Value Error(): Empty tensor

[sriharsha0806 (Sriharsha Annamaneni)]

pytorch version 0.3

Conv2d_mask[group_index_in*g_size_out: (group_index_out + 1)g_size_out, group_index_ing_size_in:(group_index_in+1)*g_size_in, :, :] = 1.
ValueError: result of slicing is an empty tensor

May I know the reason for the following error,

I have checked the following post but I did not understand?

Result of slicing is an empty tensor

Hi, I am trying to create a variable-length sequence for a LSTM. Can anyone help me understand why this code works: lens = list(range(170,1,-1)) xs = Variable(torch.randn(169, 200, 1)) packed = torch.nn.utils.rnn.pack_padded_sequence(xs, lens, batch_first=True) and this code does not: lens = [294, 289, 288, 282, 273, 270, 261, 260, 240, 235, 231, 228, 228, 227, 226, 226, 199, 195, 194, 192, 190, 189, 177, 176, 165, 165, 161, 156, 153, 149, 149, 142, 142, 137, 136, 136, 135, 134, 134, 132, 1…

[ptrblck]

Could you post an executable code snippet?
Also I would suggest to upgrade PyTorch to 0.4.0 and see, if this error still occurs.

[sriharsha0806 (Sriharsha Annamaneni)]

The issue has been resolved. How to initialize the convolutional weights for different instances of same model? I don’t want to use copy

[ptrblck]

Just apply the weight_init with each instance:

model1 = Net()
model1.apply(weight_init)
model2 = Net()
model2.apply(weight_init)

Or would you like use the same initialized weights?
If so, you could copy the state_dict.