Summary: Removing hardcoded block reduction operation from `sample_farthest_points.cu` code, and replace it with `cub::BlockReduce` reducing complexity of the code, and letting established libraries do the thinking for us.
Reviewed By: bottler
Differential Revision: D38617147
fbshipit-source-id: b230029c55f05cda0aab1648d3105a8d3e92d27b
Summary: Split Volumes class to data and location part so that location part can be reused in planned VoxelGrid classes.
Reviewed By: bottler
Differential Revision: D38782015
fbshipit-source-id: 489da09c5c236f3b81961ce9b09edbd97afaa7c8
Summary:
generic_model_args no longer exists. Update some references to it, mostly in doc.
This fixes the testing of all the yaml files in test_forward pass.
Reviewed By: shapovalov
Differential Revision: D38789202
fbshipit-source-id: f11417efe772d7f86368b3598aa66c52b1309dbf
Summary:
We identified that these logging statements can deteriorate performance in certain cases. I propose removing them from the regular renderer implementation and letting individuals re-insert debug logging wherever needed on a case-by-case basis.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1260
Reviewed By: kjchalup
Differential Revision: D38737439
Pulled By: bottler
fbshipit-source-id: cf9dcbbeae4dbf214c2e17d5bafa00b2ff796393
Summary: Useful for visualising colmap output where some frames are not correctly registered.
Reviewed By: bottler
Differential Revision: D38743191
fbshipit-source-id: e823df2997870dc41d76784e112d4349f904d311
Summary: Previously, "psnr" was evaluated between the masked g.t. image and the render. To avoid confusion, "psnr" is now renamed to "psnr_masked".
Reviewed By: bottler
Differential Revision: D38707511
fbshipit-source-id: 8ee881ab1a05453d6692dde9782333a47d8c1234
Summary: Builds for new PyTorch 1.12.1. Drop builds for PyTorch 1.8.0 and 1.8.1.
Reviewed By: kjchalup
Differential Revision: D38658991
fbshipit-source-id: 6192e226c2154cd051eeee98498d9a395cfd6fd5
Summary: Reports also the PSNR between the unmasked G.T. image and the render.
Reviewed By: bottler
Differential Revision: D38655943
fbshipit-source-id: 1603a2d02116ea1ce037e5530abe1afc65a2ba93
Summary:
**"filename"**: "projects/nerf/nerf/implicit_function.py"
**"warning_type"**: "Incompatible variable type [9]",
**"warning_message"**: " input_skips is declared to have type `Tuple[int]` but is used as type `Tuple[]`.",
**"warning_line"**: 256,
**"fix"**: input_skips: Tuple[int,...] = ()
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1288
Reviewed By: kjchalup
Differential Revision: D38615188
Pulled By: bottler
fbshipit-source-id: a014344dd6cf2125f564f948a3c905ceb84cf994
Summary: This makes the new volumes tutorial work on google colab.
Reviewed By: kjchalup
Differential Revision: D38501906
fbshipit-source-id: a606a357e929dae903dc4d9067bd1519f05b1458
Summary: need to pip install visdom in new volumes tutorial.
Reviewed By: kjchalup
Differential Revision: D38501905
fbshipit-source-id: 534bf097e41f05b3389e9420e6dd2b61a4517861
Summary: Linear followed by exponential LR progression. Needed for making Blender scenes converge.
Reviewed By: kjchalup
Differential Revision: D38557007
fbshipit-source-id: ad630dbc5b8fabcb33eeb5bdeed5e4f31360bac2
Summary:
LLFF (and most/all non-synth datasets) will have no background/foreground distinction. Add support for data with no fg mask.
