Update python to 3.10

.github/workflows/1xH100_tests.yml

@@ -39,7 +39,7 @@ jobs:
       gpu-arch-version: ${{ matrix.gpu-arch-version }}
       submodules: recursive
       script: |
-        conda create -n venv python=3.9 -y
+        conda create -n venv python=3.10 -y
         conda activate venv
         export PATH=/opt/rh/devtoolset-10/root/usr/bin/:$PATH
         python -m pip install --upgrade pip

.github/workflows/1xL4_tests.yml

@@ -39,7 +39,7 @@ jobs:
       gpu-arch-version: ${{ matrix.gpu-arch-version }}
       submodules: recursive
       script: |
-        conda create -n venv python=3.9 -y
+        conda create -n venv python=3.10 -y
         conda activate venv
         export PATH=/opt/rh/devtoolset-10/root/usr/bin/:$PATH
         python -m pip install --upgrade pip

.github/workflows/4xH100_tests.yml

@@ -37,7 +37,7 @@ jobs:
       gpu-arch-version: ${{ matrix.gpu-arch-version }}
       submodules: recursive
       script: |
-        conda create -n venv python=3.9 -y
+        conda create -n venv python=3.10 -y
         conda activate venv
         export PATH=/opt/rh/devtoolset-10/root/usr/bin/:$PATH
         python -m pip install --upgrade pip

.github/workflows/build_wheels_linux.yml

@@ -32,7 +32,7 @@ jobs:
       with-rocm: enable
       with-xpu: enable
       # Note: if free-threaded python is required add py3.13t here
-      python-versions: '["3.9"]'
+      python-versions: '["3.10"]'
 
   build:
     needs: generate-matrix

.github/workflows/regression_test.yml

@@ -45,7 +45,7 @@ jobs:
       gpu-arch-version: ${{ matrix.gpu-arch-version }}
       submodules: recursive
       script: |
-        conda create -n venv python=3.9 -y
+        conda create -n venv python=3.10 -y
         conda activate venv
         python -m pip install --upgrade pip
         pip install ${{ matrix.torch-spec }}
@@ -105,7 +105,7 @@ jobs:
       gpu-arch-version: ${{ matrix.gpu-arch-version }}
       submodules: recursive
       script: |
-        conda create -n venv python=3.9 -y
+        conda create -n venv python=3.10 -y
         conda activate venv
         echo "::group::Install newer objcopy that supports --set-section-alignment"
         dnf install -y gcc-toolset-10-binutils

.github/workflows/regression_test_rocm.yml

@@ -40,7 +40,7 @@ jobs:
       docker-image: ${{ matrix.docker-image }}
       submodules: recursive
       script: |
-        conda create -n venv python=3.9 -y
+        conda create -n venv python=3.10 -y
         conda activate venv
         python -m pip install --upgrade pip
         pip install ${{ matrix.torch-spec }}

setup.py

@@ -16,7 +16,7 @@
 
 current_date = datetime.now().strftime("%Y%m%d")
 
-PY3_9_HEXCODE = "0x03090000"
+min_supported_cpython_hexcode = "0x030A0000"  # Python 3.10 hexcode
 
 
 def get_git_commit_id():
@@ -398,7 +398,7 @@ def get_extensions():
 
     extra_link_args = []
     extra_compile_args = {
-        "cxx": [f"-DPy_LIMITED_API={PY3_9_HEXCODE}"],
+        "cxx": [f"-DPy_LIMITED_API={min_supported_cpython_hexcode}"],
         "nvcc": nvcc_args if use_cuda else rocm_args,
     }
 
@@ -781,5 +781,5 @@ def bool_to_on_off(value):
     long_description_content_type="text/markdown",
     url="https://github.com/pytorch/ao",
     cmdclass={"build_ext": TorchAOBuildExt},
-    options={"bdist_wheel": {"py_limited_api": "cp39"}},
+    options={"bdist_wheel": {"py_limited_api": "cp310"}},
 )

test/quantization/pt2e/test_quantize_pt2e_qat.py

@@ -1104,7 +1104,7 @@ def _prepare_qat_linears(self, model):
                 else:
                     in_channels = child.linear1.weight.size(1)
 
-                example_input = (torch.rand((1, in_channels)),)
+                example_input = (torch.rand((2, 2, 2, in_channels)),)
                 traced_child = torch.export.export(
                     child, example_input, strict=True
                 ).module()

test/quantization/pt2e/test_x86inductor_fusion.py

@@ -2457,6 +2457,8 @@ def forward(self, x):
 
         mod = M().eval()
         v = torch.randn((2, 3, 8, 8), dtype=torch.float32, requires_grad=False).add(1)
+        # Mark the batch dimension (dimension 0) as dynamic for proper dynamic shape testing
+        torch._dynamo.mark_dynamic(v, 0)
         if include_ops is None:
             include_ops = [
                 "torch.ops.onednn.qconv_pointwise",

torchao/quantization/pt2e/_numeric_debugger.py

@@ -114,10 +114,14 @@ def _get_greatest_ancestor_node_source(node: Node) -> "NodeSource":
         return node_source
 
     def _is_node_in_original_graph(node: Node) -> bool:
+        # Handle guard nodes that don't have from_node metadata in newer PyTorch versions
+        if FROM_NODE_KEY not in node.meta or node.meta[FROM_NODE_KEY] is None:
+            # Guard nodes (like _guards_fn) created by newer PyTorch versions might not have from_node metadata
+            # Skip these nodes as they are not part of the original user graph
+            return False
+
         if (
-            FROM_NODE_KEY not in node.meta
-            or node.meta[FROM_NODE_KEY] is None
-            or node.meta[FROM_NODE_KEY][-1].pass_name
+            node.meta[FROM_NODE_KEY][-1].pass_name
             == "ExportedProgram.module().unlift()"
         ):
             # This node is not part of the ExportedProgram.module().graph, so it doesn't have a debug handle