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Merged
merged 1 commit into from
Jul 28, 2025
Merged

Arm backend: Add bitwise scalar ops #12857

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3 changes: 3 additions & 0 deletions backends/arm/_passes/match_arg_ranks_pass.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,9 @@ def __init__(self, exported_program):
exir_ops.edge.aten.le.Tensor,
exir_ops.edge.aten.pow.Tensor_Tensor,
exir_ops.edge.aten.where.self,
exir_ops.edge.aten.bitwise_and.Tensor,
exir_ops.edge.aten.bitwise_xor.Tensor,
exir_ops.edge.aten.bitwise_or.Tensor,
]

def _match_op_rank(self, graph_module, node, arg, max_rank):
Expand Down
6 changes: 6 additions & 0 deletions backends/arm/_passes/replace_scalar_with_tensor_pass.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,9 @@
exir_ops.edge.aten.lt.Scalar: exir_ops.edge.aten.lt.Tensor,
exir_ops.edge.aten.le.Scalar: exir_ops.edge.aten.le.Tensor,
exir_ops.edge.aten.ne.Scalar: exir_ops.edge.aten.ne.Tensor,
exir_ops.edge.aten.bitwise_and.Scalar: exir_ops.edge.aten.bitwise_and.Tensor,
exir_ops.edge.aten.bitwise_or.Scalar: exir_ops.edge.aten.bitwise_or.Tensor,
exir_ops.edge.aten.bitwise_xor.Scalar: exir_ops.edge.aten.bitwise_xor.Tensor,
torch.ops.aten.add.Scalar: torch.ops.aten.add.Tensor,
torch.ops.aten.sub.Scalar: torch.ops.aten.sub.Tensor,
torch.ops.aten.mul.Scalar: torch.ops.aten.mul.Tensor,
Expand All @@ -46,6 +49,9 @@
torch.ops.aten.lt.Scalar: torch.ops.aten.lt.Tensor,
torch.ops.aten.le.Scalar: torch.ops.aten.le.Tensor,
torch.ops.aten.ne.Scalar: torch.ops.aten.ne.Tensor,
torch.ops.aten.bitwise_and.Scalar: torch.ops.aten.bitwise_and.Tensor,
torch.ops.aten.bitwise_or.Scalar: torch.ops.aten.bitwise_or.Tensor,
torch.ops.aten.bitwise_xor.Scalar: torch.ops.aten.bitwise_xor.Tensor,
}


Expand Down
3 changes: 3 additions & 0 deletions backends/arm/operator_support/ethos_u55_support.py
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Original file line number Diff line number Diff line change
Expand Up @@ -125,6 +125,9 @@ class EthosU55NotSupported(OperatorSupportBase):
exir_ops.edge.aten.bitwise_and.Tensor,
exir_ops.edge.aten.bitwise_or.Tensor,
exir_ops.edge.aten.bitwise_xor.Tensor,
exir_ops.edge.aten.bitwise_and.Scalar,
exir_ops.edge.aten.bitwise_or.Scalar,
exir_ops.edge.aten.bitwise_xor.Scalar,
exir_ops.edge.aten.bitwise_not,
exir_ops.edge.aten.logical_and.default,
exir_ops.edge.aten.logical_or.default,
Expand Down
3 changes: 3 additions & 0 deletions backends/arm/operator_support/tosa_supported_operators.py
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Original file line number Diff line number Diff line change
Expand Up @@ -164,6 +164,9 @@ def is_node_supported(
exir_ops.edge.aten.bitwise_and.Tensor,
exir_ops.edge.aten.bitwise_or.Tensor,
exir_ops.edge.aten.bitwise_xor.Tensor,
exir_ops.edge.aten.bitwise_and.Scalar,
exir_ops.edge.aten.bitwise_or.Scalar,
exir_ops.edge.aten.bitwise_xor.Scalar,
exir_ops.edge.aten.expand_copy.default,
exir_ops.edge.aten.cat.default,
exir_ops.edge.aten.ceil.default,
Expand Down
252 changes: 252 additions & 0 deletions backends/arm/test/ops/test_bitwise.py
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Original file line number Diff line number Diff line change
Expand Up @@ -56,6 +56,27 @@ class BitwiseBinary(torch.nn.Module):
}


class BitwiseBinaryScalar(torch.nn.Module):
test_data = {
"zeros": lambda: (torch.zeros(1, 10, 10, 10, dtype=torch.int32), 0),
"ones_int8": lambda: (torch.ones(10, 10, 10, dtype=torch.int8), 1),
"pattern_int8": lambda: (0xAA * torch.ones(1, 2, 2, 2, dtype=torch.int8), 0x77),
"pattern_int16": lambda: (
0xAAAA * torch.ones(1, 2, 2, 2, dtype=torch.int16),
0x7777,
),
"pattern_int32": lambda: (
0xAAAAAAAA * torch.ones(1, 2, 2, 2, dtype=torch.int32),
0x77777777,
),
"rand_rank2": lambda: (torch.randint(-128, 127, (10, 10), dtype=torch.int8), 5),
"rand_rank4": lambda: (
torch.randint(-128, 127, (1, 10, 10, 10), dtype=torch.int8),
-7,
),
}


