(ctx, X, weight)
| 61 | class Conv2D(torch.autograd.Function): |
| 62 | @staticmethod |
| 63 | def forward(ctx, X, weight): |
| 64 | ctx.save_for_backward(X, weight) |
| 65 | return F.conv2d(X, weight) |
| 66 | |
| 67 | # Use @once_differentiable by default unless we intend to double backward |
| 68 | @staticmethod |
nothing calls this directly
no outgoing calls
no test coverage detected