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Summary: ## Context Bins are used in mipnerf to allow to manipulate easily intervals. For example, by doing the following, `bins[..., :-1]` you will obtain all the left coordinates of your intervals, while doing `bins[..., 1:]` is equals to the right coordinates of your intervals. We introduce here the support of bins like in MipNerf implementation. ## RayPointRefiner Small changes have been made to modify RayPointRefiner. - If bins is None ``` mids = torch.lerp(ray_bundle.lengths[..., 1:], ray_bundle.lengths[…, :-1], 0.5) z_samples = sample_pdf( mids, # [..., npt] weights[..., 1:-1], # [..., npt - 1] …. ) ``` - If bins is not None In the MipNerf implementation the sampling is done on all the bins. It allows us to use the full weights tensor without slashing it. ``` z_samples = sample_pdf( ray_bundle.bins, # [..., npt + 1] weights, # [..., npt] ... ) ``` ## RayMarcher Add a ray_deltas optional argument. If None, keep the same deltas computation from ray_lengths. Reviewed By: shapovalov Differential Revision: D46389092 fbshipit-source-id: d4f1963310065bd31c1c7fac1adfe11cbeaba606