(fun, in1, in2)
| 121 | |
| 122 | |
| 123 | def pytorch_adapter(fun, in1, in2): |
| 124 | with torch.cuda.stream(torch_stream): |
| 125 | tin1 = [torch_dlpack.from_dlpack(dltensor) for dltensor in in1] |
| 126 | tin2 = [torch_dlpack.from_dlpack(dltensor) for dltensor in in2] |
| 127 | tout1, tout2 = fun(tin1, tin2) |
| 128 | out1, out2 = [torch_dlpack.to_dlpack(tout) for tout in tout1], [ |
| 129 | torch_dlpack.to_dlpack(tout) for tout in tout2 |
| 130 | ] |
| 131 | torch_stream.synchronize() |
| 132 | return out1, out2 |
| 133 | |
| 134 | |
| 135 | def pytorch_wrapper(fun): |
no test coverage detected