class And(BitwiseBinary):
aten_op = "torch.ops.aten.bitwise_and.Tensor"
exir_op = "executorch_exir_dialects_edge__ops_aten_bitwise_and_Tensor"
Expand All @@ -80,6 +101,36 @@ def forward(self, tensor1: torch.Tensor, tensor2: torch.Tensor):
return tensor1.bitwise_or(tensor2)


class AndScalar(BitwiseBinaryScalar):
aten_op = "torch.ops.aten.bitwise_and.Scalar"
# Tensor because it gets converted from Scalar -> Tensor in lowering
exir_op = "executorch_exir_dialects_edge__ops_aten_bitwise_and_Tensor"

def forward(self, tensor: torch.Tensor, scalar: int):
return tensor.bitwise_and(scalar)


class XorScalar(BitwiseBinaryScalar):
aten_op = "torch.ops.aten.bitwise_xor.Scalar"
# Tensor because it gets converted from Scalar -> Tensor in lowering
exir_op = "executorch_exir_dialects_edge__ops_aten_bitwise_xor_Tensor"

def forward(self, tensor: torch.Tensor, scalar: int):
return tensor.bitwise_xor(scalar)


class OrScalar(BitwiseBinaryScalar):
aten_op = "torch.ops.aten.bitwise_or.Scalar"
# Tensor because it gets converted from Scalar -> Tensor in lowering
exir_op = "executorch_exir_dialects_edge__ops_aten_bitwise_or_Tensor"

def forward(self, tensor: torch.Tensor, scalar: int):
return tensor.bitwise_or(scalar)


# Bitwise AND


@common.parametrize("test_data", And().test_data)
def test_bitwise_and_tensor_tosa_MI(test_data: input_t2):
pipeline = TosaPipelineMI[input_t2](
Expand All @@ -94,6 +145,20 @@ def test_bitwise_and_tensor_tosa_MI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", AndScalar.test_data)
def test_bitwise_and_scalar_tosa_MI(test_data: input_t2):
pipeline = TosaPipelineMI[input_t2](
AndScalar(),
test_data(),
AndScalar.aten_op,
AndScalar.exir_op,
atol=0,
rtol=0,
qtol=0,
)
pipeline.run()


@common.parametrize("test_data", And().test_data)
def test_bitwise_and_tensor_tosa_BI(test_data: input_t2):
pipeline = TosaPipelineBI[input_t2](
Expand All @@ -110,6 +175,22 @@ def test_bitwise_and_tensor_tosa_BI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", AndScalar.test_data)
def test_bitwise_and_scalar_tosa_BI(test_data: input_t2):
pipeline = TosaPipelineBI[input_t2](
AndScalar(),
test_data(),
AndScalar.aten_op,
AndScalar.exir_op,
atol=0,
rtol=0,
qtol=0,
)
pipeline.pop_stage("quantize")
pipeline.pop_stage("check.quant_nodes")
pipeline.run()


@common.parametrize("test_data", And().test_data)
def test_bitwise_and_tensor_u55_BI(test_data: input_t2):
# Tests that we don't delegate these ops since they are not supported on U55.
Expand All @@ -123,6 +204,43 @@ def test_bitwise_and_tensor_u55_BI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", AndScalar.test_data)
def test_bitwise_and_scalar_u55_BI(test_data: input_t2):
# There will be one full op which will be delegated.
num_delegates = 1
num_exir = 0
pipeline = OpNotSupportedPipeline[input_t2](
AndScalar(),
test_data(),
{
AndScalar.exir_op: 1,
"executorch_exir_dialects_edge__ops_aten_full_default": num_exir,
},
num_delegates,
quantize=True,
u55_subset=True,
)
pipeline.run()


@common.parametrize("test_data", AndScalar.test_data)
@common.XfailIfNoCorstone320
def test_bitwise_and_scalar_u85_BI(test_data: input_t2):
pipeline = EthosU85PipelineBI[input_t2](
AndScalar(),
test_data(),
AndScalar.aten_op,
AndScalar.exir_op,
run_on_fvp=True,
atol=0,
rtol=0,
qtol=0,
)
pipeline.pop_stage("quantize")
pipeline.pop_stage("check.quant_nodes")
pipeline.run()


