Hi,
I am porting the code from “Deep Learning with PyTorch” from python to C++ and learning the C++ frontend API at the same time.
I am facing a difficulty when porting this snippet:
loss = nn.CrossEntropyLoss()
input = Variable(torch.randn(3, 5), requires_grad=True) 
target = Variable(torch.LongTensor(3).random_(5)) 
output = loss(input, target)
output.backward()

I have written this:
  auto input2 = torch::randn({3, 5}, torch::requires_grad(true).dtype(torch::kLong));
  auto target2 = torch::tensor({3},torch::kLong).random_(5);
  auto output2 = torch::binary_cross_entropy(input2, target2);
  output2.backward();

It compiles, but I have a runtime exception which says:
terminate called after throwing an instance of 'at::Error'
  what():  normal_ is not implemented for type CPULongType (normal_ at /pytorch/build/aten/src/ATen/TypeDefault.cpp:1652)
frame #0: at::native::randn(at::ArrayRef<long>, at::Generator*, at::TensorOptions const&) + 0x44 (0x7f1ffc68a704 in /home/inglada/local/libtorch/lib/libcaffe2.so)
frame #1: at::native::randn(at::ArrayRef<long>, at::TensorOptions const&) + 0xe (0x7f1ffc68a7be in /home/inglada/local/libtorch/lib/libcaffe2.so)
frame #2: ./Chapter03/chapter03() [0x428c8a]
frame #3: torch::randn(at::ArrayRef<long>, at::TensorOptions const&) + 0x177 (0x42ade2 in ./Chapter03/chapter03)
frame #4: main + 0x20a (0x427494 in ./Chapter03/chapter03)
frame #5: __libc_start_main + 0xf1 (0x7f1ffb7342e1 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: _start + 0x2a (0x42687a in ./Chapter03/chapter03)

I understand that I can not create a normal random tensor with long ints, but if I do
auto input2 = torch::randn({3, 5}, torch::requires_grad(true));
then the exception appears when computing the cross entropy:
terminate called after throwing an instance of 'at::Error'
  what():  Expected object of scalar type Float but got scalar type Long for argument #2 'target' (checked_tensor_unwrap at /pytorch/aten/src/ATen/Utils.h:74)

What can I do to get the same behaviour as in python?
Thank you.