Description
🐛 Describe the bug
#258
these cases are target 2.5
-
LossNLL2d has no correct assert
"test_cross_entropy_loss_2d_out_of_bounds_class_index_xpu_float16",
"test_cross_entropy_loss_2d_out_of_bounds_class_index_xpu_float32", - Jianghang -
native_group_norm : RuntimeError: Expected X.is_contiguous(memory_format) to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)
"test_GroupNorm_memory_format_xpu", - Resolve the memory format issue of GroupNorm #677 -
upsamplingNearest2d: Failed: Unexpected success
"test_upsamplingNearest2d_launch_fail_xpu", - grid size check -
do not aline with cuda fix cuda bias code in test_nn #656 fix it
"test_upsamplingBiMode2d_consistency",
"test_upsamplingBiLinear2d_consistency_interp_size_bug", -
cause by cuda hard code
"test_device_mask_xpu", fix cuda bias code in test_nn #656 fix it
"test_overwrite_module_params_on_conversion_cpu_device_xpu",
(https://github.com/pytorch/pytorch/blob/1fb498d6e34e0e9b43b2c26dc0a18a4fc3a52605/aten/src/ATen/native/cuda/UpSampleNearest2d.cu#L303) is specially for cuda, keep in skip list
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