MGT.py文件里的第87,88行“inputs_extras_embedding = torch.cat([self.embedding_modulesi
for i in range(len(self.num_embeddings))] + [inputs_pe], dim=-1)”
代码报错,报错详情如下:
---------- Training ----------
num_samples: 1188, num_batches: 594
0%| | 0/594 [00:00<?, ?it/s]Traceback (most recent call last):
File "F:/orginalCode/MGT-main/main.py", line 236, in
train(args, logger)
File "F:/orginalCode/MGT-main/main.py", line 156, in train
criterion, optimizer, scheduler, args)
File "F:/orginalCode/MGT-main/main.py", line 91, in train_epoch
outputs = model(inputs, targets, *extras, statics)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(*input, *kwargs)
File "F:\orginalCode\MGT-main\models\MGT.py", line 503, in forward
z_inputs, z_targets = self.temporal_embedding(extras) # (B, P, d_model), (B, Q, d_model)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(input, kwargs)
File "F:\orginalCode\MGT-main\models\MGT.py", line 88, in forward
for i in range(len(self.num_embeddings))] + [inputs_pe], dim=-1)
File "F:\orginalCode\MGT-main\models\MGT.py", line 88, in
for i in range(len(self.num_embeddings))] + [inputs_pe], dim=-1)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\modules\sparse.py", line 126, in forward
self.norm_type, self.scale_grad_by_freq, self.sparse)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\functional.py", line 1852, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
TypeError: embedding(): argument 'indices' (position 2) must be Tensor, not list
0%| | 0/594 [00:13<?, ?it/s]
MGT.py文件里的第87,88行“inputs_extras_embedding = torch.cat([self.embedding_modulesi for i in range(len(self.num_embeddings))] + [inputs_pe], dim=-1)” 代码报错,报错详情如下:
---------- Training ---------- num_samples: 1188, num_batches: 594 0%| | 0/594 [00:00<?, ?it/s]Traceback (most recent call last): File "F:/orginalCode/MGT-main/main.py", line 236, in
train(args, logger)
File "F:/orginalCode/MGT-main/main.py", line 156, in train
criterion, optimizer, scheduler, args)
File "F:/orginalCode/MGT-main/main.py", line 91, in train_epoch
outputs = model(inputs, targets, *extras, statics)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(*input, *kwargs)
File "F:\orginalCode\MGT-main\models\MGT.py", line 503, in forward
z_inputs, z_targets = self.temporal_embedding(extras) # (B, P, d_model), (B, Q, d_model)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(input, kwargs)
File "F:\orginalCode\MGT-main\models\MGT.py", line 88, in forward
for i in range(len(self.num_embeddings))] + [inputs_pe], dim=-1)
File "F:\orginalCode\MGT-main\models\MGT.py", line 88, in
for i in range(len(self.num_embeddings))] + [inputs_pe], dim=-1)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\modules\sparse.py", line 126, in forward
self.norm_type, self.scale_grad_by_freq, self.sparse)
File "D:\programfiles\Anaconda3\lib\site-packages\torch\nn\functional.py", line 1852, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
TypeError: embedding(): argument 'indices' (position 2) must be Tensor, not list
0%| | 0/594 [00:13<?, ?it/s]
Process finished with exit code 1