update version to 0.7.8

Summary: as title

Reviewed By: das-intensity

Differential Revision: D62588556

fbshipit-source-id: 55bae19dd1df796e83179cd29d805fcd871b6d23

.circleci/config.yml

@@ -162,90 +162,6 @@ workflows:
     jobs:
       # - main:
       #     context: DOCKERHUB_TOKEN
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py38_cu113_pyt1120
-          python_version: '3.8'
-          pytorch_version: 1.12.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py38_cu116_pyt1120
-          python_version: '3.8'
-          pytorch_version: 1.12.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py38_cu113_pyt1121
-          python_version: '3.8'
-          pytorch_version: 1.12.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py38_cu116_pyt1121
-          python_version: '3.8'
-          pytorch_version: 1.12.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py38_cu116_pyt1130
-          python_version: '3.8'
-          pytorch_version: 1.13.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py38_cu117_pyt1130
-          python_version: '3.8'
-          pytorch_version: 1.13.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py38_cu116_pyt1131
-          python_version: '3.8'
-          pytorch_version: 1.13.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py38_cu117_pyt1131
-          python_version: '3.8'
-          pytorch_version: 1.13.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py38_cu117_pyt200
-          python_version: '3.8'
-          pytorch_version: 2.0.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda118
-          context: DOCKERHUB_TOKEN
-          cu_version: cu118
-          name: linux_conda_py38_cu118_pyt200
-          python_version: '3.8'
-          pytorch_version: 2.0.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py38_cu117_pyt201
-          python_version: '3.8'
-          pytorch_version: 2.0.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda118
-          context: DOCKERHUB_TOKEN
-          cu_version: cu118
-          name: linux_conda_py38_cu118_pyt201
-          python_version: '3.8'
-          pytorch_version: 2.0.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
@@ -303,89 +219,61 @@ workflows:
           python_version: '3.8'
           pytorch_version: 2.2.0
       - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
+          conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
-          cu_version: cu113
+          cu_version: cu118
-          name: linux_conda_py39_cu113_pyt1120
+          name: linux_conda_py38_cu118_pyt222
-          python_version: '3.9'
+          python_version: '3.8'
-          pytorch_version: 1.12.0
+          pytorch_version: 2.2.2
       - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
+          conda_docker_image: pytorch/conda-builder:cuda121
           context: DOCKERHUB_TOKEN
-          cu_version: cu116
+          cu_version: cu121
-          name: linux_conda_py39_cu116_pyt1120
+          name: linux_conda_py38_cu121_pyt222
-          python_version: '3.9'
+          python_version: '3.8'
-          pytorch_version: 1.12.0
+          pytorch_version: 2.2.2
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py39_cu113_pyt1121
-          python_version: '3.9'
-          pytorch_version: 1.12.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py39_cu116_pyt1121
-          python_version: '3.9'
-          pytorch_version: 1.12.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py39_cu116_pyt1130
-          python_version: '3.9'
-          pytorch_version: 1.13.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py39_cu117_pyt1130
-          python_version: '3.9'
-          pytorch_version: 1.13.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py39_cu116_pyt1131
-          python_version: '3.9'
-          pytorch_version: 1.13.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py39_cu117_pyt1131
-          python_version: '3.9'
-          pytorch_version: 1.13.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py39_cu117_pyt200
-          python_version: '3.9'
-          pytorch_version: 2.0.0
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
           cu_version: cu118
-          name: linux_conda_py39_cu118_pyt200
+          name: linux_conda_py38_cu118_pyt231
-          python_version: '3.9'
+          python_version: '3.8'
-          pytorch_version: 2.0.0
+          pytorch_version: 2.3.1
       - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
+          conda_docker_image: pytorch/conda-builder:cuda121
           context: DOCKERHUB_TOKEN
-          cu_version: cu117
+          cu_version: cu121
-          name: linux_conda_py39_cu117_pyt201
+          name: linux_conda_py38_cu121_pyt231
-          python_version: '3.9'
+          python_version: '3.8'
-          pytorch_version: 2.0.1
+          pytorch_version: 2.3.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
           cu_version: cu118
-          name: linux_conda_py39_cu118_pyt201
+          name: linux_conda_py38_cu118_pyt240
-          python_version: '3.9'
+          python_version: '3.8'
-          pytorch_version: 2.0.1
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py38_cu121_pyt240
+          python_version: '3.8'
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py38_cu118_pyt241
+          python_version: '3.8'
+          pytorch_version: 2.4.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py38_cu121_pyt241
+          python_version: '3.8'
+          pytorch_version: 2.4.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
@@ -443,89 +331,61 @@ workflows:
           python_version: '3.9'
           pytorch_version: 2.2.0
       - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
+          conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
-          cu_version: cu113
+          cu_version: cu118
-          name: linux_conda_py310_cu113_pyt1120
+          name: linux_conda_py39_cu118_pyt222
-          python_version: '3.10'
+          python_version: '3.9'
-          pytorch_version: 1.12.0
+          pytorch_version: 2.2.2
       - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
+          conda_docker_image: pytorch/conda-builder:cuda121
           context: DOCKERHUB_TOKEN
-          cu_version: cu116
+          cu_version: cu121
-          name: linux_conda_py310_cu116_pyt1120
+          name: linux_conda_py39_cu121_pyt222
-          python_version: '3.10'
+          python_version: '3.9'
-          pytorch_version: 1.12.0
+          pytorch_version: 2.2.2
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py310_cu113_pyt1121
-          python_version: '3.10'
-          pytorch_version: 1.12.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py310_cu116_pyt1121
-          python_version: '3.10'
-          pytorch_version: 1.12.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py310_cu116_pyt1130
-          python_version: '3.10'
-          pytorch_version: 1.13.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py310_cu117_pyt1130
-          python_version: '3.10'
-          pytorch_version: 1.13.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          context: DOCKERHUB_TOKEN
-          cu_version: cu116
-          name: linux_conda_py310_cu116_pyt1131
-          python_version: '3.10'
-          pytorch_version: 1.13.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py310_cu117_pyt1131
-          python_version: '3.10'
-          pytorch_version: 1.13.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          context: DOCKERHUB_TOKEN
-          cu_version: cu117
-          name: linux_conda_py310_cu117_pyt200
-          python_version: '3.10'
-          pytorch_version: 2.0.0
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
           cu_version: cu118
-          name: linux_conda_py310_cu118_pyt200
+          name: linux_conda_py39_cu118_pyt231
-          python_version: '3.10'
+          python_version: '3.9'
-          pytorch_version: 2.0.0
+          pytorch_version: 2.3.1
       - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
+          conda_docker_image: pytorch/conda-builder:cuda121
           context: DOCKERHUB_TOKEN
-          cu_version: cu117
+          cu_version: cu121
-          name: linux_conda_py310_cu117_pyt201
+          name: linux_conda_py39_cu121_pyt231
-          python_version: '3.10'
+          python_version: '3.9'
-          pytorch_version: 2.0.1
+          pytorch_version: 2.3.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
           cu_version: cu118
-          name: linux_conda_py310_cu118_pyt201
+          name: linux_conda_py39_cu118_pyt240
-          python_version: '3.10'
+          python_version: '3.9'
-          pytorch_version: 2.0.1
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py39_cu121_pyt240
+          python_version: '3.9'
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py39_cu118_pyt241
+          python_version: '3.9'
+          pytorch_version: 2.4.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py39_cu121_pyt241
+          python_version: '3.9'
+          pytorch_version: 2.4.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
@@ -582,6 +442,62 @@ workflows:
           name: linux_conda_py310_cu121_pyt220
           python_version: '3.10'
           pytorch_version: 2.2.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py310_cu118_pyt222
+          python_version: '3.10'
+          pytorch_version: 2.2.2
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py310_cu121_pyt222
+          python_version: '3.10'
+          pytorch_version: 2.2.2
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py310_cu118_pyt231
+          python_version: '3.10'
+          pytorch_version: 2.3.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py310_cu121_pyt231
+          python_version: '3.10'
+          pytorch_version: 2.3.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py310_cu118_pyt240
+          python_version: '3.10'
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py310_cu121_pyt240
+          python_version: '3.10'
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py310_cu118_pyt241
+          python_version: '3.10'
+          pytorch_version: 2.4.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py310_cu121_pyt241
+          python_version: '3.10'
+          pytorch_version: 2.4.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
@@ -638,6 +554,62 @@ workflows:
           name: linux_conda_py311_cu121_pyt220
           python_version: '3.11'
           pytorch_version: 2.2.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py311_cu118_pyt222
+          python_version: '3.11'
+          pytorch_version: 2.2.2
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py311_cu121_pyt222
+          python_version: '3.11'
+          pytorch_version: 2.2.2
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py311_cu118_pyt231
+          python_version: '3.11'
+          pytorch_version: 2.3.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py311_cu121_pyt231
+          python_version: '3.11'
+          pytorch_version: 2.3.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py311_cu118_pyt240
+          python_version: '3.11'
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py311_cu121_pyt240
+          python_version: '3.11'
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py311_cu118_pyt241
+          python_version: '3.11'
+          pytorch_version: 2.4.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py311_cu121_pyt241
+          python_version: '3.11'
+          pytorch_version: 2.4.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
@@ -652,6 +624,62 @@ workflows:
           name: linux_conda_py312_cu121_pyt220
           python_version: '3.12'
           pytorch_version: 2.2.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py312_cu118_pyt222
+          python_version: '3.12'
+          pytorch_version: 2.2.2
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py312_cu121_pyt222
+          python_version: '3.12'
+          pytorch_version: 2.2.2
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py312_cu118_pyt231
+          python_version: '3.12'
+          pytorch_version: 2.3.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py312_cu121_pyt231
+          python_version: '3.12'
+          pytorch_version: 2.3.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py312_cu118_pyt240
+          python_version: '3.12'
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py312_cu121_pyt240
+          python_version: '3.12'
+          pytorch_version: 2.4.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py312_cu118_pyt241
+          python_version: '3.12'
+          pytorch_version: 2.4.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py312_cu121_pyt241
+          python_version: '3.12'
+          pytorch_version: 2.4.1
       - binary_linux_conda_cuda:
           name: testrun_conda_cuda_py310_cu117_pyt201
           context: DOCKERHUB_TOKEN

