Drop support for pytorch 1.12 and 1.13

.github/workflows/publish.yaml

@@ -43,8 +43,8 @@ jobs:
           # Using ubuntu-20.04 instead of 22.04 for more compatibility (glibc). Ideally we'd use the
           # manylinux docker image, but I haven't figured out how to install CUDA on manylinux.
           os: [ubuntu-20.04]
-          python-version: ['3.7', '3.8', '3.9', '3.10', '3.11', '3.12']
-          torch-version: ['1.12.1', '1.13.1', '2.0.1', '2.1.2', '2.2.2', '2.3.0', '2.4.0.dev20240420']
+          python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
+          torch-version: ['2.0.1', '2.1.2', '2.2.2', '2.3.1', '2.4.0.dev20240505']
           cuda-version: ['11.8.0', '12.2.2']
           # We need separate wheels that either uses C++11 ABI (-D_GLIBCXX_USE_CXX11_ABI) or not.
           # Pytorch wheels currently don't use it, but nvcr images have Pytorch compiled with C++11 ABI.
@@ -53,33 +53,11 @@ jobs:
           cxx11_abi: ['FALSE', 'TRUE']
           exclude:
             # Pytorch < 2.2 does not support Python 3.12
-            - torch-version: '1.12.1'
-              python-version: '3.12'
-            - torch-version: '1.13.1'
-              python-version: '3.12'
             - torch-version: '2.0.1'
               python-version: '3.12'
             - torch-version: '2.1.2'
               python-version: '3.12'
-            # Pytorch <= 1.12 does not support Python 3.11
-            - torch-version: '1.12.1'
-              python-version: '3.11'
-            # Pytorch >= 2.0 only supports Python >= 3.8
-            - torch-version: '2.0.1'
-              python-version: '3.7'
-            - torch-version: '2.1.2'
-              python-version: '3.7'
-            - torch-version: '2.2.2'
-              python-version: '3.7'
-            - torch-version: '2.3.0'
-              python-version: '3.7'
-            - torch-version: '2.4.0.dev20240420'
-              python-version: '3.7'
             # Pytorch <= 2.0 only supports CUDA <= 11.8
-            - torch-version: '1.12.1'
-              cuda-version: '12.2.2'
-            - torch-version: '1.13.1'
-              cuda-version: '12.2.2'
             - torch-version: '2.0.1'
               cuda-version: '12.2.2'
 
@@ -138,8 +116,8 @@ jobs:
           # e.g. we can have system CUDA version being 11.7 but if torch==1.12 then we need to download the wheel from cu116
           # This code is ugly, maybe there's a better way to do this.
           export TORCH_CUDA_VERSION=$(python -c "from os import environ as env; \
-            minv = {'1.12': 113, '1.13': 116, '2.0': 117, '2.1': 118, '2.2': 118, '2.3': 118, '2.4': 118}[env['MATRIX_TORCH_VERSION']]; \
-            maxv = {'1.12': 116, '1.13': 117, '2.0': 118, '2.1': 121, '2.2': 121, '2.3': 121, '2.4': 121}[env['MATRIX_TORCH_VERSION']]; \
+            minv = {'2.0': 117, '2.1': 118, '2.2': 118, '2.3': 118, '2.4': 118}[env['MATRIX_TORCH_VERSION']]; \
+            maxv = {'2.0': 118, '2.1': 121, '2.2': 121, '2.3': 121, '2.4': 121}[env['MATRIX_TORCH_VERSION']]; \
             print(max(min(int(env['MATRIX_CUDA_VERSION']), maxv), minv))" \
           )
           if [[ ${{ matrix.torch-version }} == *"dev"* ]]; then

setup.py

@@ -207,7 +207,6 @@ def append_nvcc_threads(nvcc_extra_args):
                 f"--offload-arch={os.getenv('HIP_ARCHITECTURES', 'native')}",
                 "-U__CUDA_NO_HALF_OPERATORS__",
                 "-U__CUDA_NO_HALF_CONVERSIONS__",
-                "-DCK_FMHA_FWD_FAST_EXP2=1",
                 "-fgpu-flush-denormals-to-zero",
             ]
             + cc_flag,
@@ -367,7 +366,7 @@ def run(self):
     else {
         "bdist_wheel": CachedWheelsCommand,
     },
-    python_requires=">=3.7",
+    python_requires=">=3.8",
     install_requires=[
         "torch",
         "packaging",