From f776870f47485fcf3793e0cd7440ba78a409ce6c Mon Sep 17 00:00:00 2001
From: Github Executorch <github_executorch@arm.com>
Date: Tue, 23 Dec 2025 09:31:51 -0800
Subject: [PATCH 1/2] Fix circular import in cortex_m passes using relative
 imports
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Changed cortex_m_pass_manager.py to use relative imports (from .activation_fusion_pass)
instead of absolute imports (from executorch.backends.cortex_m.passes) for
intra-package references. This breaks the circular import chain:
__init__.py → cortex_m_pass_manager.py → __init__.py

Resolves: ImportError: cannot import name 'ActivationFusionPass' from
partially initialized module 'executorch.backends.cortex_m.passes'
---
 backends/cortex_m/passes/cortex_m_pass_manager.py | 15 +++++++--------
 backends/cortex_m/quantizer/__init__.py           |  1 -
 2 files changed, 7 insertions(+), 9 deletions(-)

diff --git a/backends/cortex_m/passes/cortex_m_pass_manager.py b/backends/cortex_m/passes/cortex_m_pass_manager.py
index bd3fad1cf94..c47bcc357ea 100644
--- a/backends/cortex_m/passes/cortex_m_pass_manager.py
+++ b/backends/cortex_m/passes/cortex_m_pass_manager.py
@@ -10,14 +10,6 @@
     FoldAndAnnotateQParamsPass,
     ScalarsToAttributePass,
 )
-from executorch.backends.cortex_m.passes import (
-    ActivationFusionPass,
-    ClampHardswishPass,
-    ConvertToCortexMPass,
-    DecomposeHardswishPass,
-    QuantizedOpFusionPass,
-    ReplaceQuantNodesPass,
-)
 from executorch.backends.transforms.replace_scalar_with_tensor import (
     ReplaceScalarWithTensorArgPass,
 )
@@ -26,6 +18,13 @@
 from executorch.exir.program._program import _transform
 from torch.export import ExportedProgram
 
+from .activation_fusion_pass import ActivationFusionPass
+from .clamp_hardswish_pass import ClampHardswishPass
+from .convert_to_cortex_m_pass import ConvertToCortexMPass
+from .decompose_hardswish_pass import DecomposeHardswishPass
+from .quantized_op_fusion_pass import QuantizedOpFusionPass
+from .replace_quant_nodes_pass import ReplaceQuantNodesPass
+
 
 class CortexMPassManager(PassManager):
 
diff --git a/backends/cortex_m/quantizer/__init__.py b/backends/cortex_m/quantizer/__init__.py
index 39a3de431ff..c55f200bbaa 100644
--- a/backends/cortex_m/quantizer/__init__.py
+++ b/backends/cortex_m/quantizer/__init__.py
@@ -16,4 +16,3 @@
     SOFTMAX_OUTPUT_FIXED_QSPEC,
     SOFTMAX_PER_TENSOR_CONFIG,
 )
-from .quantizer import CortexMQuantizer, SharedQspecQuantizer  # noqa

From 8186e269364db35989630321ce78e419dc21c966 Mon Sep 17 00:00:00 2001
From: Github Executorch <github_executorch@arm.com>
Date: Mon, 5 Jan 2026 14:27:25 -0800
Subject: [PATCH 2/2] Fix division by zero in reduce_util.h grain size
 calculation

Add zero check for reduction_size before dividing to calculate grain_size,
preventing crash when fuzzer triggers edge case with empty reduction dimension.
---
 kernels/portable/cpu/util/reduce_util.h | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/kernels/portable/cpu/util/reduce_util.h b/kernels/portable/cpu/util/reduce_util.h
index 51981328c4f..f800fb6f736 100644
--- a/kernels/portable/cpu/util/reduce_util.h
+++ b/kernels/portable/cpu/util/reduce_util.h
@@ -814,10 +814,12 @@ template <typename Func>
     const Func& func) {
 #ifdef ET_USE_THREADPOOL
   const ssize_t reduction_size = get_reduced_dim_product(in, dim);
-  const auto grain_size = std::max(
-      static_cast<ssize_t>(1),
-      static_cast<ssize_t>(executorch::extension::internal::GRAIN_SIZE) /
-          reduction_size);
+  const auto grain_size = reduction_size == 0
+      ? 1
+      : std::max(
+            static_cast<ssize_t>(1),
+            static_cast<ssize_t>(executorch::extension::internal::GRAIN_SIZE) /
+                reduction_size);
 #else // ET_USE_THREADPOOL
   const auto grain_size = 1;
 #endif // ET_USE_THREADPOOL