From 2a6cdba6e5f74c2294fecc2d1344537522efbaab Mon Sep 17 00:00:00 2001
From: bobrenjc93 <bobren@meta.com>
Date: Mon, 6 Oct 2025 10:03:51 -0700
Subject: [PATCH] [torchfuzz] various edge case fixes (#164715)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/164715
Approved by: https://github.com/pianpwk
ghstack dependencies: #164432, #164434, #164514, #164646, #164647, #164649, #164687, #164688, #164693, #164694
---
 tools/experimental/torchfuzz/codegen.py       |  6 ++++++
 .../torchfuzz/multi_process_fuzzer.py         |  2 +-
 .../torchfuzz/operators/scalar_pointwise.py   | 19 +++++++++++++++++++
 3 files changed, 26 insertions(+), 1 deletion(-)

diff --git a/tools/experimental/torchfuzz/codegen.py b/tools/experimental/torchfuzz/codegen.py
index 8d6e15d2d542..21d1aa70a2cf 100644
--- a/tools/experimental/torchfuzz/codegen.py
+++ b/tools/experimental/torchfuzz/codegen.py
@@ -180,6 +180,12 @@ class FuzzTemplate:
                         code_lines.append(
                             f"{arg_name} = torch.as_strided(torch.randint({min_val}, {max_val}, ({storage_size},)).to({dtype_str}), {size_str}, {stride_str})"
                         )
+                    elif spec.dtype == torch.bool:
+                        # For boolean tensors, use randint to generate True/False values
+                        # Using randn().to(bool) would yield almost all True due to non-zero floats
+                        code_lines.append(
+                            f"{arg_name} = torch.as_strided(torch.randint(0, 2, ({storage_size},), dtype=torch.int8).bool(), {size_str}, {stride_str})"
+                        )
                     else:
                         code_lines.append(
                             f"{arg_name} = torch.as_strided(torch.randn({storage_size}).to({dtype_str}), {size_str}, {stride_str})"
diff --git a/tools/experimental/torchfuzz/multi_process_fuzzer.py b/tools/experimental/torchfuzz/multi_process_fuzzer.py
index 05bc77966199..1a602dbf4842 100644
--- a/tools/experimental/torchfuzz/multi_process_fuzzer.py
+++ b/tools/experimental/torchfuzz/multi_process_fuzzer.py
@@ -62,7 +62,7 @@ IGNORE_PATTERNS: list[re.Pattern] = [
     re.compile(
         r"TypeError\(\"unsupported operand type\(s\) for \*: 'SymBool' and 'FakeTensor'\"\)"
     ),  # https://github.com/pytorch/pytorch/issues/164684
-    re.compile(r"KeyError: u0"),  # https://github.com/pytorch/pytorch/issues/164685
+    re.compile(r"KeyError: u\d+"),  # https://github.com/pytorch/pytorch/issues/164685
     re.compile(
         r"torch\._inductor\.exc\.InductorError: CppCompileError: C\+\+ compile error"
     ),  # https://github.com/pytorch/pytorch/issues/164686
diff --git a/tools/experimental/torchfuzz/operators/scalar_pointwise.py b/tools/experimental/torchfuzz/operators/scalar_pointwise.py
index 46e72c05bce5..6350c0120631 100644
--- a/tools/experimental/torchfuzz/operators/scalar_pointwise.py
+++ b/tools/experimental/torchfuzz/operators/scalar_pointwise.py
@@ -78,3 +78,22 @@ class ScalarDivOperator(ScalarPointwiseOperator):
 
     def __init__(self):
         super().__init__("scalar_div", "/")
+
+    def codegen(
+        self, output_name: str, input_names: list[str], output_spec: Spec
+    ) -> str:
+        """Generate code for scalar division with zero-denominator guard."""
+        if len(input_names) != 2:
+            raise ValueError(f"{self.__class__.__name__} requires exactly two inputs")
+
+        # Prevent ZeroDivisionError at runtime by clamping the denominator.
+        # Clamp denominator to at least 1 (for ints) or 1e-6 (for floats).
+        if isinstance(output_spec, ScalarSpec) and output_spec.dtype in [
+            torch.int8,
+            torch.int16,
+            torch.int32,
+            torch.int64,
+        ]:
+            return f"{output_name} = {input_names[0]} / max({input_names[1]}, 1)"
+        else:
+            return f"{output_name} = {input_names[0]} / max({input_names[1]}, 1e-6)"