Arm backend: Add constant ops unittests.

backends/arm/test/ops/test_eye.py

@@ -0,0 +1,113 @@
+# 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 import common
+from executorch.backends.arm.test.tester.test_pipeline import (
+    EthosU55PipelineBI,
+    EthosU85PipelineBI,
+    OpNotSupportedPipeline,
+    TosaPipelineBI,
+    TosaPipelineMI,
+)
+
+input_t = tuple[torch.Tensor]
+test_data_t = tuple[int, torch.dtype]
+
+
+class EyeAdd(torch.nn.Module):
+    aten_op: str = "torch.ops.aten.eye.default"
+
+    def __init__(self, n: int, dtype: torch.dtype):
+        super().__init__()
+        self.args = (n,)
+        self.dtype = dtype
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        return torch.eye(*self.args, dtype=self.dtype) + x
+
+    test_data: dict[str, test_data_t] = {
+        "10x3x3": (lambda: (torch.randn(10, 3, 3),), (3, torch.float32)),
+        "10x1": (lambda: (torch.randn(10, 1),), (10, torch.float32)),
+        "int32_int32": (
+            lambda: (torch.randint(0, 10, [10], dtype=torch.int32),),
+            (10, torch.int32),
+        ),
+    }
+
+    test_data_not_delegated: dict[str, test_data_t] = {
+        "fp32_int64": (lambda: (torch.randn(10),), (10, torch.int64)),
+        "fp32_int32": (lambda: (torch.randn(10),), (10, torch.int32)),
+        "int32_int64": (
+            lambda: (torch.randint(0, 10, [10], dtype=torch.int32),),
+            (10, torch.int64),
+        ),
+    }
+
+
+@common.parametrize("test_data", EyeAdd.test_data)
+def test_eye_tosa_MI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = TosaPipelineMI[input_t](
+        EyeAdd(*init_data),
+        input_data(),
+        EyeAdd.aten_op,
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", EyeAdd.test_data)
+def test_eye_tosa_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = TosaPipelineBI[input_t](
+        EyeAdd(*init_data),
+        input_data(),
+        EyeAdd.aten_op,
+    )
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize("test_data", EyeAdd.test_data)
+def test_eye_u55_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = EthosU55PipelineBI[input_t](
+        EyeAdd(*init_data),
+        input_data(),
+        EyeAdd.aten_op,
+        use_to_edge_transform_and_lower=True,
+    )
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize("test_data", EyeAdd.test_data)
+def test_eye_u85_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = EthosU85PipelineBI[input_t](
+        EyeAdd(*init_data),
+        input_data(),
+        EyeAdd.aten_op,
+        use_to_edge_transform_and_lower=True,
+    ).dump_artifact("to_edge_transform_and_lower")
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize(
+    "test_data",
+    EyeAdd.test_data_not_delegated,
+    xfails={
+        "fp32_int32": "MLETORCG-716: Do not delegate empty networks to vela",
+        "fp32_int64": "MLETORCG-716: Do not delegate empty networks to vela",
+        "int32_int64": "MLETORCG-716: Do not delegate empty networks to vela",
+    },
+)
+def test_eye_tosa_BI_not_delegated(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = OpNotSupportedPipeline[input_t](
+        EyeAdd(*init_data), input_data(), non_delegated_ops={}, quantize=True
+    )
+    pipeline.run()

backends/arm/test/ops/test_ones.py

@@ -0,0 +1,114 @@
+# 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 import common
+from executorch.backends.arm.test.tester.test_pipeline import (
+    EthosU55PipelineBI,
+    EthosU85PipelineBI,
+    OpNotSupportedPipeline,
+    TosaPipelineBI,
+    TosaPipelineMI,
+)
+
+input_t = tuple[torch.Tensor]
+test_data_t = tuple[int, torch.dtype]
+
+
+class OnesAdd(torch.nn.Module):
+    aten_op: str = "torch.ops.aten.ones.default"
+
+    def __init__(self, n: int, dtype: torch.dtype):
+        super().__init__()
+        self.args = (n,)
+        self.dtype = dtype
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        return torch.ones(*self.args, dtype=self.dtype) + x
+
+    test_data: dict[str, test_data_t] = {
+        "10x3x3": (lambda: (torch.randn(10, 3, 3),), (3, torch.float32)),
+        "10x1": (lambda: (torch.randn(10, 1),), (10, torch.float32)),
+        "int32_int32": (
+            lambda: (torch.randint(0, 10, [10], dtype=torch.int32),),
+            (10, torch.int32),
+        ),
+    }
+
+    test_data_not_delegated: dict[str, test_data_t] = {
+        "fp32_int64": (lambda: (torch.randn(10),), (10, torch.int64)),
+        "fp32_int32": (lambda: (torch.randn(10),), (10, torch.int32)),
+        "int32_int64": (
+            lambda: (torch.randint(0, 10, [10], dtype=torch.int32),),
+            (10, torch.int64),
+        ),
+    }
+
+
+@common.parametrize("test_data", OnesAdd.test_data)
+def test_ones_tosa_MI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = TosaPipelineMI[input_t](
+        OnesAdd(*init_data),
+        input_data(),
+        OnesAdd.aten_op,
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", OnesAdd.test_data)
+def test_ones_tosa_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = TosaPipelineBI[input_t](
+        OnesAdd(*init_data),
+        input_data(),
+        OnesAdd.aten_op,
+    )
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize("test_data", OnesAdd.test_data)
+def test_ones_u55_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = EthosU55PipelineBI[input_t](
+        OnesAdd(*init_data),
+        input_data(),
+        OnesAdd.aten_op,
+        use_to_edge_transform_and_lower=True,
+    )
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize("test_data", OnesAdd.test_data)
+def test_ones_u85_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = EthosU85PipelineBI[input_t](
+        OnesAdd(*init_data),
+        input_data(),
+        OnesAdd.aten_op,
+        use_to_edge_transform_and_lower=True,
+    ).dump_artifact("to_edge_transform_and_lower")
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize(
+    "test_data",
+    OnesAdd.test_data_not_delegated,
+    xfails={
+        "fp32_int32": "MLETORCG-716: Do not delegate empty networks to vela",
+        "fp32_int64": "MLETORCG-716: Do not delegate empty networks to vela",
+        "int32_int64": "MLETORCG-716: Do not delegate empty networks to vela",
+    },
+)
+def test_ones_tosa_BI_not_delegated(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = OpNotSupportedPipeline[input_t](
+        OnesAdd(*init_data), input_data(), non_delegated_ops={}, quantize=True
+    )
+    pipeline.run()

