Builds with pytorch 1.5

Summary:
Add conda packages for pytorch 1.5. Make wheels be only pytorch 1.5.

Note that pytorch 1.4 has conda packages for cuda 9.2, 10.0 and 10.1, whilst pytorch 1.5 has packages for cuda 9.2, 10.1 and 10.2. We mirror these choices.

Reviewed By: nikhilaravi

Differential Revision: D21157392

fbshipit-source-id: 2f7311e6a83774a6d6c8afb8110b8bd9f37f1454

.circleci/config.in.yml

@@ -207,22 +207,27 @@ workflows:
       - main
       {{workflows()}}
       - binary_linux_conda_cuda:
-          name: testrun_conda_cuda_py3.7_cu100
+          name: testrun_conda_cuda_py37_cu100_pyt14
           python_version: "3.7"
           pytorch_version: "1.4"
           cu_version: "cu100"
+      - binary_linux_conda_cuda:
+          name: testrun_conda_cuda_py37_cu102_pyt15
+          python_version: "3.7"
+          pytorch_version: "1.5"
+          cu_version: "cu102"
       - binary_macos_wheel:
           cu_version: cpu
-          name: macos_wheel_py3.6_cpu
+          name: macos_wheel_py36_cpu
           python_version: '3.6'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'
       - binary_macos_wheel:
           cu_version: cpu
-          name: macos_wheel_py3.7_cpu
+          name: macos_wheel_py37_cpu
           python_version: '3.7'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'
       - binary_macos_wheel:
           cu_version: cpu
-          name: macos_wheel_py3.8_cpu
+          name: macos_wheel_py38_cpu
           python_version: '3.8'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'

