(grad, grad_indices, values)
| 98 | # |
| 99 | |
| 100 | def _make_sparse(grad, grad_indices, values): |
| 101 | size = grad.size() |
| 102 | if grad_indices.numel() == 0 or values.numel() == 0: |
| 103 | return torch.empty_like(grad) |
| 104 | return torch.sparse_coo_tensor(grad_indices, values, size) |
| 105 | |
| 106 | # We don't support sparse gradients |
| 107 | param = torch.arange(8).reshape(2, 4).float() |
no outgoing calls
no test coverage detected