Traceback (most recent call last):
File "E:\中国四维\四维世景科技(北京)有限公司\AI学习\YOLOv12\YOLOv12-train.py", line 37, in <module>
model.train(
File "D:\X\Anaconda\Lib\site-packages\ultralytics\engine\model.py", line 800, in train
self.trainer.train()
File "D:\X\Anaconda\Lib\site-packages\ultralytics\engine\trainer.py", line 235, in train
self._do_train()
File "D:\X\Anaconda\Lib\site-packages\ultralytics\engine\trainer.py", line 423, in _do_train
loss, self.loss_items = self.model(batch)
^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\tasks.py", line 138, in forward
return self.loss(x, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\tasks.py", line 338, in loss
preds = self.forward(batch["img"])
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\tasks.py", line 139, in forward
return self.predict(x, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\tasks.py", line 157, in predict
return self._predict_once(x, profile, visualize, embed)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\tasks.py", line 180, in _predict_once
x = m(x) # run
^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\modules\block.py", line 318, in forward
y.extend(m(y[-1]) for m in self.m)
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\modules\block.py", line 318, in <genexpr>
y.extend(m(y[-1]) for m in self.m)
^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\modules\block.py", line 353, in forward
return self.cv3(torch.cat((self.m(self.cv1(x)), self.cv2(x)), 1))
^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
: 0% ──────────── 0/1 0.2s
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\container.py", line 240, in forward
input = module(input)
^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\modules\block.py", line 495, in forward
return x + self.cv2(self.cv1(x)) if self.add else self.cv2(self.cv1(x))
^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\ultralytics\nn\modules\conv.py", line 81, in forward
return self.act(self.bn(self.conv(x)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\modules\activation.py", line 432, in forward
return F.silu(input, inplace=self.inplace)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\X\Anaconda\Lib\site-packages\torch\nn\functional.py", line 2379, in silu
return torch._C._nn.silu_(input)
^^^^^^^^^^^^^^^^^^^^^^^^^
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 30.00 MiB. GPU 0 has a total capacity of 4.00 GiB of which 14.64 MiB is free. Of the allocated memory 2.22 GiB is allocated by PyTorch, and 37.32 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variable如何解决