.circleci/config.yml

@@ -207,87 +207,131 @@ workflows:
       - main
       - binary_linux_conda:
           cu_version: cu92
-          name: binary_linux_conda_py3.6_cu92
+          name: linux_conda_py36_cu92_pyt14
           python_version: '3.6'
           pytorch_version: '1.4'
-          wheel_docker_image: pytorch/manylinux-cuda92
       - binary_linux_conda:
           cu_version: cu100
-          name: binary_linux_conda_py3.6_cu100
+          name: linux_conda_py36_cu100_pyt14
           python_version: '3.6'
           pytorch_version: '1.4'
-          wheel_docker_image: pytorch/manylinux-cuda100
       - binary_linux_conda:
           cu_version: cu101
-          name: binary_linux_conda_py3.6_cu101
+          name: linux_conda_py36_cu101_pyt14
           python_version: '3.6'
           pytorch_version: '1.4'
       - binary_linux_conda:
           cu_version: cu92
-          name: binary_linux_conda_py3.7_cu92
+          name: linux_conda_py36_cu92_pyt15
+          python_version: '3.6'
+          pytorch_version: '1.5'
+      - binary_linux_conda:
+          cu_version: cu101
+          name: linux_conda_py36_cu101_pyt15
+          python_version: '3.6'
+          pytorch_version: '1.5'
+      - binary_linux_conda:
+          cu_version: cu102
+          name: linux_conda_py36_cu102_pyt15
+          python_version: '3.6'
+          pytorch_version: '1.5'
+      - binary_linux_conda:
+          cu_version: cu92
+          name: linux_conda_py37_cu92_pyt14
           python_version: '3.7'
           pytorch_version: '1.4'
-          wheel_docker_image: pytorch/manylinux-cuda92
       - binary_linux_conda:
           cu_version: cu100
-          name: binary_linux_conda_py3.7_cu100
+          name: linux_conda_py37_cu100_pyt14
           python_version: '3.7'
           pytorch_version: '1.4'
-          wheel_docker_image: pytorch/manylinux-cuda100
       - binary_linux_conda:
           cu_version: cu101
-          name: binary_linux_conda_py3.7_cu101
+          name: linux_conda_py37_cu101_pyt14
           python_version: '3.7'
           pytorch_version: '1.4'
       - binary_linux_conda:
           cu_version: cu92
-          name: binary_linux_conda_py3.8_cu92
+          name: linux_conda_py37_cu92_pyt15
+          python_version: '3.7'
+          pytorch_version: '1.5'
+      - binary_linux_conda:
+          cu_version: cu101
+          name: linux_conda_py37_cu101_pyt15
+          python_version: '3.7'
+          pytorch_version: '1.5'
+      - binary_linux_conda:
+          cu_version: cu102
+          name: linux_conda_py37_cu102_pyt15
+          python_version: '3.7'
+          pytorch_version: '1.5'
+      - binary_linux_conda:
+          cu_version: cu92
+          name: linux_conda_py38_cu92_pyt14
           python_version: '3.8'
           pytorch_version: '1.4'
-          wheel_docker_image: pytorch/manylinux-cuda92
       - binary_linux_conda:
           cu_version: cu100
-          name: binary_linux_conda_py3.8_cu100
+          name: linux_conda_py38_cu100_pyt14
           python_version: '3.8'
           pytorch_version: '1.4'
-          wheel_docker_image: pytorch/manylinux-cuda100
       - binary_linux_conda:
           cu_version: cu101
-          name: binary_linux_conda_py3.8_cu101
+          name: linux_conda_py38_cu101_pyt14
           python_version: '3.8'
           pytorch_version: '1.4'
+      - binary_linux_conda:
+          cu_version: cu92
+          name: linux_conda_py38_cu92_pyt15
+          python_version: '3.8'
+          pytorch_version: '1.5'
+      - binary_linux_conda:
+          cu_version: cu101
+          name: linux_conda_py38_cu101_pyt15
+          python_version: '3.8'
+          pytorch_version: '1.5'
+      - binary_linux_conda:
+          cu_version: cu102
+          name: linux_conda_py38_cu102_pyt15
+          python_version: '3.8'
+          pytorch_version: '1.5'
       - binary_linux_wheel:
           cu_version: cpu
-          name: binary_linux_wheel_py3.6_cpu
+          name: linux_wheel_py36_cpu_pyt15
           python_version: '3.6'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'
       - binary_linux_wheel:
           cu_version: cpu
-          name: binary_linux_wheel_py3.7_cpu
+          name: linux_wheel_py37_cpu_pyt15
           python_version: '3.7'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'
       - binary_linux_wheel:
           cu_version: cpu
-          name: binary_linux_wheel_py3.8_cpu
+          name: linux_wheel_py38_cpu_pyt15
           python_version: '3.8'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'
       - binary_linux_conda_cuda:
-          name: testrun_conda_cuda_py3.7_cu100
+          name: testrun_conda_cuda_py37_cu100_pyt14
           python_version: "3.7"
           pytorch_version: "1.4"
           cu_version: "cu100"
+      - binary_linux_conda_cuda:
+          name: testrun_conda_cuda_py37_cu102_pyt15
+          python_version: "3.7"
+          pytorch_version: "1.5"
+          cu_version: "cu102"
       - binary_macos_wheel:
           cu_version: cpu
-          name: macos_wheel_py3.6_cpu
+          name: macos_wheel_py36_cpu
           python_version: '3.6'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'
       - binary_macos_wheel:
           cu_version: cpu
-          name: macos_wheel_py3.7_cpu
+          name: macos_wheel_py37_cpu
           python_version: '3.7'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'
       - binary_macos_wheel:
           cu_version: cpu
-          name: macos_wheel_py3.8_cpu
+          name: macos_wheel_py38_cpu
           python_version: '3.8'
-          pytorch_version: '1.4'
+          pytorch_version: '1.5'

