iopath dependency

Summary: Add ioPath as a dependency of PyTorch3D in preparation for using the new PathManager.

Reviewed By: nikhilaravi

Differential Revision: D25372971

fbshipit-source-id: d8aa661d2de975e747dd494edc42bf843990cf68

.circleci/config.in.yml

@@ -75,6 +75,7 @@ jobs:
       # - run: conda install -c pytorch pytorch torchvision
 
       - run: pip3 install --progress-bar off 'git+https://github.com/facebookresearch/fvcore'
+      - run: pip3 install --progress-bar off 'git+https://github.com/facebookresearch/iopath'
       - run:
           name: get cub
           command: |

.circleci/config.yml

@@ -75,6 +75,7 @@ jobs:
       # - run: conda install -c pytorch pytorch torchvision
 
       - run: pip3 install --progress-bar off 'git+https://github.com/facebookresearch/fvcore'
+      - run: pip3 install --progress-bar off 'git+https://github.com/facebookresearch/iopath'
       - run:
           name: get cub
           command: |

INSTALL.md

@@ -13,6 +13,7 @@ The core library is written in PyTorch. Several components have underlying imple
 - torchvision that matches the PyTorch installation. You can install them together as explained at pytorch.org to make sure of this.
 - gcc & g++ ≥ 4.9
 - [fvcore](https://github.com/facebookresearch/fvcore)
+- [ioPath](https://github.com/facebookresearch/iopath)
 - If CUDA is to be used, use a version which is supported by the corresponding pytorch version and at least version 9.2.
 - If CUDA is to be used and you are building from source, the CUB library must be available. We recommend version 1.10.0.
 
@@ -21,7 +22,7 @@ The runtime dependencies can be installed by running:
 conda create -n pytorch3d python=3.8
 conda activate pytorch3d
 conda install -c pytorch pytorch=1.7.0 torchvision cudatoolkit=10.2
-conda install -c conda-forge -c fvcore fvcore
+conda install -c conda-forge fvcore iopath
 ```
 
 For the CUB build time dependency, if you are using conda, you can continue with

dev/run_tutorials.sh

@@ -19,7 +19,7 @@ conda init bash
 source ~/.bashrc
 conda create -y -n myenv python=3.8 matplotlib ipython ipywidgets nbconvert
 conda activate myenv
-conda install -y -c conda-forge fvcore
+conda install -y -c conda-forge fvcore iopath
 conda install -y -c pytorch pytorch=1.6.0 cudatoolkit=10.1 torchvision
 conda install -y -c pytorch3d-nightly pytorch3d
 pip install plotly scikit-image

docs/requirements.txt

@@ -6,5 +6,6 @@ sphinx_markdown_tables
 mock
 numpy
 git+git://github.com/facebookresearch/fvcore.git
+git+git://github.com/facebookresearch/iopath.git
 https://download.pytorch.org/whl/cpu/torchvision-0.8.2%2Bcpu-cp37-cp37m-linux_x86_64.whl
 https://download.pytorch.org/whl/cpu/torch-1.7.1%2Bcpu-cp37-cp37m-linux_x86_64.whl

packaging/build_conda.sh

@@ -17,4 +17,4 @@ setup_conda_pytorch_constraint
 setup_conda_cudatoolkit_constraint
 setup_visual_studio_constraint
 # shellcheck disable=SC2086
-conda build $CONDA_CHANNEL_FLAGS ${TEST_FLAG:-} -c bottler -c defaults -c conda-forge --no-anaconda-upload -c fvcore --python "$PYTHON_VERSION" packaging/pytorch3d
+conda build $CONDA_CHANNEL_FLAGS ${TEST_FLAG:-} -c bottler -c defaults -c conda-forge --no-anaconda-upload --python "$PYTHON_VERSION" packaging/pytorch3d

packaging/pytorch3d/meta.yaml

@@ -22,6 +22,7 @@ requirements:
     - numpy >=1.11
     - torchvision >=0.5
     - fvcore
+    - iopath
     {{ environ.get('CONDA_PYTORCH_CONSTRAINT') }}
     {{ environ.get('CONDA_CUDATOOLKIT_CONSTRAINT') }}
 

setup.py

@@ -109,7 +109,7 @@ def __init__(self, *args, **kwargs):
     description="PyTorch3D is FAIR's library of reusable components "
     "for deep Learning with 3D data.",
     packages=find_packages(exclude=("configs", "tests", "tests.*")),
-    install_requires=["torchvision>=0.4", "fvcore"],
+    install_requires=["torchvision>=0.4", "fvcore", "iopath"],
     extras_require={
         "all": ["matplotlib", "tqdm>4.29.0", "imageio", "ipywidgets"],
         "dev": ["flake8", "isort", "black==19.3b0"],