[Relax][PyTorch] Fix PyTorch Dynamo frontend for Darwin compatibility (#18619)

## Why

The llvm_target() function reads `/proc/cpuinfo` which only exists on
`Linux`, causing tests to fail on `macOS` with FileNotFoundError.

## How

- Add cross-platform CPU feature detection in llvm_target() using
platform.system() and sysctl for macOS
- Update tests

Author: guan404ming

python/tvm/relax/frontend/torch/dynamo.py

@@ -19,6 +19,7 @@
 # pylint: disable=import-outside-toplevel, unused-argument, use-list-literal
 # mypy: ignore-errors
 """PyTorch Dynamo backend of Relax."""
+
 import functools
 from typing import Optional
 
@@ -202,6 +203,43 @@ def _capture(graph_module: fx.GraphModule, example_inputs):
 
 @functools.lru_cache(None)
 def llvm_target():
-    if "avx512" in open("/proc/cpuinfo").read():
-        return "llvm -mcpu=skylake-avx512"
-    return "llvm -mcpu=core-avx2"
+    import platform
+    import subprocess
+
+    AVX512_TARGET = "llvm -mcpu=skylake-avx512"
+    AVX2_TARGET = "llvm -mcpu=core-avx2"
+    DEFAULT_TARGET = "llvm"
+
+    system = platform.system()
+
+    if system == "Linux":
+        try:
+            with open("/proc/cpuinfo") as f:
+                cpuinfo = f.read()
+            if "avx512" in cpuinfo:
+                return AVX512_TARGET
+            return AVX2_TARGET
+        except FileNotFoundError:
+            pass
+    elif system == "Darwin":
+        try:
+            result = subprocess.run(
+                ["sysctl", "-n", "machdep.cpu.features"],
+                capture_output=True,
+                text=True,
+                check=False,
+            )
+            if result.returncode == 0:
+                cpu_features = result.stdout.lower()
+                if "avx512" in cpu_features:
+                    return AVX512_TARGET
+                if "avx2" in cpu_features:
+                    return AVX2_TARGET
+        except (FileNotFoundError, subprocess.SubprocessError):
+            pass
+
+        if platform.machine() == "arm64":
+            return DEFAULT_TARGET
+
+    # Default fallback
+    return DEFAULT_TARGET

tests/python/relax/test_frontend_dynamo.py

@@ -206,10 +206,10 @@ def subgraph_0(
             # block 0
             with R.dataflow():
                 lv: R.Tensor((10,), dtype="float32") = R.sin(inp_0)
-                lv1: R.Tensor((10,), dtype="float32") = R.add(lv, R.const(1, "float32"))
+                lv1: R.Tensor((10,), dtype="float32") = R.add(lv, R.const(1.0, "float32"))
                 lv2: R.Tensor((10,), dtype="float32") = R.divide(inp_0, lv1)
                 lv3: R.Tensor((), dtype="float32") = R.sum(inp_1, axis=None, keepdims=False)
-                lv4: R.Tensor((), dtype="bool") = R.less(lv3, R.const(1, "float32"))
+                lv4: R.Tensor((), dtype="bool") = R.less(lv3, R.const(1.0, "float32"))
                 gv: R.Tuple(R.Tensor((10,), dtype="float32"), R.Tensor((), dtype="bool")) = (
                     lv2,
                     lv4,
@@ -219,14 +219,14 @@ def subgraph_0(
 
         @R.function
         def subgraph_1(
-            inp_01: R.Tensor((10,), dtype="float32"), inp_11: R.Tensor((10,), dtype="float32")
+            inp_0: R.Tensor((10,), dtype="float32"), inp_1: R.Tensor((10,), dtype="float32")
         ) -> R.Tensor((10,), dtype="float32"):
             # block 0
             with R.dataflow():
-                lv5: R.Tensor((10,), dtype="float32") = R.multiply(inp_01, inp_11)
-                gv1: R.Tensor((10,), dtype="float32") = lv5
-                R.output(gv1)
-            return gv1
+                lv: R.Tensor((10,), dtype="float32") = R.multiply(inp_0, inp_1)
+                gv: R.Tensor((10,), dtype="float32") = lv
+                R.output(gv)
+            return gv
 
     mod = dynamo_capture_subgraphs(Input2, torch.randn(10), torch.ones(10))
     tvm.ir.assert_structural_equal(mod, Expected2)