backends/arm/test/ops/test_zeros.py

@@ -0,0 +1,114 @@
+# 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 import common
+from executorch.backends.arm.test.tester.test_pipeline import (
+    EthosU55PipelineBI,
+    EthosU85PipelineBI,
+    OpNotSupportedPipeline,
+    TosaPipelineBI,
+    TosaPipelineMI,
+)
+
+input_t = tuple[torch.Tensor]
+test_data_t = tuple[int, torch.dtype]
+
+
+class ZerosAdd(torch.nn.Module):
+    aten_op: str = "torch.ops.aten.zeros.default"
+
+    def __init__(self, n: int, dtype: torch.dtype):
+        super().__init__()
+        self.args = (n,)
+        self.dtype = dtype
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        return torch.zeros(*self.args, dtype=self.dtype) + x
+
+    test_data: dict[str, test_data_t] = {
+        "10x3x3": (lambda: (torch.randn(10, 3, 3),), (3, torch.float32)),
+        "10x1": (lambda: (torch.randn(10, 1),), (10, torch.float32)),
+        "int32_int32": (
+            lambda: (torch.randint(0, 10, [10], dtype=torch.int32),),
+            (10, torch.int32),
+        ),
+    }
+
+    test_data_not_delegated: dict[str, test_data_t] = {
+        "fp32_int64": (lambda: (torch.randn(10),), (10, torch.int64)),
+        "fp32_int32": (lambda: (torch.randn(10),), (10, torch.int32)),
+        "int32_int64": (
+            lambda: (torch.randint(0, 10, [10], dtype=torch.int32),),
+            (10, torch.int64),
+        ),
+    }
+
+
+@common.parametrize("test_data", ZerosAdd.test_data)
+def test_zeros_tosa_MI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = TosaPipelineMI[input_t](
+        ZerosAdd(*init_data),
+        input_data(),
+        ZerosAdd.aten_op,
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", ZerosAdd.test_data)
+def test_zeros_tosa_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = TosaPipelineBI[input_t](
+        ZerosAdd(*init_data),
+        input_data(),
+        ZerosAdd.aten_op,
+    )
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize("test_data", ZerosAdd.test_data)
+def test_zeros_u55_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = EthosU55PipelineBI[input_t](
+        ZerosAdd(*init_data),
+        input_data(),
+        ZerosAdd.aten_op,
+        use_to_edge_transform_and_lower=True,
+    )
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize("test_data", ZerosAdd.test_data)
+def test_zeros_u85_BI(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = EthosU85PipelineBI[input_t](
+        ZerosAdd(*init_data),
+        input_data(),
+        ZerosAdd.aten_op,
+        use_to_edge_transform_and_lower=True,
+    ).dump_artifact("to_edge_transform_and_lower")
+    pipeline.pop_stage("check.quant_nodes")
+    pipeline.run()
+
+
+@common.parametrize(
+    "test_data",
+    ZerosAdd.test_data_not_delegated,
+    xfails={
+        "fp32_int32": "MLETORCG-716: Do not delegate empty networks to vela",
+        "fp32_int64": "MLETORCG-716: Do not delegate empty networks to vela",
+        "int32_int64": "MLETORCG-716: Do not delegate empty networks to vela",
+    },
+)
+def test_zeros_tosa_BI_not_delegated(test_data: test_data_t):
+    input_data, init_data = test_data
+    pipeline = OpNotSupportedPipeline[input_t](
+        ZerosAdd(*init_data), input_data(), non_delegated_ops={}, quantize=True
+    )
+    pipeline.run()