Update base for Update on "[ET-VK] Implementation of to_dim_order_copy"

Title says it all!

Previously, to_dim_order_copy was handled by removing the op. However, this is not possible if the op is modifying the dtype of the original tensor, so these instances of the op would be skipped by the partitioner.

This diff adds an implementation dtype conversion, which allows to_dim_order_copy to be lowered.

Differential Revision: [D86340341](https://our.internmc.facebook.com/intern/diff/D86340341/)

[ghstack-poisoned]

Author: ssjia

.ci/docker/ci_commit_pins/pytorch.txt

@@ -1 +1 @@
-e6f766c7d750d40603eee3f66c5915bac606b3ea
+556fc09a9f67f24ca5591ec049c5d0c347c5f62a

.ci/scripts/test_qnn_static_llm.sh

@@ -81,7 +81,7 @@ elif [[ "${TASK_NAME}" == "stories_260k_bc" ]]; then
     fi
 
 elif [[ "${TASK_NAME}" == "smollm2_135m" ]]; then
-    $PYTHON_EXECUTABLE backends/qualcomm/tests/test_qnn_delegate.py -k TestExampleLLMScript.test_static_smollm2 --model SM8650 --build_folder build-x86/ --executorch_root . --artifact_dir ./static_smollm2 --enable_x86_64
+    $PYTHON_EXECUTABLE backends/qualcomm/tests/test_qnn_delegate.py -k TestExampleLLMScript.test_static_llm_model --model_name smollm2_135m --model SM8650 --build_folder build-x86/ --executorch_root . --artifact_dir ./static_smollm2 --enable_x86_64
     exit_code1=$?
     if [ $exit_code1 -ne 0 ]; then
         exit 1

.github/workflows/trunk.yml

@@ -347,7 +347,7 @@ jobs:
         elif [[ ${{ matrix.os}} == "zephyr-preset" ]]; then
           setup_script_args="--target-toolchain zephyr"
           toolchain_prefix=arm-zephyr-eabi-
-          threshold="135240" # 132 KiB
+          threshold="135656" # 132 KiB
           toolchain_cmake=examples/zephyr/x86_64-linux-arm-zephyr-eabi-gcc.cmake
         else
           echo "Fail unsupport OS selection ${{ matrix.os }}"

backends/arm/_passes/__init__.py

@@ -21,6 +21,9 @@
 from .convert_int64_output_ops_to_int32 import ConvertInt64OutputOpsToInt32Pass  # noqa
 from .convert_int_pow_to_mul import ConvertIntPowToMuls  # noqa
 from .convert_minmax_pass import ConvertMinMaxPass  # noqa
+from .convert_permute_singleton_to_view_pass import (  # noqa
+    ConvertPermuteSingletonToViewPass,
+)
 from .convert_split_to_slice import ConvertSplitToSlicePass  # noqa
 from .convert_squeezes_to_view import ConvertSqueezesToViewPass  # noqa
 from .convert_to_clamp import ConvertToClampPass  # noqa

backends/arm/_passes/arm_pass_manager.py

@@ -27,6 +27,7 @@
     ConvertIntPowToMuls,
     ConvertMinMaxPass,
     ConvertMmToBmmPass,
+    ConvertPermuteSingletonToViewPass,
     ConvertSplitToSlicePass,
     ConvertSqueezesToViewPass,
     ConvertToClampPass,
@@ -234,6 +235,7 @@ def _tosa_pipeline(
         self.add_pass(CastToInt32Pass())
         self.add_pass(BroadcastArgsPass())
 
+        self.add_pass(ConvertPermuteSingletonToViewPass())
         self.add_pass(FuseViewCopyTransform())
         self.add_pass(FuseConstantArgsPass(exported_program))
         self.add_pass(DecomposeConv2dWithInt16ActivationPass())

backends/arm/_passes/convert_expand_copy_to_repeat.py

@@ -20,6 +20,7 @@
 
 
 def calculate_multiples(args):
+    """Returns expand args converted to repeat args, and whether the expand changes the rank"""
     input_node_or_tensor = args[0]
 
     if isinstance(input_node_or_tensor, torch.fx.node.Node):
@@ -45,7 +46,7 @@ def calculate_multiples(args):
         multiples[i] if multiples[i] != -1 and extended_shape[i] == 1 else 1
         for i in range(expanded_rank)
     ]
-    return multiples
+    return multiples, expanded_rank != len(input_shape)
 
 
 class ConvertExpandCopyToRepeatPass(ArmPass):
@@ -62,9 +63,9 @@ def call_operator(self, op, args, kwargs, meta):
         if op != self.expand_copy:
             return super().call_operator(op, args, kwargs, meta)
 
