_dst_masked_opt ), axis=[1,2,3])
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1367, in binary_op_wrapper
return func(x, y, name=name)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 206, in wrapper
return target(*args, **kwargs)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 548, in subtract
return gen_math_ops.sub(x, y, name)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 10653, in sub
"Sub", x=x, y=y, name=name)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_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 "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3569, in _create_op_internal
op_def=op_def)
  File "E:\AI\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 2045, in __init__
self._traceback = tf_stack.extract_stack_for_node(self._c_op)

这是啥意思，内存吗？以前用原版可以正常使用，现在换了汉化版DFL就这样了