Arm backend: Add FuseEqualPlaceholdersPass

backends/arm/_passes/__init__.py

@@ -34,6 +34,7 @@
 )
 from .fuse_batchnorm2d_pass import FuseBatchnorm2DPass  # noqa
 from .fuse_constant_ops_pass import ComputeConstantOpsAOT, FuseConstantArgsPass  # noqa
+from .fuse_equal_placeholders_pass import FuseEqualPlaceholdersPass  # noqa
 from .fuse_quantized_activation_pass import FuseQuantizedActivationPass  # noqa
 from .insert_rescales_pass import InsertRescalePass  # noqa
 from .insert_table_ops import InsertTableOpsPass  # noqa

backends/arm/_passes/arm_pass_manager.py

@@ -35,6 +35,7 @@
     FoldAndAnnotateQParamsPass,
     FuseBatchnorm2DPass,
     FuseConstantArgsPass,
+    FuseEqualPlaceholdersPass,
     FuseQuantizedActivationPass,
     InsertRescalePass,
     InsertTableOpsPass,
@@ -108,6 +109,7 @@ def _tosa_080_BI_pipeline(self, exported_program: ExportedProgram) -> GraphModul
         self.add_pass(FuseConstantArgsPass(exported_program))
 
         self.add_pass(InsertTableOpsPass(exported_program))
+        self.add_pass(FuseEqualPlaceholdersPass(exported_program))
         self.add_pass(AnnotateChannelsLastDimOrder())
         self.add_pass(InsertRescalePass())
 
@@ -155,6 +157,7 @@ def _tosa_080_MI_pipeline(self, exported_program: ExportedProgram) -> GraphModul
         self.add_pass(FuseViewCopyTransform())
         self.add_pass(FuseConstantArgsPass(exported_program))
         self.add_pass(InsertTableOpsPass(exported_program))
+        self.add_pass(FuseEqualPlaceholdersPass(exported_program))
         self.add_pass(AnnotateChannelsLastDimOrder())
         self.add_pass(InsertRescalePass())
 

backends/arm/_passes/fuse_equal_placeholders_pass.py

@@ -0,0 +1,83 @@
+# 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.
+
+import torch
+from executorch.backends.arm._passes.arm_pass_utils import (
+    get_constant_placeholder_kind,
+    get_param_tensor,
+    is_param_node,
+)
+from executorch.backends.transforms.utils import (
+    create_constant_placeholder,
+    delete_constant_placeholder,
+)
+from executorch.exir import ExportedProgram
+from executorch.exir.pass_base import ExportPass, PassResult
+
+
+class FuseEqualPlaceholdersPass(ExportPass):
+    """
+    This pass optimizes memory usage by finding constant placeholders
+    pointing to identical tensors and fusing them to one single placeholder
+    with multiple users.
+    """
+
+    def __init__(self, exported_program: ExportedProgram):
+        self.exported_program = exported_program
+        super().__init__()
+
+    def call(self, graph_module: torch.fx.GraphModule) -> PassResult:
+        modified = False
+        const_placeholder_nodes = []
+        for node in graph_module.graph.nodes:
+            if is_param_node(self.exported_program, node):
+                const_placeholder_nodes.append(node)
+
+        while const_placeholder_nodes:
+
+            # Find equal tensors
+            node1 = const_placeholder_nodes.pop()
+            eq_nodes = [node1]
+            tensor1 = get_param_tensor(self.exported_program, node1)
+            if tensor1 is None:
+                continue
+
+            for node2 in const_placeholder_nodes:
+                tensor2 = get_param_tensor(self.exported_program, node2)
+                if tensor2 is None:
+                    continue
+
+                if torch.equal(tensor1, tensor2):
+                    eq_nodes.append(node2)
+
+            if len(eq_nodes) > 1:
+                common_name = node1.name + "_common"
+                common_kind = get_constant_placeholder_kind(
+                    self.exported_program, node1
+                )
+                common_persisten_buffer = True
+
+                with graph_module.graph.inserting_before(node1):
+                    common_node = create_constant_placeholder(
+                        self.exported_program,
+                        graph_module.graph,
+                        common_name,
+                        common_kind,
+                        tensor1,
+                        common_persisten_buffer,
+                    )
+
+                for eq_node in eq_nodes:
+                    eq_node.replace_all_uses_with(common_node)
+                    delete_constant_placeholder(self.exported_program, eq_node)
+                    if eq_node != node1:
+                        const_placeholder_nodes.remove(eq_node)
+
+                modified = True
+
+        if modified:
+            graph_module.recompile()
+            graph_module = super().call(graph_module).graph_module
+        return PassResult(graph_module=graph_module, modified=modified)