-        multiples = calculate_multiples(args)
+        multiples, changes_rank = calculate_multiples(args)
 
-        if all((x == 1 for x in multiples)):
+        if all((x == 1 for x in multiples)) and not changes_rank:
             # All dimensions/repetitions occur only once. Remove node
             # altogether since it's in practice just a copy.
             logger.warning("Found redundant expand node (no-op). Removing it.")

backends/arm/_passes/convert_permute_singleton_to_view_pass.py

@@ -0,0 +1,62 @@
+# Copyright 2025 Arm Limited and/or its affiliates.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+
+from typing import Sequence, Set, Tuple, Type
+
+from executorch.exir.dialects._ops import ops as exir_ops
+from executorch.exir.pass_base import ExportPass
+
+from torch._ops import OpOverload
+
+
+_PERMUTE_TARGETS: Tuple[OpOverload, ...] = (
+    exir_ops.edge.aten.permute.default,
+    exir_ops.edge.aten.permute_copy.default,
+)
+
+
+class ConvertPermuteSingletonToViewPass(ExportPass):
+    """Replace permutations that only move singleton axes with a reshape.
+
+    Examples:
+    x = rand(1,1,1,4)
+    y = permute(x, (0,3,1,2))
+
+    becomes:
+    x = rand(1,1,1,4)
+    y = view_copy(x, (1,4,1,1))
+    """
+
+    _passes_required_after: Set[Type[ExportPass]] = set()
+
+    def call_operator(self, op, args, kwargs, meta):
+        if op not in _PERMUTE_TARGETS:
+            return super().call_operator(op, args, kwargs, meta)
+
+        input_tensor = args[0].data
+        permutation = args[1]
+        if not is_singleton_permutation(input_tensor.shape, permutation):
+            return super().call_operator(op, args, kwargs, meta)
+
+        output_shape = meta["val"].shape
+        view_args = (args[0], output_shape)
+        return super().call_operator(
+            exir_ops.edge.aten.view_copy.default, view_args, kwargs, meta
+        )
+
+
+def is_singleton_permutation(shape: Sequence[int], permutation: Sequence[int]) -> bool:
+    """
+    Treat as a view only when non-singleton axes keep their order; singleton
+    axes may move freely since they carry no data volume.
+    """
+    rank = len(shape)
+    normalized_perm = [d % rank for d in permutation]
+
+    non_singleton_axes = [i for i, size in enumerate(shape) if size != 1]
+    permuted_non_singleton_axes = [axis for axis in normalized_perm if shape[axis] != 1]
+
+    return permuted_non_singleton_axes == non_singleton_axes

backends/arm/_passes/decompose_embedding_pass.py

@@ -17,7 +17,6 @@
 from .arm_pass_utils import create_node, get_first_fake_tensor
 
 logger = logging.getLogger(__name__)
-logger.setLevel(logging.WARNING)
 
 
 class DecomposeEmbeddingPass(ArmPass):

backends/arm/_passes/insert_int32_casts_after_int64_placeholders.py

@@ -36,6 +36,8 @@ class InsertInt32CastsAfterInt64PlaceholdersPass(ArmPass):
     # Key: op overload; Value: zero-based indices of positional args that must be i64.
     I64_INPUT_ARG_POSITIONS = {
         torch.ops.aten.one_hot.default: (0,),
+        torch.ops.aten.index_copy_.default: (2,),
+        torch.ops.aten.index_copy.default: (2,),
     }
 
     def _insert_callsite_i32_to_i64_casts(self, graph_module: torch.fx.GraphModule):

backends/arm/ethosu/backend.py

@@ -63,7 +63,7 @@ def _compile_tosa_flatbuffer(
         binary = vela_compile(
             tosa_flatbuffer,
             compile_flags,
-            verbose=logger.getEffectiveLevel() == logging.INFO,
+            verbose=logger.getEffectiveLevel() <= logging.INFO,
             intermediate_path=compile_spec.get_intermediate_path(),
         )
         return binary