.circleci/regenerate.py

@@ -19,16 +19,14 @@ from packaging import version
 # The CUDA versions which have pytorch conda packages available for linux for each
 # version of pytorch.
 CONDA_CUDA_VERSIONS = {
-    "1.12.0": ["cu113", "cu116"],
-    "1.12.1": ["cu113", "cu116"],
-    "1.13.0": ["cu116", "cu117"],
-    "1.13.1": ["cu116", "cu117"],
-    "2.0.0": ["cu117", "cu118"],
-    "2.0.1": ["cu117", "cu118"],
     "2.1.0": ["cu118", "cu121"],
     "2.1.1": ["cu118", "cu121"],
     "2.1.2": ["cu118", "cu121"],
     "2.2.0": ["cu118", "cu121"],
+    "2.2.2": ["cu118", "cu121"],
+    "2.3.1": ["cu118", "cu121"],
+    "2.4.0": ["cu118", "cu121"],
+    "2.4.1": ["cu118", "cu121"],
 }
 
 

INSTALL.md

@@ -8,11 +8,10 @@
 The core library is written in PyTorch. Several components have underlying implementation in CUDA for improved performance. A subset of these components have CPU implementations in C++/PyTorch. It is advised to use PyTorch3D with GPU support in order to use all the features.
 
 - Linux or macOS or Windows
-- Python 3.8, 3.9 or 3.10
+- Python
-- PyTorch 1.12.0, 1.12.1, 1.13.0, 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.1.2 or 2.2.0.
+- PyTorch 2.1.0, 2.1.1, 2.1.2, 2.2.0, 2.2.1, 2.2.2, 2.3.0, 2.3.1, 2.4.0 or 2.4.1.
 - 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 older than 11.7 is to be used and you are building from source, the CUB library must be available. We recommend version 1.10.0.
@@ -22,7 +21,7 @@ The runtime dependencies can be installed by running:
 conda create -n pytorch3d python=3.9
 conda activate pytorch3d
 conda install pytorch=1.13.0 torchvision pytorch-cuda=11.6 -c pytorch -c nvidia
-conda install -c fvcore -c iopath -c conda-forge fvcore iopath
+conda install -c iopath iopath
 ```
 
 For the CUB build time dependency, which you only need if you have CUDA older than 11.7, if you are using conda, you can continue with
@@ -49,6 +48,7 @@ For developing on top of PyTorch3D or contributing, you will need to run the lin
 - tdqm
 - jupyter
 - imageio
+- fvcore
 - plotly
 - opencv-python
 
@@ -59,6 +59,7 @@ conda install jupyter
 pip install scikit-image matplotlib imageio plotly opencv-python
 
 # Tests/Linting
+conda install -c fvcore -c conda-forge fvcore
 pip install black usort flake8 flake8-bugbear flake8-comprehensions
 ```
 
