Summary: If we are not visualizing the training with visdom, then there are a couple of outputs of the coarse rendering step which are not small and are returned by the renderer but never used. We don't need to bother transferring them to the CPU.
Reviewed By: nikhilaravi
Differential Revision: D28939958
fbshipit-source-id: 7e0d6681d6524f7fb57b6b20164580006120de80
Summary:
All classes implicitly inherit from `object` since Python 3, so remove unnecessary explicit inheritance.
From the [official documentation](https://docs.python.org/3/library/functions.html#object):
> `object` is a base for all classes.
Reviewed By: nikhilaravi
Differential Revision: D28942595
fbshipit-source-id: 466c0d19d8a93a6263e7ad734c3e87160cfa6066
Summary:
Inside the implicit function, the color and density calculations are independent and time is saved by putting them on separate streams.
(In fact, colors is slower than densities, and the raymarcher does some calculation with the densities before the colors. So theoretically we could go further and not join the streams together until the colors are actually needed. The code would be more complicated. But the profile suggests that the raymarcher is quick and so this wouldn't be expected to make a big difference.)
In inference, this might increase memory usage, so it isn't an obvious win. That is why I have added a flag.
Reviewed By: nikhilaravi
Differential Revision: D28648549
fbshipit-source-id: c087de80d8ccfce1dad3a13e71df2f305a36952e
Summary: When harmonic embedding is used, we always cat its input onto its output before proceeding. Avoid an intermediate tensor by making the module do that for itself.
Reviewed By: davnov134
Differential Revision: D28185791
fbshipit-source-id: 98d92c94a918dd42e16cdadcaac71dabbc7de5c3
Summary:
Add custom layer to avoid repeating copied data for every ray position.
This should also save time in the backward pass because there are fewer multiplies with the weights.
Reviewed By: theschnitz
Differential Revision: D28382412
fbshipit-source-id: 1ba7356cd8520ebd598568ae503e47d31d3989eb
Summary: We don't use gradents of sample_pdf. Here we disable gradient calculation around calling it, instead of calling detach later. There's a theoretical speedup, but mainly this enables using sample_pdf implementations which don't support gradients.
Reviewed By: nikhilaravi
Differential Revision: D28057284
fbshipit-source-id: 8a9d5e73f18b34e1e4291028008e02973023638d
Summary: Implements the training script of NeRF.
Reviewed By: nikhilaravi
Differential Revision: D25684439
fbshipit-source-id: 8b19b6dc282eb6bf6e46ec4476bb0f13a84c90dd
Summary: Implements the `Stats` class that handles logging of the training statistics.
Reviewed By: nikhilaravi
Differential Revision: D25684430
fbshipit-source-id: 920a1c65917ab5d047988494d92173da60cfd64b
Summary: Implements the main NeRF model class that controls the radiance field and its renderer
Reviewed By: nikhilaravi
Differential Revision: D25684419
fbshipit-source-id: fae45572daa6748c6234bd212f3e68110f778238
Summary: Implements the radiance field function of NeRF
Reviewed By: nikhilaravi
Differential Revision: D25684413
fbshipit-source-id: 4bf6dd5d22e6134a09f7b9f314536ec16670f737
Summary: An initial NeRF diff which sets up the folder structure and implements the raymarching algorithm of NeRF.
Reviewed By: nikhilaravi
Differential Revision: D25623990
fbshipit-source-id: ac6b05a9b866358bd4bbf44858f06859d8a6ebd1
