I read all posts regarding the same problem but couldn’t figure my error out.
def main(A, B, num_epochs):
    n = A.shape[0]
    dim = A.shape[1]
    C = range(0, n - 1)
    train_loader = zip(A, B, C)

    # Training the Model
    for epoch in range(num_epochs):
        shuffle(train_loader)
        for (x, y,  i) in train_loader:
            x = Variable(torch.FloatTensor(x), requires_grad=False)
            y = Variable(torch.FloatTensor(y), requires_grad=False)

RuntimeError: already counted a million dimensions in a given sequence. Most likely your items are also sequences and there’s no way to infer how many dimension should the tensor have
The error occurs when calling
            x = Variable(torch.FloatTensor(x), requires_grad=False)

I also tried:
            x = Variable(torch.FloatTensor(x).data, requires_grad=False)

which resulted in the same error.
The reason I added x conversion to torch because otherwise I get this error:
            x = Variable(x, requires_grad=False)

RuntimeError: Variable data has to be a tensor, but got matrix
x.shape and y.shape are (1,300)