Cortex_m backend: Add cortex_m tester + test_add

backends/arm/test/conftest.py

@@ -118,7 +118,7 @@ def is_option_enabled(option: str, fail_if_not_enabled: bool = False) -> bool:
       a RuntimeError instead of returning False.
     """
 
-    if option in pytest._test_options and pytest._test_options[option]:  # type: ignore[attr-defined]
+    if hasattr(pytest, "_test_options") and option in pytest._test_options and pytest._test_options[option]:  # type: ignore[attr-defined]
         return True
     else:
         if fail_if_not_enabled:

backends/cortex_m/test/cortex_m_tester.py

@@ -0,0 +1,102 @@
+# 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 dataclasses import dataclass
+from typing import Any
+
+import torch
+
+from executorch.backends.arm.quantizer.arm_quantizer import (
+    get_symmetric_quantization_config,
+    TOSAQuantizer,
+)
+from executorch.backends.arm.test.common import get_u55_compile_spec
+from executorch.backends.arm.test.tester.arm_tester import Serialize
+from executorch.backends.cortex_m.passes.quantized_op_fusion_pass import (
+    QuantizedOpFusionPass,
+)
+
+from executorch.backends.cortex_m.passes.replace_quant_nodes_pass import (
+    ReplaceQuantNodesPass,
+)
+from executorch.backends.test.harness import Tester as TesterBase
+from executorch.backends.test.harness.stages import (
+    Export,
+    Quantize,
+    RunPasses,
+    StageType,
+    ToEdgeTransformAndLower,
+    ToExecutorch,
+)
+from executorch.backends.xnnpack._passes import XNNPACKPassManager
+
+
+class CortexMQuantize(Quantize):
+    def __init__(self):
+        compile_spec = get_u55_compile_spec()
+        quantizer = TOSAQuantizer(compile_spec)
+        config = get_symmetric_quantization_config()
+
+        super().__init__(quantizer, config)
+
+
+class CortexMRunPasses(RunPasses):
+    def __init__(self):
+        super().__init__(
+            XNNPACKPassManager, pass_list=[QuantizedOpFusionPass, ReplaceQuantNodesPass]
+        )
+
+
+class CortexMSerialize(Serialize):
+    def __init__(self):
+        compile_spec = get_u55_compile_spec()
+        super().__init__(compile_spec, 1024)
+
+
+cortex_m_stage_classes = {
+    StageType.EXPORT: Export,
+    StageType.QUANTIZE: CortexMQuantize,
+    StageType.RUN_PASSES: CortexMRunPasses,
+    StageType.SERIALIZE: Serialize,
+    StageType.TO_EDGE_TRANSFORM_AND_LOWER: ToEdgeTransformAndLower,
+    StageType.TO_EXECUTORCH: ToExecutorch,
+    StageType.SERIALIZE: CortexMSerialize,
+}
+
+
+class CortexMTester(TesterBase):
+    def __init__(self, module, example_inputs):
+        super().__init__(module, example_inputs, cortex_m_stage_classes)
+
+    def test_dialect(self, ops_before_transforms, ops_after_transforms, qtol=0):
+        """
+        Test the python dialect op implementation.
+        """
+        self.quantize()
+        self.export()
+        self.to_edge_transform_and_lower()
+        self.check_count(ops_before_transforms)
+        self.run_passes()
+        self.check_count(ops_after_transforms)
+        self.run_method_and_compare_outputs(inputs=self.example_inputs, qtol=qtol)
+
+    def test_implementation(self, qtol=0):
+        """
+        Test the optimized op implementation in simulation
+        """
+        self.quantize()
+        self.export()
+        self.to_edge_transform_and_lower()
+        self.run_passes()
+        self.to_executorch()
+        self.serialize()
+        self.run_method_and_compare_outputs(inputs=self.example_inputs, qtol=qtol)
+
+
+@dataclass
+class McuTestCase:
+    model: torch.nn.Module
+    example_inputs: tuple[Any]

backends/cortex_m/test/ops/__init__.py

@@ -0,0 +1,4 @@
+# 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.