.circleci/regenerate.py

@@ -11,25 +11,36 @@ import jinja2
 import yaml
 
 
+# The CUDA versions which have pytorch conda packages available for linux for each
+# version of pytorch.
+CONDA_CUDA_VERSIONS = {
+    "1.4": ["cu92", "cu100", "cu101"],
+    "1.5": ["cu92", "cu101", "cu102"],
+}
+
+
 def workflows(prefix="", filter_branch=None, upload=False, indentation=6):
     w = []
     for btype in ["conda"]:
         for python_version in ["3.6", "3.7", "3.8"]:
-            for cu_version in ["cu92", "cu100", "cu101"]:
-                w += workflow_pair(
-                    btype=btype,
-                    python_version=python_version,
-                    cu_version=cu_version,
-                    prefix=prefix,
-                    upload=upload,
-                    filter_branch=filter_branch,
-                )
+            for pytorch_version in ["1.4", "1.5"]:
+                for cu_version in CONDA_CUDA_VERSIONS[pytorch_version]:
+                    w += workflow_pair(
+                        btype=btype,
+                        python_version=python_version,
+                        pytorch_version=pytorch_version,
+                        cu_version=cu_version,
+                        prefix=prefix,
+                        upload=upload,
+                        filter_branch=filter_branch,
+                    )
     for btype in ["wheel"]:
         for python_version in ["3.6", "3.7", "3.8"]:
             for cu_version in ["cpu"]:
                 w += workflow_pair(
                     btype=btype,
                     python_version=python_version,
+                    pytorch_version="1.5",
                     cu_version=cu_version,
                     prefix=prefix,
                     upload=upload,
@@ -40,16 +51,26 @@ def workflows(prefix="", filter_branch=None, upload=False, indentation=6):
 
 
 def workflow_pair(
-    *, btype, python_version, cu_version, prefix="", upload=False, filter_branch
+    *,
+    btype,
+    python_version,
+    pytorch_version,
+    cu_version,
+    prefix="",
+    upload=False,
+    filter_branch,
 ):
 
     w = []
-    base_workflow_name = f"{prefix}binary_linux_{btype}_py{python_version}_{cu_version}"
+    py = python_version.replace(".", "")
+    pyt = pytorch_version.replace(".", "")
+    base_workflow_name = f"{prefix}linux_{btype}_py{py}_{cu_version}_pyt{pyt}"
 
     w.append(
         generate_base_workflow(
             base_workflow_name=base_workflow_name,
             python_version=python_version,
+            pytorch_version=pytorch_version,
             cu_version=cu_version,
             btype=btype,
             filter_branch=filter_branch,
@@ -70,21 +91,22 @@ def workflow_pair(
 
 
 def generate_base_workflow(
-    *, base_workflow_name, python_version, cu_version, btype, filter_branch=None
+    *,
+    base_workflow_name,
+    python_version,
+    cu_version,
+    pytorch_version,
+    btype,
+    filter_branch=None,
 ):
 
     d = {
         "name": base_workflow_name,
         "python_version": python_version,
         "cu_version": cu_version,
-        "pytorch_version": "1.4",
+        "pytorch_version": pytorch_version,
     }
 
-    if cu_version == "cu92":
-        d["wheel_docker_image"] = "pytorch/manylinux-cuda92"
-    elif cu_version == "cu100":
-        d["wheel_docker_image"] = "pytorch/manylinux-cuda100"
-
     if filter_branch is not None:
         d["filters"] = {"branches": {"only": filter_branch}}
 

INSTALL.md

@@ -9,17 +9,17 @@ The core library is written in PyTorch. Several components have underlying imple
 
 - Linux or macOS or Windows
 - Python ≥ 3.6
-- PyTorch 1.4
+- PyTorch 1.4 or 1.5
 - torchvision that matches the PyTorch installation. You can install them together at pytorch.org to make sure of this.
 - gcc & g++ ≥ 4.9
-- CUDA 9.2 or 10.0 or 10.1
 - [fvcore](https://github.com/facebookresearch/fvcore)
+- If CUDA is to be used, use at least version 9.2.
 
 These can be installed by running:
 ```
 conda create -n pytorch3d python=3.8
 conda activate pytorch3d
-conda install -c pytorch pytorch torchvision cudatoolkit=10.0
+conda install -c pytorch pytorch torchvision cudatoolkit=10.2
 conda install -c conda-forge -c fvcore fvcore
 ```