python3Packages.pytorch: add compute capabilities for CUDA 11

CUDA 11 supports capabilities 8.0 and 8.6. The change adds these
capabilities when CUDA 11 is used, enabling support for Ampere GPUs.

pkgs/development/python-modules/pytorch/default.nix

@@ -74,27 +74,35 @@ let
   # (allowing FBGEMM to be built in pytorch-1.1), and may future proof this
   # derivation.
   brokenArchs = [ "3.0" ]; # this variable is only used as documentation.
-  cuda9ArchList = [
-    "3.5"
-    "5.0"
-    "5.2"
-    "6.0"
-    "6.1"
-    "7.0"
-    "7.0+PTX"  # I am getting a "undefined architecture compute_75" on cuda 9
-               # which leads me to believe this is the final cuda-9-compatible architecture.
-  ];
-  cuda10ArchList = cuda9ArchList ++ [
-    "7.5"
-    "7.5+PTX"  # < most recent architecture as of cudatoolkit_10_0 and pytorch-1.2.0
-  ];
+
+  cudaCapabilities = rec {
+    cuda9 = [
+      "3.5"
+      "5.0"
+      "5.2"
+      "6.0"
+      "6.1"
+      "7.0"
+      "7.0+PTX"  # I am getting a "undefined architecture compute_75" on cuda 9
+                 # which leads me to believe this is the final cuda-9-compatible architecture.
+    ];
+
+    cuda10 = cuda9 ++ [
+      "7.5"
+      "7.5+PTX"  # < most recent architecture as of cudatoolkit_10_0 and pytorch-1.2.0
+    ];
+
+    cuda11 = cuda10 ++ [
+      "8.0"
+      "8.0+PTX"  # < CUDA toolkit 11.0
+      "8.6"
+      "8.6+PTX"  # < CUDA toolkit 11.1
+    ];
+  };
   final_cudaArchList =
     if !cudaSupport || cudaArchList != null
     then cudaArchList
-    else
-      if lib.versions.major cudatoolkit.version == "9"
-      then cuda9ArchList
-      else cuda10ArchList; # the assert above removes any ambiguity here.
+    else cudaCapabilities."cuda${lib.versions.major cudatoolkit.version}";
 
   # Normally libcuda.so.1 is provided at runtime by nvidia-x11 via
   # LD_LIBRARY_PATH=/run/opengl-driver/lib.  We only use the stub