I am trying to run a LeNET over my dataset of images containing 128*128 size.
MY model info is like this:
LeNet(
(conv1): Conv2d(3, 6, kernel_size=(5, 5), stride=(1, 1))
(pool): MaxPool2d(kernel_size=(2, 2), stride=(2, 2), dilation=(1, 1), ceil_mode=False)
(conv2): Conv2d(6, 16, kernel_size=(5, 5), stride=(1, 1))
(fc1): Linear(in_features=400, out_features=120, bias=True)
(fc2): Linear(in_features=120, out_features=84, bias=True)
(fc3): Linear(in_features=84, out_features=10, bias=True)
)
Traceback (most recent call last):
File “cnn.py”, line 88, in 
for data in trainLoader:
File “/home/jessie-pinkman/anaconda2/lib/python2.7/site-packages/torch/utils/data/dataloader.py”, line 281, in next
return self._process_next_batch(batch)
File “/home/jessie-pinkman/anaconda2/lib/python2.7/site-packages/torch/utils/data/dataloader.py”, line 301, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
RuntimeError: Traceback (most recent call last):
File “/home/jessie-pinkman/anaconda2/lib/python2.7/site-packages/torch/utils/data/dataloader.py”, line 55, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File “/home/jessie-pinkman/anaconda2/lib/python2.7/site-packages/torch/utils/data/dataloader.py”, line 135, in default_collate
return [default_collate(samples) for samples in transposed]
File “/home/jessie-pinkman/anaconda2/lib/python2.7/site-packages/torch/utils/data/dataloader.py”, line 112, in default_collate
return torch.stack(batch, 0, out=out)
File “/home/jessie-pinkman/anaconda2/lib/python2.7/site-packages/torch/functional.py”, line 66, in stack
return torch.cat(inputs, dim, out=out)
RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 0. Got 32 and 48 in dimension 3 at /opt/conda/conda-bld/pytorch_1518238581238/work/torch/lib/TH/generic/THTensorMath.c:2897
I need some help…Thank you .