I think if you comment these two lines and then print train_set data size
# train_set.data.unsqueeze_(1)                                                                                                                                                                 
# train_set.data = train_set.data.repeat(1, 3, 1, 1)
print(train_set.data.size())

gives
torch.Size([60000, 28, 28])

then if you
print(x.shape)

this gives
torch.Size([24, 1, 32, 32])

fashion mnist dataset has 1 channel images of size 28x28, which we resized to 32x32.
Resize has no issue, it works as it should.
I think if you want 3x32x32, then you will have to pass these images through
c = nn.Conv2d(in_channels=1, out_channels=3, kernel_size=1)
c(x).shape

gives
torch.Size([24, 3, 32, 32])