炼丹报错问题

眼鼻嘴666

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平均分:NAN  参与人数:0  我的评分:未评

不论是用别人的丹，还是自己从零开始训练，都出现下面这些代码，这是什么情况？
  (0) Resource exhausted: OOM when allocating tensor with shape[576,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_31 (defined at \DeepFaceLabRG\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.

         [[concat/concat/_363]]
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[576,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_31 (defined at \DeepFaceLabRG\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.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node Pad_31:
IdentityN_20 (defined at \DeepFaceLabRG\core\leras\ops\__init__.py:33)

Input Source operations connected to node Pad_31:
IdentityN_20 (defined at \DeepFaceLabRG\core\leras\ops\__init__.py:33)

Original stack trace for 'Pad_31':
  File "\python-3.8.5\lib\threading.py", line 890, in _bootstrap
    self._bootstrap_inner()
  File "\python-3.8.5\lib\threading.py", line 932, in _bootstrap_inner
    self.run()
  File "\python-3.8.5\lib\threading.py", line 870, in run
    self._target(*self._args, **self._kwargs)
  File "\DeepFaceLabRG\mainscripts\Trainer.py", line 45, in trainerThread
    model = models.import_model(model_class_name)(
  File "\DeepFaceLabRG\models\ModelBase.py", line 195, in __init__
    self.on_initialize()
  File "\DeepFaceLabRG\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 "\DeepFaceLabRG\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 33, in inner
    return call_and_grad(*inputs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 261, in __call__
    return self._d(self._f, a, k)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 217, in decorated
    return _graph_mode_decorator(wrapped, args, kwargs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 330, in _graph_mode_decorator
    result, grad_fn = f(*args)
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 20, in call_and_grad
    outputs = kernel_call()
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 19, in kernel_call
    return call(self, *inputs, **kwargs)
  File "\DeepFaceLabRG\core\leras\archis\DeepFakeArchi.py", line 230, in forward
    x = self.res2(x)
  File "\DeepFaceLabRG\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 33, in inner
    return call_and_grad(*inputs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 261, in __call__
    return self._d(self._f, a, k)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 217, in decorated
    return _graph_mode_decorator(wrapped, args, kwargs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 330, in _graph_mode_decorator
    result, grad_fn = f(*args)
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 20, in call_and_grad
    outputs = kernel_call()
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 19, in kernel_call
    return call(self, *inputs, **kwargs)
  File "\DeepFaceLabRG\core\leras\archis\DeepFakeArchi.py", line 84, in forward
    x = self.conv1(inp)
  File "\DeepFaceLabRG\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "\DeepFaceLabRG\core\leras\layers\Conv2D.py", line 87, in forward
    x = tf.pad (x, padding, mode='CONSTANT')
  File "\python-3.8.5\lib\site-packages\tensorflow\python\util\dispatch.py", line 206, in wrapper
    return target(*args, **kwargs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\array_ops.py", line 3514, in pad
    result = gen_array_ops.pad(tensor, paddings, name=name)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 6503, in pad
    _, _, _op, _outputs = _op_def_library._apply_op_helper(
  File "\python-3.8.5\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 748, in _apply_op_helper
    op = g._create_op_internal(op_type_name, inputs, dtypes=None,
  File "\python-3.8.5\lib\site-packages\tensorflow\python\framework\ops.py", line 3557, in _create_op_internal
    ret = Operation(
  File "\python-3.8.5\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 "F:\DeepFaceLab\_internal\python-3.8.5\lib\site-packages\tensorflow\python\client\session.py", line 1375, in _do_call
    return fn(*args)
  File "F:\DeepFaceLab\_internal\python-3.8.5\lib\site-packages\tensorflow\python\client\session.py", line 1359, in _run_fn
    return self._call_tf_sessionrun(options, feed_dict, fetch_list,
  File "F:\DeepFaceLab\_internal\python-3.8.5\lib\site-packages\tensorflow\python\client\session.py", line 1451, in _call_tf_sessionrun
    return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: OOM when allocating tensor with shape[576,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node Pad_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.