Also, we had a bug in stats loading, like this:
* Load stats
* One of the stats has a history of length 0
* That's fine, e.g. maybe it's fg_error but the dataset has no notion of fg/bg. So leave it as len 0
* Check whether all the stats have the same history length as an arbitrarily chosen "reference-stat"
* Ooops the reference-stat happened to be the stat with length 0
* assert (legit_stat_len == reference_stat_len (=0)) ---> failed assert
Also some minor fixes (from Jeremy's other diff) to support LLFF
Reviewed By: davnov134
Differential Revision: D38475272
fbshipit-source-id: 5b35ac86d1d5239759f537621f41a3aa4eb3bd68
Summary: In a multisequence (fewview) scenario, it does not make sense to use all cameras for evaluating the difficulty as they come from different scenes. Using only this batch’s source (known) cameras instead.
Reviewed By: bottler
Differential Revision: D38491070
fbshipit-source-id: d6312d8fbb125b28a33db9f53d4215bcd1ca28a8
Summary:
Request in https://github.com/facebookresearch/pytorch3d/issues/1233 for option to disable CUDA build.
Also option to disable binary build completely. This could be useful e.g. in the config tutorial where we need a small python-only part of pytorch3d.
Reviewed By: kjchalup
Differential Revision: D38458624
fbshipit-source-id: 421a0b1cc31306d7e322d3e743e30a7533d7f034
Summary:
Misc fixes.
- most important: the mac image is gone so switch to a newer one.
- torch.concat is new; was used accidentally
- remove lpips from testing in meta.yaml as it is breaking the conda test. Better to leave the relevant tests failing in OSS.
- TypedDict usage is breaking implicitron on Python 3.7.
Reviewed By: patricklabatut
Differential Revision: D38458164
fbshipit-source-id: b16c26453a743b9a771e2a6787b9a4d2a52e41c2
Summary: This field is specific to one purpose.
Reviewed By: patricklabatut
Differential Revision: D38424891
fbshipit-source-id: e017304497012430c30e436da7052b9ad6fc7614
Summary: One way to tidy the installation so we don't install files in site-packages/projects. Fixes https://github.com/facebookresearch/pytorch3d/issues/1279
Reviewed By: shapovalov, davnov134
Differential Revision: D38426772
fbshipit-source-id: ac1a54fbf230adb53904701e1f38bf9567f647ce
Summary: Don't copy from one part of config to another, rather do the copy within GenericModel.
Reviewed By: davnov134
Differential Revision: D38248828
fbshipit-source-id: ff8af985c37ea1f7df9e0aa0a45a58df34c3f893
Summary: Made the config system call open_dict when it calls the tweak function.
Reviewed By: shapovalov
Differential Revision: D38315334
fbshipit-source-id: 5924a92d8d0bf399bbf3788247f81fc990e265e7
Summary:
Stats are logically connected to the training loop, not to the model. Hence, moving to the training loop.
Also removing resume_epoch from OptimizerFactory in favor of a single place - ModelFactory. This removes the need for config consistency checks etc.
Reviewed By: kjchalup
Differential Revision: D38313475
fbshipit-source-id: a1d188a63e28459df381ff98ad8acdcdb14887b7
Summary: Before this diff, train_stats.py would not be created by default, EXCEPT when resuming training. This makes them appear from start.
Reviewed By: shapovalov
Differential Revision: D38320341
fbshipit-source-id: 8ea5b99ec81c377ae129f58e78dc2eaff94821ad
Summary: Remove the dataset's need to provide the task type.
Reviewed By: davnov134, kjchalup
Differential Revision: D38314000
fbshipit-source-id: 3805d885b5d4528abdc78c0da03247edb9abf3f7
Summary:
Added _NEED_CONTROL
to JsonIndexDatasetMapProviderV2 and made dataset_tweak_args use it.
Reviewed By: bottler
Differential Revision: D38313914
fbshipit-source-id: 529847571065dfba995b609a66737bd91e002cfe
Summary: Only import it if you ask for it.
Reviewed By: kjchalup
Differential Revision: D38327167
fbshipit-source-id: 3f05231f26eda582a63afc71b669996342b0c6f9
