Unable to train without poses iPhone.py

[kurtjcu]

I have tried to use the iPhone config and training loops forever in the validation stage.

model>nerf.py>Graph>render
line 325

while ray.isnan().any(): # TODO: weird bug, ray becomes NaN arbitrarily if batch_size>1, not deterministic reproducible
            center,ray = camera.get_center_and_ray(opt,pose,intr=intr) # [B,HW,3]

my conda env

# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: linux-64
@EXPLICIT
https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
https://repo.anaconda.com/pkgs/main/linux-64/blas-1.0-mkl.conda
https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2023.01.10-h06a4308_0.conda
https://conda.anaconda.org/nvidia/linux-64/cuda-cudart-11.8.89-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/cuda-cupti-11.8.87-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/cuda-nvrtc-11.8.89-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/cuda-nvtx-11.8.86-0.tar.bz2
https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-hab24e00_0.tar.bz2
https://repo.anaconda.com/pkgs/main/linux-64/intel-openmp-2021.4.0-h06a4308_3561.conda
https://repo.anaconda.com/pkgs/main/linux-64/ld_impl_linux-64-2.38-h1181459_1.conda
https://conda.anaconda.org/nvidia/linux-64/libcublas-11.11.3.6-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/libcufft-10.9.0.58-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/libcufile-1.6.0.25-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/libcurand-10.3.2.56-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/libcusolver-11.4.1.48-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/libcusparse-11.7.5.86-0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-12.2.0-h337968e_19.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/libnpp-11.8.0.86-0.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/libnvjpeg-11.9.0.86-0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-12.2.0-h46fd767_19.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.11-3_cp311.conda
https://conda.anaconda.org/pytorch-nightly/noarch/pytorch-mutex-1.0-cuda.tar.bz2
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https://conda.anaconda.org/nvidia/linux-64/cuda-libraries-11.8.0-0.tar.bz2
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https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-12.2.0-h69a702a_19.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libgomp-12.2.0-h65d4601_19.tar.bz2
https://repo.anaconda.com/pkgs/main/linux-64/mkl-2021.4.0-h06a4308_640.conda
https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
https://conda.anaconda.org/nvidia/linux-64/cuda-runtime-11.8.0-0.tar.bz2
https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-12_linux64_mkl.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-12_linux64_mkl.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-12.2.0-h65d4601_19.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-12_linux64_mkl.tar.bz2
https://conda.anaconda.org/pytorch-nightly/linux-64/pytorch-cuda-11.8-h7e8668a_3.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.8-h166bdaf_0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/aom-3.5.0-h27087fc_0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.1-h166bdaf_1.tar.bz2
https://repo.anaconda.com/pkgs/main/linux-64/bzip2-1.0.8-h7b6447c_0.conda
https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.18.1-h7f98852_0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/fftw-3.3.10-nompi_hf0379b8_106.conda
https://conda.anaconda.org/conda-forge/linux-64/gettext-0.21.1-h27087fc_0.tar.bz2
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https://conda.anaconda.org/conda-forge/linux-64/graphite2-1.3.13-h58526e2_1001.tar.bz2
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https://conda.anaconda.org/conda-forge/linux-64/libglu-9.0.0-he1b5a44_1001.tar.bz2
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https://conda.anaconda.org/conda-forge/linux-64/liblapacke-3.9.0-12_linux64_mkl.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-h7f98852_0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libogg-1.3.4-h7f98852_1.tar.bz2
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https://conda.anaconda.org/conda-forge/linux-64/libpciaccess-0.17-h166bdaf_0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libsodium-1.0.18-h36c2ea0_1.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libtasn1-4.19.0-h166bdaf_0.tar.bz2
https://conda.anaconda.org/conda-forge/linux-64/libtool-2.4.7-h27087fc_0.conda
https://repo.anaconda.com/pkgs/main/linux-64/libunistring-0.9.10-h27cfd23_0.conda
https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.38.1-h0b41bf4_0.conda
https://conda.anaconda.org/conda-forge/linux-64/libuv-1.44.2-h166bdaf_0.tar.bz2
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https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.9-h7f98852_0.tar.bz2
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https://conda.anaconda.org/conda-forge/linux-64/xorg-renderproto-0.11.1-h7f98852_1002.tar.bz2
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https://conda.anaconda.org/pytorch-nightly/linux-64/torchtriton-2.1.0+46672772b4-py311.tar.bz2
https://conda.anaconda.org/pytorch-nightly/linux-64/torchvision-0.16.0.dev20230402-py311_cu118.tar.bz2
https://conda.anaconda.org/conda-forge/noarch/lpips-0.1.3-pyhd8ed1ab_0.tar.bz2

[chenhsuanlin]

Hi @kurtjcu, there's a weird bug (as mentioned in the comment) that I haven't been able to resolve here, which could (sometimes) make ray contain NaN values if the batch size were larger than 1. If you happen to find the root cause, please help submit a PR and I would be happy to merge!

[samhodge-aiml]

What is the code or option change to make the batch_size=1 Doing it in the options did not work.

[tb2-sy]

What is the code or option change to make the batch_size=1 Doing it in the options did not work.

Just modify model/barf.py get_pose() function, add eps to
center_aligned = (center-sim3.t0)/sim3.s0@sim3.R*sim3.s1+sim3.t1, that is
center_aligned = (center-sim3.t0)/(sim3.s0 + 1e-7)@sim3.R*sim3.s1+sim3.t1