         [[concat/concat/_363]]
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[576,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node Pad_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 "F:\DeepFaceLab\_internal\DeepFaceLabRG\mainscripts\Trainer.py", line 130, in trainerThread
    iter, iter_time = model.train_one_iter()
  File "F:\DeepFaceLab\_internal\DeepFaceLabRG\models\ModelBase.py", line 476, in train_one_iter
    losses = self.onTrainOneIter()
  File "F:\DeepFaceLab\_internal\DeepFaceLabRG\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:\DeepFaceLab\_internal\DeepFaceLabRG\models\Model_SAEHD\Model.py", line 576, in src_dst_train
    s, d = nn.tf_sess.run ( [ src_loss, dst_loss, src_dst_loss_gv_op],
  File "F:\DeepFaceLab\_internal\python-3.8.5\lib\site-packages\tensorflow\python\client\session.py", line 967, in run
    result = self._run(None, fetches, feed_dict, options_ptr,
  File "F:\DeepFaceLab\_internal\python-3.8.5\lib\site-packages\tensorflow\python\client\session.py", line 1190, in _run
    results = self._do_run(handle, final_targets, final_fetches,
  File "F:\DeepFaceLab\_internal\python-3.8.5\lib\site-packages\tensorflow\python\client\session.py", line 1368, in _do_run
    return self._do_call(_run_fn, feeds, fetches, targets, options,
  File "F:\DeepFaceLab\_internal\python-3.8.5\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[576,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_31 (defined at \DeepFaceLabRG\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.

         [[concat/concat/_363]]
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[576,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_31 (defined at \DeepFaceLabRG\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.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node Pad_31:
IdentityN_20 (defined at \DeepFaceLabRG\core\leras\ops\__init__.py:33)

Input Source operations connected to node Pad_31:
IdentityN_20 (defined at \DeepFaceLabRG\core\leras\ops\__init__.py:33)

Original stack trace for 'Pad_31':
  File "\python-3.8.5\lib\threading.py", line 890, in _bootstrap
    self._bootstrap_inner()
  File "\python-3.8.5\lib\threading.py", line 932, in _bootstrap_inner
    self.run()
  File "\python-3.8.5\lib\threading.py", line 870, in run
    self._target(*self._args, **self._kwargs)
  File "\DeepFaceLabRG\mainscripts\Trainer.py", line 45, in trainerThread
    model = models.import_model(model_class_name)(
  File "\DeepFaceLabRG\models\ModelBase.py", line 195, in __init__
    self.on_initialize()
  File "\DeepFaceLabRG\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 "\DeepFaceLabRG\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 33, in inner
    return call_and_grad(*inputs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 261, in __call__
    return self._d(self._f, a, k)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 217, in decorated
    return _graph_mode_decorator(wrapped, args, kwargs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 330, in _graph_mode_decorator
    result, grad_fn = f(*args)
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 20, in call_and_grad
    outputs = kernel_call()
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 19, in kernel_call
    return call(self, *inputs, **kwargs)
  File "\DeepFaceLabRG\core\leras\archis\DeepFakeArchi.py", line 230, in forward
    x = self.res2(x)
  File "\DeepFaceLabRG\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 33, in inner
    return call_and_grad(*inputs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 261, in __call__
    return self._d(self._f, a, k)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 217, in decorated
    return _graph_mode_decorator(wrapped, args, kwargs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\custom_gradient.py", line 330, in _graph_mode_decorator
    result, grad_fn = f(*args)
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 20, in call_and_grad
    outputs = kernel_call()
  File "\DeepFaceLabRG\core\leras\ops\__init__.py", line 19, in kernel_call
    return call(self, *inputs, **kwargs)
  File "\DeepFaceLabRG\core\leras\archis\DeepFakeArchi.py", line 84, in forward
    x = self.conv1(inp)
  File "\DeepFaceLabRG\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "\DeepFaceLabRG\core\leras\layers\Conv2D.py", line 87, in forward
    x = tf.pad (x, padding, mode='CONSTANT')
  File "\python-3.8.5\lib\site-packages\tensorflow\python\util\dispatch.py", line 206, in wrapper
    return target(*args, **kwargs)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\array_ops.py", line 3514, in pad
    result = gen_array_ops.pad(tensor, paddings, name=name)
  File "\python-3.8.5\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 6503, in pad
    _, _, _op, _outputs = _op_def_library._apply_op_helper(
  File "\python-3.8.5\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 748, in _apply_op_helper
    op = g._create_op_internal(op_type_name, inputs, dtypes=None,
  File "\python-3.8.5\lib\site-packages\tensorflow\python\framework\ops.py", line 3557, in _create_op_internal
    ret = Operation(
  File "\python-3.8.5\lib\site-packages\tensorflow\python\framework\ops.py", line 2045, in __init__
    self._traceback = tf_stack.extract_stack_for_node(self._c_op)

wtxx8888

显卡显存不满足需求爆了，需要降低降低BS。

00M提示即为爆显存。

眼鼻嘴666

wtxx8888 发表于 2022-6-18 17:38
显卡显存不满足需求爆了，需要降低降低BS。

00M提示即为爆显存。

bs都调到2了

wtxx8888

眼鼻嘴666 发表于 2022-6-18 19:04
bs都调到2了

BS2都不行，这就不是你配置能用的丹。换小的吧