pytorch

6d62134f - fix aminmax output resize issue when input is a zero dimension tensor (#96171)

fix aminmax output resize issue when input is a zero dimension tensor (#96171) Fix https://github.com/pytorch/pytorch/issues/96042 ### before ``` >>> torch.aminmax(torch.tensor(1, device='cpu'), dim=0, keepdim=True) __main__:1: UserWarning: An output with one or more elements was resized since it had shape [], which does not match the required output shape [1]. This behavior is deprecated, and in a future PyTorch release outputs will not be resized unless they have zero elements. You can explicitly reuse an out tensor t by resizing it, inplace, to zero elements with t.resize_(0). (Triggered internally at ../aten/src/ATen/native/Resize.cpp:24.) torch.return_types.aminmax( min=tensor([1]), max=tensor([1])) >>> torch.aminmax(torch.tensor(1, device='cpu'), dim=0, keepdim=False) torch.return_types.aminmax( min=tensor(1), max=tensor(1)) ``` ### after ``` >>> torch.aminmax(torch.tensor(1, device='cpu'), dim=0, keepdim=True) torch.return_types.aminmax( min=tensor(1), max=tensor(1)) >>> torch.aminmax(torch.tensor(1, device='cpu'), dim=0, keepdim=False) torch.return_types.aminmax( min=tensor(1), max=tensor(1)) ``` Marked the following test as expected_fail: `test_vmap.py TestVmapOperatorsOpInfoCPU.test_op_has_batch_rule_aminmax_cpu_float32` Given input shape of (2), the loop out is shape (2), the batched vmap out is (2, 1), which mismatched. The loop out will calculate twice on a tensor shape of ( ): without this patch, the output is (1), and then stacked into (2, 1); with this patch, the output is ( ), then stacked into (2). Pull Request resolved: https://github.com/pytorch/pytorch/pull/96171 Approved by: https://github.com/jgong5, https://github.com/ngimel, https://github.com/zou3519