Pytorch:嵌入层后,无法获得 <class 'torch.Tensor'> 的 repr
Pytorch: after embedding layer, Unable to get repr for <class 'torch.Tensor'>
我是 PyTorch 的新手,正在尝试重现该项目:https://github.com/eXascaleInfolab/ActiveLink
但是feedforward()
出现了错误,困扰我好几天了,这里是部分代码(模型的完整代码请看https://github.com/eXascaleInfolab/ActiveLink/blob/master/models.py):
def forward(self, e1, rel, batch_size=None, weights=None):
......
e1_embedded = self.emb_e(e1).view(-1, 1, 10, 20)
rel_embedded = self.emb_rel(rel).view(-1, 1, 10, 20)
stacked_inputs = torch.cat([e1_embedded, rel_embedded], 2) # out: (128L, 1L, 20L, 20L)
这给了我错误(我正在使用 GPU):
THCudaCheck FAIL file=/pytorch/aten/src/THC/generic/THCTensorMath.cu line=196 error=710 : device-side assert triggered
Traceback (most recent call last):
File "main.py", line 147, in <module>
main()
File "main.py", line 136, in main
model = run_meta_incremental(config, model, train_batcher, test_rank_batcher)
File "/home/yonghui/yt/meta_incr_training.py", line 158, in run_meta_incremental
g = run_inner(config, model, task)
File "/home/yonghui/yt/meta_incr_training.py", line 120, in run_inner
pred = model.forward(e1, rel)
File "/home/yonghui/yt/models.py", line 136, in forward
stacked_inputs = torch.cat([e1_embedded, rel_embedded], 2)
RuntimeError: cuda runtime error (710) : device-side assert triggered at /pytorch/aten/src/THC/generic/THCTensorMath.cu:196
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [0,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [1,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [2,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [3,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [4,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [5,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [6,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [7,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
我使用 Debugger 试图找出问题所在:
在e1
和rel
嵌入之前,它们都是int64
中的张量,形状为torch.Size([128, 1])
。
e1
可以正常嵌入,转换为torch.float32
和torch.Size([128, 1, 10, 20])
。然而,在rel
通过emb_rel
的embedding层后,Debugger显示所有tenros为Unable to get repr for <class 'torch.Tensor'>
.
这是怎么回事?我该如何解决?感谢您提供任何可能的帮助!!
错误出现在打印此错误消息之前的某处,可能是在重塑中。
调用视图不会改变底层数据,它只会改变它们的“视图”,而且是懒惰的。如果张量的不同视图是不可能的(例如,因为张量没有连续存储在内存中,参见PyTorch forum),它在应该使用张量内容的第一次场合失败,在你想要 debug-print 张量的情况。
为了调试,考虑将 view
替换为 reshape
(参见 )。
此问题已通过使用调试器并检查输入张量得到解决。
在embedding之前检查张量后,发现有些元素超出了范围,尤其是索引从0开始的情况。
我是 PyTorch 的新手,正在尝试重现该项目:https://github.com/eXascaleInfolab/ActiveLink
但是feedforward()
出现了错误,困扰我好几天了,这里是部分代码(模型的完整代码请看https://github.com/eXascaleInfolab/ActiveLink/blob/master/models.py):
def forward(self, e1, rel, batch_size=None, weights=None):
......
e1_embedded = self.emb_e(e1).view(-1, 1, 10, 20)
rel_embedded = self.emb_rel(rel).view(-1, 1, 10, 20)
stacked_inputs = torch.cat([e1_embedded, rel_embedded], 2) # out: (128L, 1L, 20L, 20L)
这给了我错误(我正在使用 GPU):
THCudaCheck FAIL file=/pytorch/aten/src/THC/generic/THCTensorMath.cu line=196 error=710 : device-side assert triggered
Traceback (most recent call last):
File "main.py", line 147, in <module>
main()
File "main.py", line 136, in main
model = run_meta_incremental(config, model, train_batcher, test_rank_batcher)
File "/home/yonghui/yt/meta_incr_training.py", line 158, in run_meta_incremental
g = run_inner(config, model, task)
File "/home/yonghui/yt/meta_incr_training.py", line 120, in run_inner
pred = model.forward(e1, rel)
File "/home/yonghui/yt/models.py", line 136, in forward
stacked_inputs = torch.cat([e1_embedded, rel_embedded], 2)
RuntimeError: cuda runtime error (710) : device-side assert triggered at /pytorch/aten/src/THC/generic/THCTensorMath.cu:196
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [0,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [1,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [2,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [3,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [4,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [5,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [6,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [189,0,0], thread: [7,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
我使用 Debugger 试图找出问题所在:
在e1
和rel
嵌入之前,它们都是int64
中的张量,形状为torch.Size([128, 1])
。
e1
可以正常嵌入,转换为torch.float32
和torch.Size([128, 1, 10, 20])
。然而,在rel
通过emb_rel
的embedding层后,Debugger显示所有tenros为Unable to get repr for <class 'torch.Tensor'>
.
这是怎么回事?我该如何解决?感谢您提供任何可能的帮助!!
错误出现在打印此错误消息之前的某处,可能是在重塑中。
调用视图不会改变底层数据,它只会改变它们的“视图”,而且是懒惰的。如果张量的不同视图是不可能的(例如,因为张量没有连续存储在内存中,参见PyTorch forum),它在应该使用张量内容的第一次场合失败,在你想要 debug-print 张量的情况。
为了调试,考虑将 view
替换为 reshape
(参见
此问题已通过使用调试器并检查输入张量得到解决。
在embedding之前检查张量后,发现有些元素超出了范围,尤其是索引从0开始的情况。