nerfacc.exclusive_prod

nerfacc.exclusive_prod(inputs, packed_info=None)

Exclusive Product that supports flattened tensor.

Similar to nerfacc.inclusive_prod(), but computes the exclusive product.

Parameters:

• inputs (Tensor) – The tensor to be producted. Can be either a N-D tensor, or a flattened tensor with packed_info specified.

• packed_info (Optional[Tensor]) – A tensor of shape (n_rays, 2) that specifies the start and count of each chunk in the flattened input tensor, with in total n_rays chunks. If None, the input is assumed to be a N-D tensor and the product is computed along the last dimension. Default is None.

Returns:

The exclusive product with the same shape as the input tensor.

Return type:

Tensor

Example:

>>> inputs = torch.tensor([1., 2., 3., 4., 5., 6., 7., 8., 9.], device="cuda")
>>> packed_info = torch.tensor([[0, 2], [2, 3], [5, 4]], device="cuda")
>>> exclusive_prod(inputs, packed_info)
tensor([1., 1., 1., 3., 12., 1., 6., 42., 336.], device='cuda:0')