backends/cortex_m/test/ops/test_add.py

@@ -0,0 +1,175 @@
+# 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.test.common import parametrize
+from executorch.backends.cortex_m.test.cortex_m_tester import CortexMTester, McuTestCase
+from executorch.backends.test.suite.operators.test_add import Model, ModelAlpha
+
+
+class SelfAdd(torch.nn.Module):
+    ops_before_transforms = {
+        "executorch_exir_dialects_edge__ops_aten_add_Tensor": 1,
+        "executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 2,
+        "executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 2,
+    }
+
+    ops_after_transforms = {
+        "executorch_exir_dialects_edge__ops_cortex_m_quantized_add_default": 1,
+        "executorch_exir_dialects_edge__ops_cortex_m_quantize_per_tensor_default": 1,
+        "executorch_exir_dialects_edge__ops_cortex_m_dequantize_per_tensor_default": 1,
+    }
+
+    def forward(self, x):
+        return x + x
+
+
+class ScalarAdd(Model):
+    ops_before_transforms = {
+        "executorch_exir_dialects_edge__ops_aten_add_Tensor": 1,
+        "executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 2,
+        "executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 3,
+    }
+
+    ops_after_transforms = {
+        "executorch_exir_dialects_edge__ops_cortex_m_quantized_add_default": 1,
+        "executorch_exir_dialects_edge__ops_cortex_m_quantize_per_tensor_default": 1,
+        "executorch_exir_dialects_edge__ops_cortex_m_dequantize_per_tensor_default": 1,
+    }
+
+
+class TensorAdd(Model):
+    ops_before_transforms = {
+        "executorch_exir_dialects_edge__ops_aten_add_Tensor": 1,
+        "executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 3,
+        "executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 3,
+    }
+
+    ops_after_transforms = {
+        "executorch_exir_dialects_edge__ops_cortex_m_quantized_add_default": 1,
+        "executorch_exir_dialects_edge__ops_cortex_m_quantize_per_tensor_default": 2,
+        "executorch_exir_dialects_edge__ops_cortex_m_dequantize_per_tensor_default": 1,
+    }
+
+
+class AlphaAdd(ModelAlpha):
+    ops_before_transforms = {
+        "executorch_exir_dialects_edge__ops_aten_add_Tensor": 1,
+        "executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 3,
+        "executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 3,
+    }
+
+    ops_after_transforms = {
+        "executorch_exir_dialects_edge__ops_cortex_m_quantized_add_default": 1,
+        "executorch_exir_dialects_edge__ops_cortex_m_quantize_per_tensor_default": 2,
+        "executorch_exir_dialects_edge__ops_cortex_m_dequantize_per_tensor_default": 1,
+    }
+
+
+test_cases = {
+    "self_scalar": McuTestCase(
+        SelfAdd(),
+        (10.0,),
+    ),
+    "self_rank_1": McuTestCase(
+        SelfAdd(),
+        (torch.linspace(-5, 5, 10),),
+    ),
+    "self_rank_2_pos": McuTestCase(
+        SelfAdd(),
+        (torch.linspace(0, 1000, 10).reshape((10, 1)),),
+    ),
+    "self_rank_3_neg": McuTestCase(
+        SelfAdd(),
+        (torch.linspace(-100, 0, 8).reshape((2, 2, 2)),),
+    ),
+    "self_rank_4_small": McuTestCase(
+        SelfAdd(),
+        (torch.linspace(-0.1, 0.1, 16).reshape(2, 2, 2, 2),),
+    ),
+    "self_rank_5": McuTestCase(
+        SelfAdd(),
+        (torch.linspace(-5, 5, 32).reshape(2, 2, 2, 2, 2),),
+    ),
+    "scalar_scalar": McuTestCase(
+        ScalarAdd(),
+        (-0.5, 1.0),
+    ),
+    "tensor_scalar": McuTestCase(
+        ScalarAdd(),
+        (torch.ones(2, 2), 1.0),
+    ),
+    "scalar_tensor": McuTestCase(
+        ScalarAdd(),
+        (1000.0, torch.ones(2, 2)),
+    ),
+    "broadcast_1": McuTestCase(
+        TensorAdd(),
+        (torch.ones(1), torch.ones(2, 2, 2, 2)),
+    ),
+    "broadcast_2": McuTestCase(
+        TensorAdd(),
+        (torch.ones((2, 1, 1, 1)), torch.ones(1)),
+    ),
+    "broadcast_3": McuTestCase(
+        TensorAdd(),
+        (
+            torch.linspace(-2, 2, 4).reshape(2, 1, 2, 1),
+            torch.linspace(-5, 5, 4).reshape(1, 2, 1, 2),
+        ),
+    ),
+    "alpha": McuTestCase(
+        AlphaAdd(0.5),
+        (
+            torch.linspace(-10, 10, 20).reshape(4, 5),
+            torch.linspace(-20, 20, 20).reshape(4, 5),
+        ),
+    ),
+}
+
+
+dialect_xfails = {
+    "self_scalar": ("'float' object has no attribute 'fake_mode'", AttributeError),
+    "self_rank_1": ("Output 0 does not match reference output", AssertionError),
+    "self_rank_2_pos": ("Output 0 does not match reference output", AssertionError),
+    "self_rank_3_neg": ("Output 0 does not match reference output", AssertionError),
+    "self_rank_4_small": ("Output 0 does not match reference output", AssertionError),
+    "self_rank_5": ("Output 0 does not match reference output", AssertionError),
+    "scalar_scalar": ("'float' object has no attribute 'fake_mode'", AttributeError),
+    "broadcast_3": ("Output 0 does not match reference output", AssertionError),
+    "alpha": ("Expecting kwargs for aten op IR to be empty", AssertionError),
+}
+
+
+@parametrize("test_case", test_cases, xfails=dialect_xfails)
+def test_dialect_add(test_case):
+    tester = CortexMTester(test_case.model, test_case.example_inputs)
+    tester.test_dialect(
+        test_case.model.ops_before_transforms, test_case.model.ops_after_transforms
+    )
+
+
+implementation_xfails = {
+    "self_scalar": ("'float' object has no attribute 'fake_mode'", AttributeError),
+    "self_rank_1": ("Output 0 does not match reference output", AssertionError),
+    "self_rank_2_pos": ("Output 0 does not match reference output", AssertionError),
+    "self_rank_3_neg": ("Output 0 does not match reference output", AssertionError),
+    "self_rank_4_small": ("Output 0 does not match reference output", AssertionError),
+    "self_rank_5": ("Output 0 does not match reference output", AssertionError),
+    "scalar_scalar": ("'float' object has no attribute 'fake_mode'", AttributeError),
+    "tensor_scalar": ("Output 0 does not match reference output", AssertionError),
+    "scalar_tensor": ("Output 0 does not match reference output", AssertionError),
+    "broadcast_1": ("Output 0 does not match reference output", AssertionError),
+    "broadcast_2": ("Output 0 does not match reference output", AssertionError),
+    "broadcast_3": ("Output 0 does not match reference output", AssertionError),
+    "alpha": ("Expecting kwargs for aten op IR to be empty", AssertionError),
+}
+
+
+@parametrize("test_case", test_cases, xfails=implementation_xfails)
+def test_implementation_add(test_case):
+    tester = CortexMTester(test_case.model, test_case.example_inputs)
+    tester.test_implementation()