@@ -97,7 +98,7 @@ version_str="".join([
     torch.version.cuda.replace(".",""),
     f"_pyt{pyt_version_str}"
 ])
-!pip install fvcore iopath
+!pip install iopath
 !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html
 ```
 

dev/run_tutorials.sh

@@ -23,7 +23,7 @@ conda init bash
 source ~/.bashrc
 conda create -y -n myenv python=3.8 matplotlib ipython ipywidgets nbconvert
 conda activate myenv
-conda install -y -c fvcore -c iopath -c conda-forge fvcore iopath
+conda install -y -c iopath 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

@@ -5,7 +5,6 @@ sphinx_rtd_theme
 sphinx_markdown_tables
 numpy
 iopath
-fvcore
 https://download.pytorch.org/whl/cpu/torchvision-0.15.2%2Bcpu-cp311-cp311-linux_x86_64.whl
 https://download.pytorch.org/whl/cpu/torch-2.0.1%2Bcpu-cp311-cp311-linux_x86_64.whl
 omegaconf

docs/tutorials/bundle_adjustment.ipynb

@@ -83,25 +83,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

docs/tutorials/camera_position_optimization_with_differentiable_rendering.ipynb

@@ -70,25 +70,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

docs/tutorials/dataloaders_ShapeNetCore_R2N2.ipynb

@@ -45,25 +45,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {
@@ -405,7 +411,7 @@
    "outputs": [],
    "source": [
     "random_model_images = shapenet_dataset.render(\n",
-    "    sample_nums=[3],\n",
+    "    sample_nums=[5],\n",
     "    device=device,\n",
     "    cameras=cameras,\n",
     "    raster_settings=raster_settings,\n",

docs/tutorials/deform_source_mesh_to_target_mesh.ipynb

@@ -84,25 +84,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

docs/tutorials/fit_simple_neural_radiance_field.ipynb

@@ -50,25 +50,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

docs/tutorials/fit_textured_mesh.ipynb

@@ -62,25 +62,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

docs/tutorials/fit_textured_volume.ipynb

@@ -41,25 +41,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

docs/tutorials/implicitron_config_system.ipynb

@@ -72,25 +72,31 @@
         "import os\n",
         "import sys\n",
         "import torch\n",
+        "import subprocess\n",
         "need_pytorch3d=False\n",
         "try:\n",
         "    import pytorch3d\n",
         "except ModuleNotFoundError:\n",
         "    need_pytorch3d=True\n",
         "if need_pytorch3d:\n",
-        "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+        "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-        "        # We try to install PyTorch3D via a released wheel.\n",
+        "    version_str=\"\".join([\n",
-        "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+        "        f\"py3{sys.version_info.minor}_cu\",\n",
-        "        version_str=\"\".join([\n",
+        "        torch.version.cuda.replace(\".\",\"\"),\n",
-        "            f\"py3{sys.version_info.minor}_cu\",\n",
+        "        f\"_pyt{pyt_version_str}\"\n",
-        "            torch.version.cuda.replace(\".\",\"\"),\n",
+        "    ])\n",
-        "            f\"_pyt{pyt_version_str}\"\n",
+        "    !pip install iopath\n",
-        "        ])\n",
+        "    if sys.platform.startswith(\"linux\"):\n",
-        "        !pip install fvcore iopath\n",
+        "        print(\"Trying to install wheel for PyTorch3D\")\n",
         "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-        "    else:\n",
+        "        pip_list = !pip freeze\n",
-        "        # We try to install PyTorch3D from source.\n",
+        "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-        "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+        "    if need_pytorch3d:\n",
+        "        print(f\"failed to find/install wheel for {version_str}\")\n",
+        "if need_pytorch3d:\n",
+        "    print(\"Installing PyTorch3D from source\")\n",
+        "    !pip install ninja\n",
+        "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
       ]
     },
     {

docs/tutorials/implicitron_volumes.ipynb

@@ -66,25 +66,31 @@
         "import os\n",
         "import sys\n",
         "import torch\n",
+        "import subprocess\n",
         "need_pytorch3d=False\n",
         "try:\n",
         "    import pytorch3d\n",
         "except ModuleNotFoundError:\n",
         "    need_pytorch3d=True\n",
         "if need_pytorch3d:\n",
-        "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+        "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-        "        # We try to install PyTorch3D via a released wheel.\n",
+        "    version_str=\"\".join([\n",
-        "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+        "        f\"py3{sys.version_info.minor}_cu\",\n",
-        "        version_str=\"\".join([\n",
+        "        torch.version.cuda.replace(\".\",\"\"),\n",
-        "            f\"py3{sys.version_info.minor}_cu\",\n",
+        "        f\"_pyt{pyt_version_str}\"\n",
-        "            torch.version.cuda.replace(\".\",\"\"),\n",
+        "    ])\n",
-        "            f\"_pyt{pyt_version_str}\"\n",
+        "    !pip install iopath\n",
-        "        ])\n",
+        "    if sys.platform.startswith(\"linux\"):\n",
-        "        !pip install fvcore iopath\n",
+        "        print(\"Trying to install wheel for PyTorch3D\")\n",
         "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-        "    else:\n",
+        "        pip_list = !pip freeze\n",
-        "        # We try to install PyTorch3D from source.\n",
+        "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-        "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+        "    if need_pytorch3d:\n",
+        "        print(f\"failed to find/install wheel for {version_str}\")\n",
+        "if need_pytorch3d:\n",
+        "    print(\"Installing PyTorch3D from source\")\n",
+        "    !pip install ninja\n",
+        "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
       ]
     },
     {

docs/tutorials/render_colored_points.ipynb

@@ -44,25 +44,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

docs/tutorials/render_densepose.ipynb

@@ -51,25 +51,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

docs/tutorials/render_textured_meshes.ipynb

@@ -67,25 +67,31 @@
     "import os\n",
     "import sys\n",
     "import torch\n",
+    "import subprocess\n",
     "need_pytorch3d=False\n",
     "try:\n",
     "    import pytorch3d\n",
     "except ModuleNotFoundError:\n",
     "    need_pytorch3d=True\n",
     "if need_pytorch3d:\n",
-    "    if torch.__version__.startswith(\"2.2.\") and sys.platform.startswith(\"linux\"):\n",
+    "    pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
-    "        # We try to install PyTorch3D via a released wheel.\n",
+    "    version_str=\"\".join([\n",
-    "        pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n",
+    "        f\"py3{sys.version_info.minor}_cu\",\n",
-    "        version_str=\"\".join([\n",
+    "        torch.version.cuda.replace(\".\",\"\"),\n",
-    "            f\"py3{sys.version_info.minor}_cu\",\n",
+    "        f\"_pyt{pyt_version_str}\"\n",
-    "            torch.version.cuda.replace(\".\",\"\"),\n",
+    "    ])\n",
-    "            f\"_pyt{pyt_version_str}\"\n",
+    "    !pip install iopath\n",
-    "        ])\n",
+    "    if sys.platform.startswith(\"linux\"):\n",
-    "        !pip install fvcore iopath\n",
+    "        print(\"Trying to install wheel for PyTorch3D\")\n",
     "        !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n",
-    "    else:\n",
+    "        pip_list = !pip freeze\n",
-    "        # We try to install PyTorch3D from source.\n",
+    "        need_pytorch3d = not any(i.startswith(\"pytorch3d==\") for  i in pip_list)\n",
-    "        !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
+    "    if need_pytorch3d:\n",
+    "        print(f\"failed to find/install wheel for {version_str}\")\n",
+    "if need_pytorch3d:\n",
+    "    print(\"Installing PyTorch3D from source\")\n",
+    "    !pip install ninja\n",
+    "    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'"
    ]
   },
   {

packaging/build_conda.py

@@ -80,6 +80,12 @@ def setup_cuda():
 def setup_conda_pytorch_constraint() -> List[str]:
     pytorch_constraint = f"- pytorch=={PYTORCH_VERSION}"
     os.environ["CONDA_PYTORCH_CONSTRAINT"] = pytorch_constraint
+    if pytorch_major_minor < (2, 2):
+        os.environ["CONDA_PYTORCH_MKL_CONSTRAINT"] = "- mkl!=2024.1.0"
+        os.environ["SETUPTOOLS_CONSTRAINT"] = "- setuptools<70"
+    else:
+        os.environ["CONDA_PYTORCH_MKL_CONSTRAINT"] = ""
+        os.environ["SETUPTOOLS_CONSTRAINT"] = "- setuptools"
     os.environ["CONDA_PYTORCH_BUILD_CONSTRAINT"] = pytorch_constraint
     os.environ["PYTORCH_VERSION_NODOT"] = PYTORCH_VERSION.replace(".", "")
 
@@ -117,7 +123,7 @@ def do_build(start_args: List[str]):
     if test_flag is not None:
         args.append(test_flag)
 
-    args.extend(["-c", "bottler", "-c", "fvcore", "-c", "iopath", "-c", "conda-forge"])
+    args.extend(["-c", "bottler", "-c", "iopath", "-c", "conda-forge"])
     args.append("--no-anaconda-upload")
     args.extend(["--python", os.environ["PYTHON_VERSION"]])
     args.append("packaging/pytorch3d")

packaging/linux_wheels/README.md

@@ -26,6 +26,6 @@ version_str="".join([
     torch.version.cuda.replace(".",""),
     f"_pyt{pyt_version_str}"
 ])
-!pip install fvcore iopath
+!pip install iopath
 !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html
 ```

packaging/linux_wheels/inside.sh

@@ -144,7 +144,7 @@ do
             conda activate "$tag"
             # shellcheck disable=SC2086
             conda install -y -c pytorch $extra_channel "pytorch=$pytorch_version" "$cudatools=$CUDA_TAG"
-            pip install fvcore iopath
+            pip install iopath
             echo "python version" "$python_version" "pytorch version" "$pytorch_version" "cuda version" "$cu_version" "tag" "$tag"
 
             rm -rf dist

packaging/pytorch3d/meta.yaml

@@ -12,8 +12,9 @@ requirements:
 
   host:
     - python
-    - setuptools
+    {{ environ.get('SETUPTOOLS_CONSTRAINT') }}
     {{ environ.get('CONDA_PYTORCH_BUILD_CONSTRAINT') }}
+    {{ environ.get('CONDA_PYTORCH_MKL_CONSTRAINT') }}
     {{ environ.get('CONDA_CUDATOOLKIT_CONSTRAINT') }}
     {{ environ.get('CONDA_CPUONLY_FEATURE') }}
 
@@ -21,7 +22,6 @@ requirements:
     - python
     - numpy >=1.11
     - torchvision >=0.5
-    - fvcore
     - iopath
     {{ environ.get('CONDA_PYTORCH_CONSTRAINT') }}
     {{ environ.get('CONDA_CUDATOOLKIT_CONSTRAINT') }}

projects/implicitron_trainer/__init__.py

@@ -3,3 +3,5 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe

projects/implicitron_trainer/experiment.py

@@ -5,6 +5,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 """"
 This file is the entry point for launching experiments with Implicitron.
 
@@ -97,7 +99,7 @@ except ModuleNotFoundError:
 no_accelerate = os.environ.get("PYTORCH3D_NO_ACCELERATE") is not None
 
 
-class Experiment(Configurable):  # pyre-ignore: 13
+class Experiment(Configurable):
     """
     This class is at the top level of Implicitron's config hierarchy. Its
     members are high-level components necessary for training an implicit rende-
@@ -118,12 +120,16 @@ class Experiment(Configurable):  # pyre-ignore: 13
             will be saved here.
     """
 
+    # pyre-fixme[13]: Attribute `data_source` is never initialized.
     data_source: DataSourceBase
     data_source_class_type: str = "ImplicitronDataSource"
+    # pyre-fixme[13]: Attribute `model_factory` is never initialized.
     model_factory: ModelFactoryBase
     model_factory_class_type: str = "ImplicitronModelFactory"
+    # pyre-fixme[13]: Attribute `optimizer_factory` is never initialized.
     optimizer_factory: OptimizerFactoryBase
     optimizer_factory_class_type: str = "ImplicitronOptimizerFactory"
+    # pyre-fixme[13]: Attribute `training_loop` is never initialized.
     training_loop: TrainingLoopBase
     training_loop_class_type: str = "ImplicitronTrainingLoop"
 

projects/implicitron_trainer/impl/__init__.py

@@ -3,3 +3,5 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe

projects/implicitron_trainer/impl/model_factory.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import logging
 import os
 from typing import Optional
@@ -43,7 +45,7 @@ class ModelFactoryBase(ReplaceableBase):
 
 
 @registry.register
-class ImplicitronModelFactory(ModelFactoryBase):  # pyre-ignore [13]
+class ImplicitronModelFactory(ModelFactoryBase):
     """
     A factory class that initializes an implicit rendering model.
 
@@ -59,6 +61,7 @@ class ImplicitronModelFactory(ModelFactoryBase):  # pyre-ignore [13]
 
     """
 
+    # pyre-fixme[13]: Attribute `model` is never initialized.
     model: ImplicitronModelBase
     model_class_type: str = "GenericModel"
     resume: bool = True

projects/implicitron_trainer/impl/optimizer_factory.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import inspect
 import logging
 import os

projects/implicitron_trainer/impl/training_loop.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import logging
 import os
 import time
@@ -28,13 +30,13 @@ from .utils import seed_all_random_engines
 logger = logging.getLogger(__name__)
 
 
-# pyre-fixme[13]: Attribute `evaluator` is never initialized.
 class TrainingLoopBase(ReplaceableBase):
     """
     Members:
         evaluator: An EvaluatorBase instance, used to evaluate training results.
     """
 
+    # pyre-fixme[13]: Attribute `evaluator` is never initialized.
     evaluator: Optional[EvaluatorBase]
     evaluator_class_type: Optional[str] = "ImplicitronEvaluator"
 

projects/implicitron_trainer/impl/utils.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import random
 

projects/implicitron_trainer/tests/__init__.py

@@ -3,3 +3,5 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe

projects/implicitron_trainer/tests/test_experiment.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import os
 import tempfile
 import unittest

projects/implicitron_trainer/tests/test_optimizer_factory.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import logging
 import os
 import unittest

projects/implicitron_trainer/tests/test_visualize.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import os
 import unittest
 

projects/implicitron_trainer/tests/utils.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import contextlib
 import logging
 import os

projects/implicitron_trainer/visualize_reconstruction.py

@@ -5,6 +5,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 """
 Script to visualize a previously trained model. Example call:
 

projects/nerf/nerf/nerf_renderer.py

@@ -343,12 +343,14 @@ class RadianceFieldRenderer(torch.nn.Module):
             # For a full render pass concatenate the output chunks,
             # and reshape to image size.
             out = {
-                k: torch.cat(
+                k: (
-                    [ch_o[k] for ch_o in chunk_outputs],
+                    torch.cat(
-                    dim=1,
+                        [ch_o[k] for ch_o in chunk_outputs],
-                ).view(-1, *self._image_size, 3)
+                        dim=1,
-                if chunk_outputs[0][k] is not None
+                    ).view(-1, *self._image_size, 3)
-                else None
+                    if chunk_outputs[0][k] is not None
+                    else None
+                )
                 for k in ("rgb_fine", "rgb_coarse", "rgb_gt")
             }
         else:

pytorch3d/__init__.py

@@ -4,4 +4,6 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
-__version__ = "0.7.6"
+# pyre-unsafe
+
+__version__ = "0.7.8"

pytorch3d/common/__init__.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from .datatypes import Device, get_device, make_device
 
 

pytorch3d/common/compat.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from typing import Sequence, Tuple, Union
 
 import torch

pytorch3d/common/datatypes.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from typing import Optional, Union
 
 import torch

pytorch3d/common/linear_with_repeat.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import math
 from typing import Tuple
 

pytorch3d/common/workaround/__init__.py

@@ -4,5 +4,7 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from .symeig3x3 import symeig3x3
 from .utils import _safe_det_3x3

pytorch3d/common/workaround/symeig3x3.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import math
 from typing import Optional, Tuple
 

pytorch3d/common/workaround/utils.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import torch
 

pytorch3d/csrc/ext.cpp

@@ -7,11 +7,15 @@
  */
 
 // clang-format off
+#if !defined(USE_ROCM)
 #include "./pulsar/global.h" // Include before <torch/extension.h>.
+#endif
 #include <torch/extension.h>
 // clang-format on
+#if !defined(USE_ROCM)
 #include "./pulsar/pytorch/renderer.h"
 #include "./pulsar/pytorch/tensor_util.h"
+#endif
 #include "ball_query/ball_query.h"
 #include "blending/sigmoid_alpha_blend.h"
 #include "compositing/alpha_composite.h"
@@ -99,6 +103,8 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
   m.def("marching_cubes", &MarchingCubes);
 
   // Pulsar.
+  // Pulsar not enabled on AMD.
+#if !defined(USE_ROCM)
 #ifdef PULSAR_LOGGING_ENABLED
   c10::ShowLogInfoToStderr();
 #endif
@@ -183,4 +189,5 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
   m.attr("MAX_UINT") = py::int_(MAX_UINT);
   m.attr("MAX_USHORT") = py::int_(MAX_USHORT);
   m.attr("PULSAR_MAX_GRAD_SPHERES") = py::int_(MAX_GRAD_SPHERES);
+#endif
 }

pytorch3d/csrc/knn/knn.cu

@@ -338,7 +338,7 @@ std::tuple<at::Tensor, at::Tensor> KNearestNeighborIdxCuda(
 
   TORCH_CHECK((norm == 1) || (norm == 2), "Norm must be 1 or 2.");
 
-  TORCH_CHECK(p2.size(2) == D, "Point sets must have the same last dimension");
+  TORCH_CHECK(p1.size(2) == D, "Point sets must have the same last dimension");
   auto long_dtype = lengths1.options().dtype(at::kLong);
   auto idxs = at::zeros({N, P1, K}, long_dtype);
   auto dists = at::zeros({N, P1, K}, p1.options());

pytorch3d/csrc/marching_cubes/marching_cubes.cu

@@ -382,6 +382,44 @@ __global__ void GenerateFacesKernel(
   } // end for grid-strided kernel
 }
 
+// ATen/Torch does not have an exclusive-scan operator. Additionally, in the
+// code below we need to get the "total number of items to work on" after
+// a scan, which with an inclusive-scan would simply be the value of the last
+// element in the tensor.
+//
+// This utility function hits two birds with one stone, by running
+// an inclusive-scan into a right-shifted view of a tensor that's
+// allocated to be one element bigger than the input tensor.
+//
+// Note; return tensor is `int64_t` per element, even if the input
+// tensor is only 32-bit. Also, the return tensor is one element bigger
+// than the input one.
+//
+// Secondary optional argument is an output argument that gets the
+// value of the last element of the return tensor (because you almost
+// always need this CPU-side right after this function anyway).
+static at::Tensor ExclusiveScanAndTotal(
+    const at::Tensor& inTensor,
+    int64_t* optTotal = nullptr) {
+  const auto inSize = inTensor.sizes()[0];
+  auto retTensor = at::zeros({inSize + 1}, at::kLong).to(inTensor.device());
+
+  using at::indexing::None;
+  using at::indexing::Slice;
+  auto rightShiftedView = retTensor.index({Slice(1, None)});
+
+  // Do an (inclusive-scan) cumulative sum in to the view that's
+  // shifted one element to the right...
+  at::cumsum_out(rightShiftedView, inTensor, 0, at::kLong);
+
+  if (optTotal) {
+    *optTotal = retTensor[inSize].cpu().item<int64_t>();
+  }
+
+  // ...so that the not-shifted tensor holds the exclusive-scan
+  return retTensor;
+}
+
 // Entrance for marching cubes cuda extension. Marching Cubes is an algorithm to
 // create triangle meshes from an implicit function (one of the form f(x, y, z)
 // = 0). It works by iteratively checking a grid of cubes superimposed over a
@@ -444,20 +482,18 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
   using at::indexing::Slice;
 
   auto d_voxelVerts =
-      at::zeros({numVoxels + 1}, at::TensorOptions().dtype(at::kInt))
+      at::zeros({numVoxels}, at::TensorOptions().dtype(at::kInt))
           .to(vol.device());
-  auto d_voxelVerts_ = d_voxelVerts.index({Slice(1, None)});
   auto d_voxelOccupied =
-      at::zeros({numVoxels + 1}, at::TensorOptions().dtype(at::kInt))
+      at::zeros({numVoxels}, at::TensorOptions().dtype(at::kInt))
           .to(vol.device());
-  auto d_voxelOccupied_ = d_voxelOccupied.index({Slice(1, None)});
 
   // Execute "ClassifyVoxelKernel" kernel to precompute
   // two arrays - d_voxelOccupied and d_voxelVertices to global memory,
   // which stores the occupancy state and number of voxel vertices per voxel.
   ClassifyVoxelKernel<<<grid, threads, 0, stream>>>(
-      d_voxelVerts_.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
+      d_voxelVerts.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
-      d_voxelOccupied_.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
+      d_voxelOccupied.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
       vol.packed_accessor32<float, 3, at::RestrictPtrTraits>(),
       isolevel);
   AT_CUDA_CHECK(cudaGetLastError());
@@ -467,12 +503,9 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
   // count for voxels in the grid and compute the number of active voxels.
   // If the number of active voxels is 0, return zero tensor for verts and
   // faces.
-
+  int64_t activeVoxels = 0;
-  auto d_voxelOccupiedScan = at::cumsum(d_voxelOccupied, 0);
+  auto d_voxelOccupiedScan =
-  auto d_voxelOccupiedScan_ = d_voxelOccupiedScan.index({Slice(1, None)});
+      ExclusiveScanAndTotal(d_voxelOccupied, &activeVoxels);
-
-  // number of active voxels
-  int64_t activeVoxels = d_voxelOccupiedScan[numVoxels].cpu().item<int64_t>();
 
   const int device_id = vol.device().index();
   auto opt = at::TensorOptions().dtype(at::kInt).device(at::kCUDA, device_id);
@@ -487,24 +520,21 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
     return std::make_tuple(verts, faces, ids);
   }
 
-  // Execute "CompactVoxelsKernel" kernel to compress voxels for accleration.
+  // Execute "CompactVoxelsKernel" kernel to compress voxels for acceleration.
   // This allows us to run triangle generation on only the occupied voxels.
   auto d_compVoxelArray = at::zeros({activeVoxels}, opt);
   CompactVoxelsKernel<<<grid, threads, 0, stream>>>(
       d_compVoxelArray.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
       d_voxelOccupied.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
-      d_voxelOccupiedScan_
+      d_voxelOccupiedScan
           .packed_accessor32<int64_t, 1, at::RestrictPtrTraits>(),
       numVoxels);
   AT_CUDA_CHECK(cudaGetLastError());
   cudaDeviceSynchronize();
 
   // Scan d_voxelVerts array to generate offsets of vertices for each voxel
-  auto d_voxelVertsScan = at::cumsum(d_voxelVerts, 0);
+  int64_t totalVerts = 0;
-  auto d_voxelVertsScan_ = d_voxelVertsScan.index({Slice(1, None)});
+  auto d_voxelVertsScan = ExclusiveScanAndTotal(d_voxelVerts, &totalVerts);
-
-  // total number of vertices
-  int64_t totalVerts = d_voxelVertsScan[numVoxels].cpu().item<int64_t>();
 
   // Execute "GenerateFacesKernel" kernel
   // This runs only on the occupied voxels.
@@ -524,7 +554,7 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCuda(
       faces.packed_accessor<int64_t, 2, at::RestrictPtrTraits>(),
       ids.packed_accessor<int64_t, 1, at::RestrictPtrTraits>(),
       d_compVoxelArray.packed_accessor32<int, 1, at::RestrictPtrTraits>(),
-      d_voxelVertsScan_.packed_accessor32<int64_t, 1, at::RestrictPtrTraits>(),
+      d_voxelVertsScan.packed_accessor32<int64_t, 1, at::RestrictPtrTraits>(),
       activeVoxels,
       vol.packed_accessor32<float, 3, at::RestrictPtrTraits>(),
       faceTable.packed_accessor32<int, 2, at::RestrictPtrTraits>(),

pytorch3d/csrc/pulsar/host/commands.h

@@ -357,11 +357,11 @@ void MAX_WS(
 //
 //
 #define END_PARALLEL() \
-  end_parallel:;       \
+  end_parallel :;      \
   }
 #define END_PARALLEL_NORET() }
 #define END_PARALLEL_2D() \
-  end_parallel:;          \
+  end_parallel :;         \
   }                       \
   }
 #define END_PARALLEL_2D_NORET() \

pytorch3d/csrc/pulsar/include/renderer.construct.device.h

@@ -93,7 +93,7 @@ HOST void construct(
   MALLOC(self->di_sorted_d, DrawInfo, max_num_balls);
   MALLOC(self->region_flags_d, char, max_num_balls);
   MALLOC(self->num_selected_d, size_t, 1);
-  MALLOC(self->forw_info_d, float, width* height*(3 + 2 * n_track));
+  MALLOC(self->forw_info_d, float, width* height * (3 + 2 * n_track));
   MALLOC(self->min_max_pixels_d, IntersectInfo, 1);
   MALLOC(self->grad_pos_d, float3, max_num_balls);
   MALLOC(self->grad_col_d, float, max_num_balls* n_channels);

pytorch3d/csrc/pulsar/include/renderer.render.device.h

@@ -99,7 +99,7 @@ GLOBAL void render(
   /** Whether loading of balls is completed. */
   SHARED bool loading_done;
   /** The number of balls loaded overall (just for statistics). */
-  SHARED int n_balls_loaded;
+  [[maybe_unused]] SHARED int n_balls_loaded;
   /** The area this thread block covers. */
   SHARED IntersectInfo block_area;
   if (thread_block.thread_rank() == 0) {

pytorch3d/csrc/rasterize_coarse/rasterize_coarse.cu

@@ -244,8 +244,7 @@ at::Tensor RasterizeCoarseCuda(
   if (num_bins_y >= kMaxItemsPerBin || num_bins_x >= kMaxItemsPerBin) {
     std::stringstream ss;
     ss << "In RasterizeCoarseCuda got num_bins_y: " << num_bins_y
-       << ", num_bins_x: " << num_bins_x << ", "
+       << ", num_bins_x: " << num_bins_x << ", " << "; that's too many!";
-       << "; that's too many!";
     AT_ERROR(ss.str());
   }
   auto opts = elems_per_batch.options().dtype(at::kInt);

pytorch3d/csrc/rasterize_meshes/rasterize_meshes.cu

@@ -144,7 +144,7 @@ __device__ void CheckPixelInsideFace(
   const bool zero_face_area =
       (face_area <= kEpsilon && face_area >= -1.0f * kEpsilon);
 
-  if (zmax < 0 || cull_backfaces && back_face || outside_bbox ||
+  if (zmax < 0 || (cull_backfaces && back_face) || outside_bbox ||
       zero_face_area) {
     return;
   }

pytorch3d/csrc/utils/float_math.cuh

@@ -18,6 +18,8 @@ const auto vEpsilon = 1e-8;
 
 // Common functions and operators for float2.
 
+// Complex arithmetic is already defined for AMD.
+#if !defined(USE_ROCM)
 __device__ inline float2 operator-(const float2& a, const float2& b) {
   return make_float2(a.x - b.x, a.y - b.y);
 }
@@ -41,6 +43,7 @@ __device__ inline float2 operator*(const float2& a, const float2& b) {
 __device__ inline float2 operator*(const float a, const float2& b) {
   return make_float2(a * b.x, a * b.y);
 }
+#endif
 
 __device__ inline float FloatMin3(const float a, const float b, const float c) {
   return fminf(a, fminf(b, c));

pytorch3d/csrc/utils/warp_reduce.cuh

@@ -23,37 +23,51 @@ WarpReduceMin(scalar_t* min_dists, int64_t* min_idxs, const size_t tid) {
     min_idxs[tid] = min_idxs[tid + 32];
     min_dists[tid] = min_dists[tid + 32];
   }
+// AMD does not use explicit syncwarp and instead automatically inserts memory
+// fences during compilation.
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   // s = 16
   if (min_dists[tid] > min_dists[tid + 16]) {
     min_idxs[tid] = min_idxs[tid + 16];
     min_dists[tid] = min_dists[tid + 16];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   // s = 8
   if (min_dists[tid] > min_dists[tid + 8]) {
     min_idxs[tid] = min_idxs[tid + 8];
     min_dists[tid] = min_dists[tid + 8];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   // s = 4
   if (min_dists[tid] > min_dists[tid + 4]) {
     min_idxs[tid] = min_idxs[tid + 4];
     min_dists[tid] = min_dists[tid + 4];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   // s = 2
   if (min_dists[tid] > min_dists[tid + 2]) {
     min_idxs[tid] = min_idxs[tid + 2];
     min_dists[tid] = min_dists[tid + 2];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   // s = 1
   if (min_dists[tid] > min_dists[tid + 1]) {
     min_idxs[tid] = min_idxs[tid + 1];
     min_dists[tid] = min_dists[tid + 1];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
 }
 
 template <typename scalar_t>
@@ -65,30 +79,42 @@ __device__ void WarpReduceMax(
     dists[tid] = dists[tid + 32];
     dists_idx[tid] = dists_idx[tid + 32];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   if (dists[tid] < dists[tid + 16]) {
     dists[tid] = dists[tid + 16];
     dists_idx[tid] = dists_idx[tid + 16];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   if (dists[tid] < dists[tid + 8]) {
     dists[tid] = dists[tid + 8];
     dists_idx[tid] = dists_idx[tid + 8];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   if (dists[tid] < dists[tid + 4]) {
     dists[tid] = dists[tid + 4];
     dists_idx[tid] = dists_idx[tid + 4];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   if (dists[tid] < dists[tid + 2]) {
     dists[tid] = dists[tid + 2];
     dists_idx[tid] = dists_idx[tid + 2];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
   if (dists[tid] < dists[tid + 1]) {
     dists[tid] = dists[tid + 1];
     dists_idx[tid] = dists_idx[tid + 1];
   }
+#if !defined(USE_ROCM)
   __syncwarp();
+#endif
 }

pytorch3d/datasets/__init__.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from .r2n2 import BlenderCamera, collate_batched_R2N2, R2N2, render_cubified_voxels
 from .shapenet import ShapeNetCore
 from .utils import collate_batched_meshes

pytorch3d/datasets/r2n2/__init__.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from .r2n2 import R2N2
 from .utils import BlenderCamera, collate_batched_R2N2, render_cubified_voxels
 

pytorch3d/datasets/r2n2/r2n2.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import json
 import warnings
 from os import path

pytorch3d/datasets/r2n2/utils.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import math
 from typing import Dict, List
 

pytorch3d/datasets/shapenet/__init__.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from .shapenet_core import ShapeNetCore
 
 

pytorch3d/datasets/shapenet/shapenet_core.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import json
 import os
 import warnings

pytorch3d/datasets/shapenet_base.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import warnings
 from typing import Dict, List, Optional, Tuple
 

pytorch3d/datasets/utils.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from typing import Dict, List
 
 from pytorch3d.renderer.mesh import TexturesAtlas

pytorch3d/implicitron/__init__.py

@@ -3,3 +3,5 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe

pytorch3d/implicitron/dataset/__init__.py

@@ -3,3 +3,5 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe

pytorch3d/implicitron/dataset/blender_dataset_map_provider.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import torch
 from pytorch3d.implicitron.tools.config import registry

pytorch3d/implicitron/dataset/data_loader_map_provider.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from dataclasses import dataclass
 from enum import Enum
 from typing import Iterator, List, Optional, Tuple

pytorch3d/implicitron/dataset/data_source.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from typing import Optional, Tuple
 
 from pytorch3d.implicitron.tools.config import (
@@ -39,7 +41,7 @@ class DataSourceBase(ReplaceableBase):
 
 
 @registry.register
-class ImplicitronDataSource(DataSourceBase):  # pyre-ignore[13]
+class ImplicitronDataSource(DataSourceBase):
     """
     Represents the data used in Implicitron. This is the only implementation
     of DataSourceBase provided.
@@ -50,8 +52,11 @@ class ImplicitronDataSource(DataSourceBase):  # pyre-ignore[13]
         data_loader_map_provider_class_type: identifies type for data_loader_map_provider.
     """
 
+    # pyre-fixme[13]: Attribute `dataset_map_provider` is never initialized.
     dataset_map_provider: DatasetMapProviderBase
+    # pyre-fixme[13]: Attribute `dataset_map_provider_class_type` is never initialized.
     dataset_map_provider_class_type: str
+    # pyre-fixme[13]: Attribute `data_loader_map_provider` is never initialized.
     data_loader_map_provider: DataLoaderMapProviderBase
     data_loader_map_provider_class_type: str = "SequenceDataLoaderMapProvider"
 

pytorch3d/implicitron/dataset/dataset_base.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from collections import defaultdict
 from dataclasses import dataclass
 from typing import (

pytorch3d/implicitron/dataset/dataset_map_provider.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import logging
 import os
 from dataclasses import dataclass

pytorch3d/implicitron/dataset/frame_data.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import os
 from abc import ABC, abstractmethod
 from collections import defaultdict
@@ -274,6 +276,7 @@ class FrameData(Mapping[str, Any]):
             image_size_hw=tuple(self.effective_image_size_hw),  # pyre-ignore
         )
         crop_bbox_xywh = bbox_xyxy_to_xywh(clamp_bbox_xyxy)
+        self.crop_bbox_xywh = crop_bbox_xywh
 
         if self.fg_probability is not None:
             self.fg_probability = crop_around_box(
@@ -432,7 +435,7 @@ class FrameData(Mapping[str, Any]):
             # TODO: don't store K; enforce working in NDC space
             return join_cameras_as_batch(batch)
         else:
-            return torch.utils.data._utils.collate.default_collate(batch)
+            return torch.utils.data.dataloader.default_collate(batch)
 
 
 FrameDataSubtype = TypeVar("FrameDataSubtype", bound=FrameData)
@@ -576,11 +579,11 @@ class GenericFrameDataBuilder(FrameDataBuilderBase[FrameDataSubtype], ABC):
             camera_quality_score=safe_as_tensor(
                 sequence_annotation.viewpoint_quality_score, torch.float
             ),
-            point_cloud_quality_score=safe_as_tensor(
+            point_cloud_quality_score=(
-                point_cloud.quality_score, torch.float
+                safe_as_tensor(point_cloud.quality_score, torch.float)
-            )
+                if point_cloud is not None
-            if point_cloud is not None
+                else None
-            else None,
+            ),
         )
 
         fg_mask_np: Optional[np.ndarray] = None

pytorch3d/implicitron/dataset/json_index_dataset.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import copy
 import functools
 import gzip
@@ -124,9 +126,9 @@ class JsonIndexDataset(DatasetBase, ReplaceableBase):
             dimension of the cropping bounding box, relative to box size.
     """
 
-    frame_annotations_type: ClassVar[
+    frame_annotations_type: ClassVar[Type[types.FrameAnnotation]] = (
-        Type[types.FrameAnnotation]
+        types.FrameAnnotation
-    ] = types.FrameAnnotation
+    )
 
     path_manager: Any = None
     frame_annotations_file: str = ""

pytorch3d/implicitron/dataset/json_index_dataset_map_provider.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import json
 import os
@@ -64,7 +66,7 @@ _NEED_CONTROL: Tuple[str, ...] = (
 
 
 @registry.register
-class JsonIndexDatasetMapProvider(DatasetMapProviderBase):  # pyre-ignore [13]
+class JsonIndexDatasetMapProvider(DatasetMapProviderBase):
     """
     Generates the training / validation and testing dataset objects for
     a dataset laid out on disk like Co3D, with annotations in json files.
@@ -93,6 +95,7 @@ class JsonIndexDatasetMapProvider(DatasetMapProviderBase):  # pyre-ignore [13]
         path_manager_factory_class_type: The class type of `path_manager_factory`.
     """
 
+    # pyre-fixme[13]: Attribute `category` is never initialized.
     category: str
     task_str: str = "singlesequence"
     dataset_root: str = _CO3D_DATASET_ROOT
@@ -102,8 +105,10 @@ class JsonIndexDatasetMapProvider(DatasetMapProviderBase):  # pyre-ignore [13]
     test_restrict_sequence_id: int = -1
     assert_single_seq: bool = False
     only_test_set: bool = False
+    # pyre-fixme[13]: Attribute `dataset` is never initialized.
     dataset: JsonIndexDataset
     dataset_class_type: str = "JsonIndexDataset"
+    # pyre-fixme[13]: Attribute `path_manager_factory` is never initialized.
     path_manager_factory: PathManagerFactory
     path_manager_factory_class_type: str = "PathManagerFactory"
 

pytorch3d/implicitron/dataset/json_index_dataset_map_provider_v2.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import copy
 import json
@@ -54,7 +56,7 @@ logger = logging.getLogger(__name__)
 
 
 @registry.register
-class JsonIndexDatasetMapProviderV2(DatasetMapProviderBase):  # pyre-ignore [13]
+class JsonIndexDatasetMapProviderV2(DatasetMapProviderBase):
     """
     Generates the training, validation, and testing dataset objects for
     a dataset laid out on disk like CO3Dv2, with annotations in gzipped json files.
@@ -169,7 +171,9 @@ class JsonIndexDatasetMapProviderV2(DatasetMapProviderBase):  # pyre-ignore [13]
         path_manager_factory_class_type: The class type of `path_manager_factory`.
     """
 
+    # pyre-fixme[13]: Attribute `category` is never initialized.
     category: str
+    # pyre-fixme[13]: Attribute `subset_name` is never initialized.
     subset_name: str
     dataset_root: str = _CO3DV2_DATASET_ROOT
 
@@ -181,8 +185,10 @@ class JsonIndexDatasetMapProviderV2(DatasetMapProviderBase):  # pyre-ignore [13]
     n_known_frames_for_test: int = 0
 
     dataset_class_type: str = "JsonIndexDataset"
+    # pyre-fixme[13]: Attribute `dataset` is never initialized.
     dataset: JsonIndexDataset
 
+    # pyre-fixme[13]: Attribute `path_manager_factory` is never initialized.
     path_manager_factory: PathManagerFactory
     path_manager_factory_class_type: str = "PathManagerFactory"
 

pytorch3d/implicitron/dataset/llff_dataset_map_provider.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import numpy as np
 import torch

pytorch3d/implicitron/dataset/load_blender.py

@@ -1,6 +1,8 @@
 # @lint-ignore-every LICENSELINT
 # Adapted from https://github.com/bmild/nerf/blob/master/load_blender.py
 # Copyright (c) 2020 bmild
+
+# pyre-unsafe
 import json
 import os
 

pytorch3d/implicitron/dataset/load_llff.py

@@ -1,6 +1,8 @@
 # @lint-ignore-every LICENSELINT
 # Adapted from https://github.com/bmild/nerf/blob/master/load_llff.py
 # Copyright (c) 2020 bmild
+
+# pyre-unsafe
 import logging
 import os
 import warnings

pytorch3d/implicitron/dataset/rendered_mesh_dataset_map_provider.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from os.path import dirname, join, realpath
 from typing import Optional, Tuple
 
@@ -30,7 +32,7 @@ from .utils import DATASET_TYPE_KNOWN
 
 
 @registry.register
-class RenderedMeshDatasetMapProvider(DatasetMapProviderBase):  # pyre-ignore [13]
+class RenderedMeshDatasetMapProvider(DatasetMapProviderBase):
     """
     A simple single-scene dataset based on PyTorch3D renders of a mesh.
     Provides `num_views` renders of the mesh as train, with no val
@@ -74,6 +76,7 @@ class RenderedMeshDatasetMapProvider(DatasetMapProviderBase):  # pyre-ignore [13
     resolution: int = 128
     use_point_light: bool = True
     gpu_idx: Optional[int] = 0
+    # pyre-fixme[13]: Attribute `path_manager_factory` is never initialized.
     path_manager_factory: PathManagerFactory
     path_manager_factory_class_type: str = "PathManagerFactory"
 

pytorch3d/implicitron/dataset/scene_batch_sampler.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import warnings
 from collections import Counter

pytorch3d/implicitron/dataset/single_sequence_dataset.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 # This file defines a base class for dataset map providers which
 # provide data for a single scene.
@@ -81,7 +83,6 @@ class SingleSceneDataset(DatasetBase, Configurable):
         return self.eval_batches
 
 
-# pyre-fixme[13]: Uninitialized attribute
 class SingleSceneDatasetMapProviderBase(DatasetMapProviderBase):
     """
     Base for provider of data for one scene from LLFF or blender datasets.
@@ -98,8 +99,11 @@ class SingleSceneDatasetMapProviderBase(DatasetMapProviderBase):
             testing frame.
     """
 
+    # pyre-fixme[13]: Attribute `base_dir` is never initialized.
     base_dir: str
+    # pyre-fixme[13]: Attribute `object_name` is never initialized.
     object_name: str
+    # pyre-fixme[13]: Attribute `path_manager_factory` is never initialized.
     path_manager_factory: PathManagerFactory
     path_manager_factory_class_type: str = "PathManagerFactory"
     n_known_frames_for_test: Optional[int] = None

pytorch3d/implicitron/dataset/train_eval_data_loader_provider.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import logging
 from typing import Any, Dict, Optional, Tuple
 

pytorch3d/implicitron/dataset/types.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import dataclasses
 import gzip

pytorch3d/implicitron/dataset/utils.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import functools
 import warnings
@@ -346,6 +348,7 @@ def adjust_camera_to_image_scale_(
     camera: PerspectiveCameras,
     original_size_wh: torch.Tensor,
     new_size_wh: torch.LongTensor,
+    # pyre-fixme[7]: Expected `PerspectiveCameras` but got implicit return value of `None`.
 ) -> PerspectiveCameras:
     focal_length_px, principal_point_px = _convert_ndc_to_pixels(
         camera.focal_length[0],
@@ -365,7 +368,7 @@ def adjust_camera_to_image_scale_(
         image_size_wh_output,
     )
     camera.focal_length = focal_length_scaled[None]
-    camera.principal_point = principal_point_scaled[None]  # pyre-ignore
+    camera.principal_point = principal_point_scaled[None]
 
 
 # NOTE this cache is per-worker; they are implemented as processes.

pytorch3d/implicitron/dataset/visualize.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from typing import cast, Optional, Tuple
 
 import torch
@@ -88,9 +90,11 @@ def get_implicitron_sequence_pointcloud(
             frame_data.camera,
             frame_data.image_rgb,
             frame_data.depth_map,
-            (cast(torch.Tensor, frame_data.fg_probability) > 0.5).float()
+            (
-            if mask_points and frame_data.fg_probability is not None
+                (cast(torch.Tensor, frame_data.fg_probability) > 0.5).float()
-            else None,
+                if mask_points and frame_data.fg_probability is not None
+                else None
+            ),
         )
 
     return point_cloud, frame_data

pytorch3d/implicitron/eval_demo.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import dataclasses
 import os

pytorch3d/implicitron/evaluation/__init__.py

@@ -3,3 +3,5 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe

pytorch3d/implicitron/evaluation/evaluate_new_view_synthesis.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 import copy
 import warnings
@@ -282,9 +284,9 @@ def eval_batch(
             image_rgb_masked=image_rgb_masked,
             depth_render=cloned_render["depth_render"],
             depth_map=frame_data.depth_map,
-            depth_mask=frame_data.depth_mask[:1]
+            depth_mask=(
-            if frame_data.depth_mask is not None
+                frame_data.depth_mask[:1] if frame_data.depth_mask is not None else None
-            else None,
+            ),
             visdom_env=visualize_visdom_env,
         )
 

pytorch3d/implicitron/evaluation/evaluator.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import copy
 import json
 import logging

pytorch3d/implicitron/models/__init__.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 # Allows to register the models
 # see: pytorch3d.implicitron.tools.config.registry:register
 from pytorch3d.implicitron.models.generic_model import GenericModel

pytorch3d/implicitron/models/base_model.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from dataclasses import dataclass, field
 from typing import Any, Dict, List, Optional
 

pytorch3d/implicitron/models/feature_extractor/__init__.py

@@ -4,4 +4,6 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from .feature_extractor import FeatureExtractorBase

pytorch3d/implicitron/models/feature_extractor/feature_extractor.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from typing import Any, Dict, Optional
 
 import torch

pytorch3d/implicitron/models/feature_extractor/resnet_feature_extractor.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import logging
 import math
 from typing import Any, Dict, Optional, Tuple

pytorch3d/implicitron/models/generic_model.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 
 # Note: The #noqa comments below are for unused imports of pluggable implementations
 # which are part of implicitron. They ensure that the registry is prepopulated.
@@ -63,7 +65,7 @@ logger = logging.getLogger(__name__)
 
 
 @registry.register
-class GenericModel(ImplicitronModelBase):  # pyre-ignore: 13
+class GenericModel(ImplicitronModelBase):
     """
     GenericModel is a wrapper for the neural implicit
     rendering and reconstruction pipeline which consists
@@ -224,34 +226,42 @@ class GenericModel(ImplicitronModelBase):  # pyre-ignore: 13
 
     # ---- global encoder settings
     global_encoder_class_type: Optional[str] = None
+    # pyre-fixme[13]: Attribute `global_encoder` is never initialized.
     global_encoder: Optional[GlobalEncoderBase]
 
     # ---- raysampler
     raysampler_class_type: str = "AdaptiveRaySampler"
+    # pyre-fixme[13]: Attribute `raysampler` is never initialized.
     raysampler: RaySamplerBase
 
     # ---- renderer configs
     renderer_class_type: str = "MultiPassEmissionAbsorptionRenderer"
+    # pyre-fixme[13]: Attribute `renderer` is never initialized.
     renderer: BaseRenderer
 
     # ---- image feature extractor settings
     # (This is only created if view_pooler is enabled)
+    # pyre-fixme[13]: Attribute `image_feature_extractor` is never initialized.
     image_feature_extractor: Optional[FeatureExtractorBase]
     image_feature_extractor_class_type: Optional[str] = None
     # ---- view pooler settings
     view_pooler_enabled: bool = False
+    # pyre-fixme[13]: Attribute `view_pooler` is never initialized.
     view_pooler: Optional[ViewPooler]
 
     # ---- implicit function settings
     implicit_function_class_type: str = "NeuralRadianceFieldImplicitFunction"
     # This is just a model, never constructed.
     # The actual implicit functions live in self._implicit_functions
+    # pyre-fixme[13]: Attribute `implicit_function` is never initialized.
     implicit_function: ImplicitFunctionBase
 
     # ----- metrics
+    # pyre-fixme[13]: Attribute `view_metrics` is never initialized.
     view_metrics: ViewMetricsBase
     view_metrics_class_type: str = "ViewMetrics"
 
+    # pyre-fixme[13]: Attribute `regularization_metrics` is never initialized.
     regularization_metrics: RegularizationMetricsBase
     regularization_metrics_class_type: str = "RegularizationMetrics"
 
@@ -395,9 +405,11 @@ class GenericModel(ImplicitronModelBase):  # pyre-ignore: 13
         n_targets = (
             1
             if evaluation_mode == EvaluationMode.EVALUATION
-            else batch_size
+            else (
-            if self.n_train_target_views <= 0
+                batch_size
-            else min(self.n_train_target_views, batch_size)
+                if self.n_train_target_views <= 0
+                else min(self.n_train_target_views, batch_size)
+            )
         )
 
         # A helper function for selecting n_target first elements from the input
@@ -422,9 +434,12 @@ class GenericModel(ImplicitronModelBase):  # pyre-ignore: 13
         ray_bundle: ImplicitronRayBundle = self.raysampler(
             target_cameras,
             evaluation_mode,
-            mask=mask_crop[:n_targets]
+            mask=(
-            if mask_crop is not None and sampling_mode == RenderSamplingMode.MASK_SAMPLE
+                mask_crop[:n_targets]
-            else None,
+                if mask_crop is not None
+                and sampling_mode == RenderSamplingMode.MASK_SAMPLE
+                else None
+            ),
         )
 
         # custom_args hold additional arguments to the implicit function.

pytorch3d/implicitron/models/global_encoder/__init__.py

@@ -3,3 +3,5 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe

pytorch3d/implicitron/models/global_encoder/autodecoder.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import warnings
 from collections import defaultdict
 from typing import Dict, List, Optional, Union

pytorch3d/implicitron/models/global_encoder/global_encoder.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from typing import List, Optional, Union
 
 import torch
@@ -57,12 +59,13 @@ class GlobalEncoderBase(ReplaceableBase):
 
 # TODO: probabilistic embeddings?
 @registry.register
-class SequenceAutodecoder(GlobalEncoderBase, torch.nn.Module):  # pyre-ignore: 13
+class SequenceAutodecoder(GlobalEncoderBase, torch.nn.Module):
     """
     A global encoder implementation which provides an autodecoder encoding
     of the frame's sequence identifier.
     """
 
+    # pyre-fixme[13]: Attribute `autodecoder` is never initialized.
     autodecoder: Autodecoder
 
     def __post_init__(self):

pytorch3d/implicitron/models/implicit_function/__init__.py

@@ -3,3 +3,5 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe

pytorch3d/implicitron/models/implicit_function/base.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 from abc import ABC, abstractmethod
 from typing import Optional
 

pytorch3d/implicitron/models/implicit_function/decoding_functions.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 """
 This file contains
     - modules which get used by ImplicitFunction objects for decoding an embedding defined in
@@ -242,7 +244,6 @@ class MLPWithInputSkips(Configurable, torch.nn.Module):
 
 
 @registry.register
-# pyre-fixme[13]: Attribute `network` is never initialized.
 class MLPDecoder(DecoderFunctionBase):
     """
     Decoding function which uses `MLPWithIputSkips` to convert the embedding to output.
@@ -270,6 +271,7 @@ class MLPDecoder(DecoderFunctionBase):
 
     input_dim: int = 3
     param_groups: Dict[str, str] = field(default_factory=lambda: {})
+    # pyre-fixme[13]: Attribute `network` is never initialized.
     network: MLPWithInputSkips
 
     def __post_init__(self):

pytorch3d/implicitron/models/implicit_function/idr_feature_field.py

@@ -2,6 +2,8 @@
 # Adapted from https://github.com/lioryariv/idr/blob/main/code/model/
 #              implicit_differentiable_renderer.py
 # Copyright (c) 2020 Lior Yariv
+
+# pyre-unsafe
 import math
 from typing import Optional, Tuple
 
@@ -102,9 +104,7 @@ class IdrFeatureField(ImplicitFunctionBase, torch.nn.Module):
                 elif self.n_harmonic_functions_xyz >= 0 and layer_idx == 0:
                     torch.nn.init.constant_(lin.bias, 0.0)
                     torch.nn.init.constant_(lin.weight[:, 3:], 0.0)
-                    torch.nn.init.normal_(
+                    torch.nn.init.normal_(lin.weight[:, :3], 0.0, 2**0.5 / out_dim**0.5)
-                        lin.weight[:, :3], 0.0, 2**0.5 / out_dim**0.5
-                    )
                 elif self.n_harmonic_functions_xyz >= 0 and layer_idx in self.skip_in:
                     torch.nn.init.constant_(lin.bias, 0.0)
                     torch.nn.init.normal_(lin.weight, 0.0, 2**0.5 / out_dim**0.5)

pytorch3d/implicitron/models/implicit_function/neural_radiance_field.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import logging
 from typing import Optional, Tuple
 
@@ -193,9 +195,9 @@ class NeuralRadianceFieldBase(ImplicitFunctionBase, torch.nn.Module):
         embeds = create_embeddings_for_implicit_function(
             xyz_world=rays_points_world,
             #  for 2nd param but got `Union[None, torch.Tensor, torch.nn.Module]`.
-            xyz_embedding_function=self.harmonic_embedding_xyz
+            xyz_embedding_function=(
-            if self.input_xyz
+                self.harmonic_embedding_xyz if self.input_xyz else None
-            else None,
+            ),
             global_code=global_code,
             fun_viewpool=fun_viewpool,
             xyz_in_camera_coords=self.xyz_ray_dir_in_camera_coords,