backends/arm/test/passes/test_fuse_equal_placeholders_ops_pass.py

@@ -0,0 +1,96 @@
+# 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 copy import deepcopy
+from typing import Tuple
+
+import torch
+from executorch.backends.arm._passes.fuse_equal_placeholders_pass import (
+    FuseEqualPlaceholdersPass,
+)
+from executorch.backends.arm.test.tester.test_pipeline import PassPipeline
+
+input_t = Tuple[torch.Tensor]  # Input x
+
+
+class FuseWeightsConstants(torch.nn.Module):
+    ops_before_pass = {}
+    ops_after_pass = {}
+    ops_not_after_pass = []
+
+    def __init__(
+        self,
+    ):
+        super().__init__()
+        self.weights1 = torch.rand(1, 2, 1)
+        self.weights2 = deepcopy(self.weights1)
+        self.bias1 = torch.rand(1)
+        self.bias2 = deepcopy(self.bias1)
+        self.bias3 = deepcopy(self.bias1)
+
+    def forward(self, x):
+        return (
+            torch.conv1d(x, self.weights1, self.bias1)
+            + torch.conv1d(x, self.weights2, self.bias2)
+            + self.bias3
+        )
+
+
+class FuseWeightsStateDict(torch.nn.Module):
+    ops_before_pass = {}
+    ops_after_pass = {}
+    ops_not_after_pass = []
+
+    def __init__(
+        self,
+    ):
+        super().__init__()
+        self.fc1 = torch.nn.Linear(in_features=8, out_features=2, bias=True)
+        self.fc2 = deepcopy(self.fc1)
+
+    def forward(self, x):
+        return self.fc1(x) + self.fc2(x)
+
+
+def test_fuse_equal_placeholders_constants_tosa_MI():
+    module = FuseWeightsConstants()
+    data = (torch.rand(1, 2, 8),)
+    pipeline = PassPipeline[input_t](
+        module,
+        data,
+        tosa_version="TOSA-0.80+MI",
+        ops_before_pass=module.ops_before_pass,
+        ops_after_pass=module.ops_after_pass,
+        passes_with_exported_program=[FuseEqualPlaceholdersPass],
+    )
+    pipeline.run()
+
+    # Check that weights and bias has been merged.
+    exp_program = pipeline.tester.get_artifact().exported_program()
+    constant_keys = list(exp_program.constants.keys())
+    assert len(constant_keys) == 2, "FuseEqualPlaceholders constants failed"
+    assert "_common" in constant_keys[0], "FuseEqualPlaceholders constants failed"
+    assert "_common" in constant_keys[1], "FuseEqualPlaceholders constants failed"
+
+
+def test_fuse_equal_placeholders_state_dict_tosa_MI():
+    module = FuseWeightsStateDict()
+    data = (torch.rand(1, 2, 8),)
+    pipeline = PassPipeline[input_t](
+        module,
+        data,
+        tosa_version="TOSA-0.80+MI",
+        ops_before_pass=module.ops_before_pass,
+        ops_after_pass=module.ops_after_pass,
+        passes_with_exported_program=[FuseEqualPlaceholdersPass],
+    )
+    pipeline.run()
+
+    # Check that weights and bias has been merged.
+    exp_program = pipeline.tester.get_artifact().exported_program()
+    state_dict_keys = list(exp_program.state_dict.keys())
+    assert len(state_dict_keys) == 2, "FuseEqualPlaceholders state_dict failed"
+    assert "_common" in state_dict_keys[0], "FuseEqualPlaceholders state_dict failed"
+    assert "_common" in state_dict_keys[1], "FuseEqualPlaceholders state_dict failed"

examples/arm/setup.sh

@@ -61,7 +61,7 @@ tosa_reference_model_rev="70ed0b40fa831387e36abdb4f7fb9670a3464f5a"
 
 # vela
 vela_repo_url="https://gitlab.arm.com/artificial-intelligence/ethos-u/ethos-u-vela"
-vela_rev="425541302c7e4b6fbeca7c0061286b131ee507c3"
+vela_rev="859cc066178a87ff28230c1ce9bd370f1e98aa5a"
 
 ########
 ### Optional user args