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加入金鱼的补全在加五彩的丹192丹后出现了错位求大佬帮.....

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 楼主| 发表于 2022-6-7 02:41:20 | 显示全部楼层 |阅读模式
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Error: OOM when allocating tensor with shape[1152,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_35 (defined at F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87) ]]
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.

         [[node concat_1 (defined at F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:563) ]]
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.


Caused by op 'Pad_35', defined at:
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
    self.on_initialize()
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 410, in on_initialize
    gpu_pred_dst_dst, gpu_pred_dst_dstm = self.decoder_dst(gpu_dst_code)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 226, in forward
    x = self.res2(x)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 82, in forward
    x = self.conv1(inp)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 87, in forward
    x = tf.pad (x, padding, mode='CONSTANT')
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\array_ops.py", line 2299, in pad
    result = gen_array_ops.pad(tensor, paddings, name=name)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 5539, in pad
    "Pad", input=input, paddings=paddings, name=name)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
    op_def=op_def)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3300, in create_op
    op_def=op_def)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 1801, in __init__
    self._traceback = tf_stack.extract_stack()

ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[1152,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_35 (defined at F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87) ]]
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.

         [[node concat_1 (defined at F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:563) ]]
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.


Traceback (most recent call last):
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1334, in _do_call
    return fn(*args)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1319, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1407, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[1152,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node Pad_35}}]]
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.

         [[{{node concat_1}}]]
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.


During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py", line 131, in trainerThread
    iter, iter_time = model.train_one_iter()
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\ModelBase.py", line 480, in train_one_iter
    losses = self.onTrainOneIter()
  File "F:\DFL_maozhihanhua_RTX2080Ti\_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 "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 584, in src_dst_train
    self.target_dstm_em:target_dstm_em,
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 929, in run
    run_metadata_ptr)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1152, in _run
    feed_dict_tensor, options, run_metadata)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1328, in _do_run
    run_metadata)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1348, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[1152,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_35 (defined at F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87) ]]
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.

         [[node concat_1 (defined at F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:563) ]]
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.


Caused by op 'Pad_35', defined at:
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
    self.on_initialize()
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 410, in on_initialize
    gpu_pred_dst_dst, gpu_pred_dst_dstm = self.decoder_dst(gpu_dst_code)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 226, in forward
    x = self.res2(x)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 82, in forward
    x = self.conv1(inp)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 87, in forward
    x = tf.pad (x, padding, mode='CONSTANT')
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\array_ops.py", line 2299, in pad
    result = gen_array_ops.pad(tensor, paddings, name=name)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 5539, in pad
    "Pad", input=input, paddings=paddings, name=name)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
    op_def=op_def)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3300, in create_op
    op_def=op_def)
  File "F:\DFL_maozhihanhua_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 1801, in __init__
    self._traceback = tf_stack.extract_stack()

ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[1152,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_35 (defined at F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87) ]]
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.

         [[node concat_1 (defined at F:\DFL_maozhihanhua_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py:563) ]]
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.

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发表于 2022-6-7 21:30:39 | 显示全部楼层
aicaowlf 发表于 2022-6-7 20:25
谢谢大佬,萌新能方便跟我说说怎么调低参数吗?用的是猫神的汉化

把本页面拉到最上面,左上角的大图上有两行字,看第二行
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发表于 2022-6-7 05:15:45 | 显示全部楼层
这与金鱼的图关系不大,OOM就是显存或内存不足。调一下参数吧。
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万事如意节日勋章

发表于 2022-6-7 08:08:24 | 显示全部楼层
学习观摩一下各位大佬!!!!
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发表于 2022-6-7 08:19:46 | 显示全部楼层
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发表于 2022-6-7 08:52:20 | 显示全部楼层
OOM=out of memory,就是内存太小
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发表于 2022-6-7 09:23:39 | 显示全部楼层
学习观摩一下各位大佬!!!!
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发表于 2022-6-7 10:07:50 | 显示全部楼层
看见OOM就是显存不足啦
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发表于 2022-6-7 13:16:59 | 显示全部楼层
显存不足,调低参数或者换大显存显卡
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 楼主| 发表于 2022-6-7 20:25:27 | 显示全部楼层
WinKK 发表于 2022-6-7 05:15
这与金鱼的图关系不大,OOM就是显存或内存不足。调一下参数吧。

谢谢大佬,萌新能方便跟我说说怎么调低参数吗?用的是猫神的汉化
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