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Add meta support for _adaptive_avg_pool2d_backward (#86359)

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Pull Request resolved: https://github.com/pytorch/pytorch/pull/86359
Approved by: https://github.com/ezyang, https://github.com/albanD
This commit is contained in:
anjali411 2022-10-10 20:28:32 +00:00 committed by PyTorch MergeBot
parent 03d8ab4dec
commit a56a8c0fc0
1 changed files with 20 additions and 0 deletions
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20
torch/_meta_registrations.py
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@ -597,6 +597,26 @@ def meta_adaptive_avg_pool3d(self, output_size):
return self.new_empty(self.shape[:-3] + tuple(output_size))
@register_meta(aten._adaptive_avg_pool2d_backward.default)
def meta__adaptive_avg_pool2d_backward(grad_out, self):
ndim = grad_out.ndim
for i in range(1, ndim):
check(
grad_out.size(i) > 0,
lambda: f"adaptive_avg_pool2d_backward(): Expected grad_output to have non-zero \
size for non-batch dimensions, {grad_out.shape} with dimension {i} being empty",
)
check(
ndim == 3 or ndim == 4,
lambda: f"adaptive_avg_pool2d_backward(): Expected 3D or 4D tensor, but got {self.shape}",
)
check(
self.dtype == grad_out.dtype,
lambda: f"expected dtype {self.dtype} for `grad_output` but got dtype {grad_out.dtype}",
)
return self.new_empty(self.shape)
@register_meta(aten.repeat_interleave.Tensor)
def meta_repeat_interleave_Tensor(repeats, output_size=None):
if output_size is None: