pytorch 2.1, drop mac builds

Summary: Build updates for PyTorch 2.1

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50345762

fbshipit-source-id: 89bf4edf1c21566aa86a3abca9b4df7c4d1d17a2

.circleci/config.in.yml

@@ -156,24 +156,6 @@ jobs:
 
           docker run --gpus all  --ipc=host -v $(pwd):/remote -w /remote ${VARS_TO_PASS} ${TESTRUN_DOCKER_IMAGE} python3 ./packaging/build_conda.py
 
-  binary_macos_wheel:
-    <<: *binary_common
-    macos:
-      xcode: "13.4.1"
-    steps:
-      - checkout
-      - run:
-          # Cannot easily deduplicate this as source'ing activate
-          # will set environment variables which we need to propagate
-          # to build_wheel.sh
-          command: |
-            curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-            sh conda.sh -b
-            source $HOME/miniconda3/bin/activate
-            packaging/build_wheel.sh
-      - store_artifacts:
-          path: dist
-
 workflows:
   version: 2
   build_and_test:
@@ -187,18 +169,3 @@ workflows:
           python_version: "3.8"
           pytorch_version: '1.9.0'
           cu_version: "cu102"
-      - binary_macos_wheel:
-          cu_version: cpu
-          name: macos_wheel_py3.8_cpu
-          python_version: '3.8'
-          pytorch_version: '1.13.0'
-      - binary_macos_wheel:
-          cu_version: cpu
-          name: macos_wheel_py3.9_cpu
-          python_version: '3.9'
-          pytorch_version: '1.13.0'
-      - binary_macos_wheel:
-          cu_version: cpu
-          name: macos_wheel_py3.10_cpu
-          python_version: '3.10'
-          pytorch_version: '1.13.0'

.circleci/config.yml

@@ -156,113 +156,12 @@ jobs:
 
           docker run --gpus all  --ipc=host -v $(pwd):/remote -w /remote ${VARS_TO_PASS} ${TESTRUN_DOCKER_IMAGE} python3 ./packaging/build_conda.py
 
-  binary_macos_wheel:
-    <<: *binary_common
-    macos:
-      xcode: "13.4.1"
-    steps:
-      - checkout
-      - run:
-          # Cannot easily deduplicate this as source'ing activate
-          # will set environment variables which we need to propagate
-          # to build_wheel.sh
-          command: |
-            curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-            sh conda.sh -b
-            source $HOME/miniconda3/bin/activate
-            packaging/build_wheel.sh
-      - store_artifacts:
-          path: dist
-
 workflows:
   version: 2
   build_and_test:
     jobs:
       # - main:
       #     context: DOCKERHUB_TOKEN
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py38_cu102_pyt1100
-          python_version: '3.8'
-          pytorch_version: 1.10.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu111
-          name: linux_conda_py38_cu111_pyt1100
-          python_version: '3.8'
-          pytorch_version: 1.10.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py38_cu113_pyt1100
-          python_version: '3.8'
-          pytorch_version: 1.10.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py38_cu102_pyt1101
-          python_version: '3.8'
-          pytorch_version: 1.10.1
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu111
-          name: linux_conda_py38_cu111_pyt1101
-          python_version: '3.8'
-          pytorch_version: 1.10.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py38_cu113_pyt1101
-          python_version: '3.8'
-          pytorch_version: 1.10.1
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py38_cu102_pyt1102
-          python_version: '3.8'
-          pytorch_version: 1.10.2
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu111
-          name: linux_conda_py38_cu111_pyt1102
-          python_version: '3.8'
-          pytorch_version: 1.10.2
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py38_cu113_pyt1102
-          python_version: '3.8'
-          pytorch_version: 1.10.2
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py38_cu102_pyt1110
-          python_version: '3.8'
-          pytorch_version: 1.11.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu111
-          name: linux_conda_py38_cu111_pyt1110
-          python_version: '3.8'
-          pytorch_version: 1.11.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py38_cu113_pyt1110
-          python_version: '3.8'
-          pytorch_version: 1.11.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda115
-          context: DOCKERHUB_TOKEN
-          cu_version: cu115
-          name: linux_conda_py38_cu115_pyt1110
-          python_version: '3.8'
-          pytorch_version: 1.11.0
       - binary_linux_conda:
           context: DOCKERHUB_TOKEN
           cu_version: cu102
@@ -360,88 +259,19 @@ workflows:
           python_version: '3.8'
           pytorch_version: 2.0.1
       - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
-          cu_version: cu102
+          cu_version: cu118
-          name: linux_conda_py39_cu102_pyt1100
+          name: linux_conda_py38_cu118_pyt210
-          python_version: '3.9'
+          python_version: '3.8'
-          pytorch_version: 1.10.0
+          pytorch_version: 2.1.0
       - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
           context: DOCKERHUB_TOKEN
-          cu_version: cu111
+          cu_version: cu121
-          name: linux_conda_py39_cu111_pyt1100
+          name: linux_conda_py38_cu121_pyt210
-          python_version: '3.9'
+          python_version: '3.8'
-          pytorch_version: 1.10.0
+          pytorch_version: 2.1.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py39_cu113_pyt1100
-          python_version: '3.9'
-          pytorch_version: 1.10.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py39_cu102_pyt1101
-          python_version: '3.9'
-          pytorch_version: 1.10.1
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu111
-          name: linux_conda_py39_cu111_pyt1101
-          python_version: '3.9'
-          pytorch_version: 1.10.1
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py39_cu113_pyt1101
-          python_version: '3.9'
-          pytorch_version: 1.10.1
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py39_cu102_pyt1102
-          python_version: '3.9'
-          pytorch_version: 1.10.2
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu111
-          name: linux_conda_py39_cu111_pyt1102
-          python_version: '3.9'
-          pytorch_version: 1.10.2
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py39_cu113_pyt1102
-          python_version: '3.9'
-          pytorch_version: 1.10.2
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py39_cu102_pyt1110
-          python_version: '3.9'
-          pytorch_version: 1.11.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu111
-          name: linux_conda_py39_cu111_pyt1110
-          python_version: '3.9'
-          pytorch_version: 1.11.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py39_cu113_pyt1110
-          python_version: '3.9'
-          pytorch_version: 1.11.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda115
-          context: DOCKERHUB_TOKEN
-          cu_version: cu115
-          name: linux_conda_py39_cu115_pyt1110
-          python_version: '3.9'
-          pytorch_version: 1.11.0
       - binary_linux_conda:
           context: DOCKERHUB_TOKEN
           cu_version: cu102
@@ -539,31 +369,19 @@ workflows:
           python_version: '3.9'
           pytorch_version: 2.0.1
       - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
           context: DOCKERHUB_TOKEN
-          cu_version: cu102
+          cu_version: cu118
-          name: linux_conda_py310_cu102_pyt1110
+          name: linux_conda_py39_cu118_pyt210
-          python_version: '3.10'
+          python_version: '3.9'
-          pytorch_version: 1.11.0
+          pytorch_version: 2.1.0
       - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
           context: DOCKERHUB_TOKEN
-          cu_version: cu111
+          cu_version: cu121
-          name: linux_conda_py310_cu111_pyt1110
+          name: linux_conda_py39_cu121_pyt210
-          python_version: '3.10'
+          python_version: '3.9'
-          pytorch_version: 1.11.0
+          pytorch_version: 2.1.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda113
-          context: DOCKERHUB_TOKEN
-          cu_version: cu113
-          name: linux_conda_py310_cu113_pyt1110
-          python_version: '3.10'
-          pytorch_version: 1.11.0
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda115
-          context: DOCKERHUB_TOKEN
-          cu_version: cu115
-          name: linux_conda_py310_cu115_pyt1110
-          python_version: '3.10'
-          pytorch_version: 1.11.0
       - binary_linux_conda:
           context: DOCKERHUB_TOKEN
           cu_version: cu102
@@ -660,24 +478,37 @@ workflows:
           name: linux_conda_py310_cu118_pyt201
           python_version: '3.10'
           pytorch_version: 2.0.1
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py310_cu118_pyt210
+          python_version: '3.10'
+          pytorch_version: 2.1.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py310_cu121_pyt210
+          python_version: '3.10'
+          pytorch_version: 2.1.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda118
+          context: DOCKERHUB_TOKEN
+          cu_version: cu118
+          name: linux_conda_py311_cu118_pyt210
+          python_version: '3.11'
+          pytorch_version: 2.1.0
+      - binary_linux_conda:
+          conda_docker_image: pytorch/conda-builder:cuda121
+          context: DOCKERHUB_TOKEN
+          cu_version: cu121
+          name: linux_conda_py311_cu121_pyt210
+          python_version: '3.11'
+          pytorch_version: 2.1.0
       - binary_linux_conda_cuda:
           name: testrun_conda_cuda_py38_cu102_pyt190
           context: DOCKERHUB_TOKEN
           python_version: "3.8"
           pytorch_version: '1.9.0'
           cu_version: "cu102"
-      - binary_macos_wheel:
-          cu_version: cpu
-          name: macos_wheel_py3.8_cpu
-          python_version: '3.8'
-          pytorch_version: '1.13.0'
-      - binary_macos_wheel:
-          cu_version: cpu
-          name: macos_wheel_py3.9_cpu
-          python_version: '3.9'
-          pytorch_version: '1.13.0'
-      - binary_macos_wheel:
-          cu_version: cpu
-          name: macos_wheel_py3.10_cpu
-          python_version: '3.10'
-          pytorch_version: '1.13.0'

.circleci/regenerate.py

@@ -20,16 +20,13 @@ from packaging import version
 # version of pytorch.
 # Pytorch 1.4 also supports cuda 10.0 but we no longer build for cuda 10.0 at all.
 CONDA_CUDA_VERSIONS = {
-    "1.10.0": ["cu102", "cu111", "cu113"],
-    "1.10.1": ["cu102", "cu111", "cu113"],
-    "1.10.2": ["cu102", "cu111", "cu113"],
-    "1.11.0": ["cu102", "cu111", "cu113", "cu115"],
     "1.12.0": ["cu102", "cu113", "cu116"],
     "1.12.1": ["cu102", "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"],
 }
 
 
@@ -50,12 +47,18 @@ def pytorch_versions_for_python(python_version):
             for i in CONDA_CUDA_VERSIONS
             if version.Version(i) >= version.Version("1.11.0")
         ]
+    if python_version == "3.11":
+        return [
+            i
+            for i in CONDA_CUDA_VERSIONS
+            if version.Version(i) >= version.Version("2.1.0")
+        ]
 
 
 def workflows(prefix="", filter_branch=None, upload=False, indentation=6):
     w = []
     for btype in ["conda"]:
-        for python_version in ["3.8", "3.9", "3.10"]:
+        for python_version in ["3.8", "3.9", "3.10", "3.11"]:
             for pytorch_version in pytorch_versions_for_python(python_version):
                 for cu_version in CONDA_CUDA_VERSIONS[pytorch_version]:
                     w += workflow_pair(

INSTALL.md

@@ -9,7 +9,7 @@ The core library is written in PyTorch. Several components have underlying imple
 
 - Linux or macOS or Windows
 - Python 3.8, 3.9 or 3.10
-- PyTorch 1.10.0, 1.10.1, 1.10.2, 1.11.0, 1.12.0, 1.12.1, 1.13.0, 2.0.0 or 2.0.1.
+- PyTorch 1.12.0, 1.12.1, 1.13.0, 2.0.0, 2.0.1 or 2.1.0.
 - 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)
@@ -77,13 +77,8 @@ Or, to install a nightly (non-official, alpha) build:
 # Anaconda Cloud
 conda install pytorch3d -c pytorch3d-nightly
 ```
-### 2. Install from PyPI, on Mac only.
-This works with pytorch 1.13.0 only. The build is CPU only.
-```
-pip install pytorch3d
-```
 
-### 3. Install wheels for Linux
+### 2. Install wheels for Linux
 We have prebuilt wheels with CUDA for Linux for PyTorch 1.11.0, for each of the supported CUDA versions,
 for Python 3.8 and 3.9. This is for ease of use on Google Colab.
 These are installed in a special way.

packaging/build_conda.py

@@ -59,12 +59,17 @@ def setup_cuda():
     )
     if CU_VERSION == "cu102":
         nvcc_flags = basic_nvcc_flags
-    elif CU_VERSION == "cu110":
+    elif CU_VERSION < ("cu118"):
-        nvcc_flags = "-gencode=arch=compute_80,code=sm_80 " + basic_nvcc_flags
+        nvcc_flags = (
+            "-gencode=arch=compute_80,code=sm_80 "
+            + "-gencode=arch=compute_86,code=sm_86 "
+            + basic_nvcc_flags
+        )
     else:
         nvcc_flags = (
             "-gencode=arch=compute_80,code=sm_80 "
             + "-gencode=arch=compute_86,code=sm_86 "
+            + "-gencode=arch=compute_90,code=sm_90 "
             + basic_nvcc_flags
         )
 

setup.py

@@ -49,7 +49,7 @@ def get_extensions():
     source_cuda = glob.glob(os.path.join(extensions_dir, "**", "*.cu"), recursive=True)
     extension = CppExtension
 
-    extra_compile_args = {"cxx": ["-std=c++14"]}
+    extra_compile_args = {"cxx": ["-std=c++17"]}
     define_macros = []
     include_dirs = [extensions_dir]
 
@@ -74,7 +74,7 @@ def get_extensions():
             "-D__CUDA_NO_HALF2_OPERATORS__",
         ]
         if os.name != "nt":
-            nvcc_args.append("-std=c++14")
+            nvcc_args.append("-std=c++17")
         if cub_home is None:
             prefix = os.environ.get("CONDA_PREFIX", None)
             if prefix is not None and os.path.isdir(prefix + "/include/cub"):