刚换的3080，也下载的30系软件，训练的时候就报错，

y8235563

星级打分

• 1
• 2
• 3
• 4
• 5

平均分:NAN  参与人数:0  我的评分:未评

aceLab\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. This isn't available when running in Eager mode.


Errors may have originated from an input operation.
Input Source operations connected to node gradients/Conv2D_18_grad/Conv2DBackpropInput:
decoder_src/res2/conv2/weight/read (defined at E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:61)

Original stack trace for 'gradients/Conv2D_18_grad/Conv2DBackpropInput':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
    self.on_initialize()
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 547, in on_initialize
    gpu_G_loss_gvs += [ nn.gradients ( gpu_G_loss, self.src_dst_trainable_weights )]
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\ops\__init__.py", line 55, in tf_gradients
    grads = gradients.gradients(loss, vars, colocate_gradients_with_ops=True )
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 172, in gradients
    unconnected_gradients)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 682, in _GradientsHelper
    lambda: grad_fn(op, *out_grads))
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 338, in _MaybeCompile
    return grad_fn()  # Exit early
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 682, in <lambda>
    lambda: grad_fn(op, *out_grads))
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_grad.py", line 590, in _Conv2DGrad
    data_format=data_format),
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1291, in conv2d_backprop_input
    name=name)
  File "E:\RTX30\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:\RTX30\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:\RTX30\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)

...which was originally created as op 'Conv2D_18', defined at:
  File "threading.py", line 884, in _bootstrap
[elided 3 identical lines from previous traceback]
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
    self.on_initialize()
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 409, in on_initialize
    gpu_pred_src_src, gpu_pred_src_srcm = self.decoder_src(gpu_src_code)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 226, in forward
    x = self.res2(x)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 84, in forward
    x = self.conv2(x)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_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 "E:\RTX30\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:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2397, in conv2d
    name=name)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_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 "E:\RTX30\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)

Traceback (most recent call last):
  File "E:\RTX30\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:\RTX30\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:\RTX30\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: OOM when allocating tensor with shape[8,144,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node gradients/Conv2D_18_grad/Conv2DBackpropInput}}]]
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.


During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 131, in trainerThread
    iter, iter_time = model.train_one_iter()
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 480, in train_one_iter
    losses = self.onTrainOneIter()
  File "E:\RTX30\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:\RTX30\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:\RTX30\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:\RTX30\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:\RTX30\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:\RTX30\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: OOM when allocating tensor with shape[8,144,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node gradients/Conv2D_18_grad/Conv2DBackpropInput (defined at E:\RTX30\DFL_maozhihanhua_RTX3000\_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. This isn't available when running in Eager mode.


Errors may have originated from an input operation.
Input Source operations connected to node gradients/Conv2D_18_grad/Conv2DBackpropInput:
decoder_src/res2/conv2/weight/read (defined at E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:61)

Original stack trace for 'gradients/Conv2D_18_grad/Conv2DBackpropInput':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
    self.on_initialize()
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 547, in on_initialize
    gpu_G_loss_gvs += [ nn.gradients ( gpu_G_loss, self.src_dst_trainable_weights )]
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\ops\__init__.py", line 55, in tf_gradients
    grads = gradients.gradients(loss, vars, colocate_gradients_with_ops=True )
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 172, in gradients
    unconnected_gradients)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 682, in _GradientsHelper
    lambda: grad_fn(op, *out_grads))
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 338, in _MaybeCompile
    return grad_fn()  # Exit early
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 682, in <lambda>
    lambda: grad_fn(op, *out_grads))
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_grad.py", line 590, in _Conv2DGrad
    data_format=data_format),
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1291, in conv2d_backprop_input
    name=name)
  File "E:\RTX30\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:\RTX30\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:\RTX30\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)

...which was originally created as op 'Conv2D_18', defined at:
  File "threading.py", line 884, in _bootstrap
[elided 3 identical lines from previous traceback]
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
    self.on_initialize()
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 409, in on_initialize
    gpu_pred_src_src, gpu_pred_src_srcm = self.decoder_src(gpu_src_code)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 226, in forward
    x = self.res2(x)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 84, in forward
    x = self.conv2(x)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_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 "E:\RTX30\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:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2397, in conv2d
    name=name)
  File "E:\RTX30\DFL_maozhihanhua_RTX3000\_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 "E:\RTX30\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)

y8235563

30系和10.20的MD是通用的吗？

sd4981480

显卡驱动更新了吗？建议你下载一个1120原版和猫神的汉化版一起测试下，看是否都有问题……如果显卡驱动是最新的，那大概率就是版本或模型问题了，建议每个版本新开模型，参数放最低试试看。（简单来说就是排查下显卡驱动、模型、软件版本）……

huxiansheng

不懂帮顶

guoruoxuan

路过学习一下

tianming

3080显存太拉跨了吧，参数开小点？

471610

解决了吗？

wang769

下载猫的最新汉化版，驱动去官网下，还要下cuad

cld521

环境没安装？

wcw888

rg版试试