@common.parametrize("test_data", And().test_data)
@common.XfailIfNoCorstone320
def test_bitwise_and_tensor_u85_BI(test_data: input_t2):
Expand Down Expand Up @@ -155,6 +273,20 @@ def test_bitwise_xor_tensor_tosa_MI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", XorScalar.test_data)
def test_bitwise_xor_scalar_tosa_MI(test_data: input_t2):
pipeline = TosaPipelineMI[input_t2](
XorScalar(),
test_data(),
XorScalar.aten_op,
XorScalar.exir_op,
atol=0,
rtol=0,
qtol=0,
)
pipeline.run()


@common.parametrize("test_data", Xor().test_data)
def test_bitwise_xor_tensor_tosa_BI(test_data: input_t2):
pipeline = TosaPipelineBI[input_t2](
Expand All @@ -171,6 +303,22 @@ def test_bitwise_xor_tensor_tosa_BI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", XorScalar.test_data)
def test_bitwise_xor_scalar_tosa_BI(test_data: input_t2):
pipeline = TosaPipelineBI[input_t2](
XorScalar(),
test_data(),
XorScalar.aten_op,
XorScalar.exir_op,
atol=0,
rtol=0,
qtol=0,
)
pipeline.pop_stage("quantize")
pipeline.pop_stage("check.quant_nodes")
pipeline.run()


@common.parametrize("test_data", Xor().test_data)
def test_bitwise_xor_tensor_u55_BI(test_data: input_t2):
# Tests that we don't delegate these ops since they are not supported on U55.
Expand All @@ -184,6 +332,25 @@ def test_bitwise_xor_tensor_u55_BI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", XorScalar.test_data)
def test_bitwise_xor_scalar_u55_BI(test_data: input_t2):
# There will be one full op which will be delegated.
num_delegates = 1
num_exir = 0
pipeline = OpNotSupportedPipeline[input_t2](
XorScalar(),
test_data(),
{
XorScalar.exir_op: 1,
"executorch_exir_dialects_edge__ops_aten_full_default": num_exir,
},
num_delegates,
quantize=True,
u55_subset=True,
)
pipeline.run()


@common.parametrize("test_data", Xor().test_data)
@common.XfailIfNoCorstone320
def test_bitwise_xor_tensor_u85_BI(test_data: input_t2):
Expand All @@ -202,6 +369,24 @@ def test_bitwise_xor_tensor_u85_BI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", XorScalar.test_data)
@common.XfailIfNoCorstone320
def test_bitwise_xor_scalar_u85_BI(test_data: input_t2):
pipeline = EthosU85PipelineBI[input_t2](
XorScalar(),
test_data(),
XorScalar.aten_op,
XorScalar.exir_op,
run_on_fvp=True,
atol=0,
rtol=0,
qtol=0,
)
pipeline.pop_stage("quantize")
pipeline.pop_stage("check.quant_nodes")
pipeline.run()


@common.parametrize("test_data", Or().test_data)
def test_bitwise_or_tensor_tosa_MI(test_data: input_t2):
pipeline = TosaPipelineMI[input_t2](
Expand All @@ -216,6 +401,20 @@ def test_bitwise_or_tensor_tosa_MI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", OrScalar.test_data)
def test_bitwise_or_scalar_tosa_MI(test_data: input_t2):
pipeline = TosaPipelineMI[input_t2](
OrScalar(),
test_data(),
OrScalar.aten_op,
OrScalar.exir_op,
atol=0,
rtol=0,
qtol=0,
)
pipeline.run()


@common.parametrize("test_data", Or().test_data)
def test_bitwise_or_tensor_tosa_BI(test_data: input_t2):
pipeline = TosaPipelineBI[input_t2](
Expand All @@ -232,6 +431,22 @@ def test_bitwise_or_tensor_tosa_BI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", OrScalar.test_data)
def test_bitwise_or_scalar_tosa_BI(test_data: input_t2):
pipeline = TosaPipelineBI[input_t2](
OrScalar(),
test_data(),
OrScalar.aten_op,
OrScalar.exir_op,
atol=0,
rtol=0,
qtol=0,
)
pipeline.pop_stage("quantize")
pipeline.pop_stage("check.quant_nodes")
pipeline.run()


@common.parametrize("test_data", Or().test_data)
def test_bitwise_or_tensor_u55_BI(test_data: input_t2):
# Tests that we don't delegate these ops since they are not supported on U55.
Expand All @@ -245,6 +460,25 @@ def test_bitwise_or_tensor_u55_BI(test_data: input_t2):
pipeline.run()


@common.parametrize("test_data", OrScalar.test_data)
def test_bitwise_or_scalar_u55_BI(test_data: input_t2):
# There will be one full op which will be delegated.
num_delegates = 1
num_exir = 0
pipeline = OpNotSupportedPipeline[input_t2](
OrScalar(),
test_data(),
{
OrScalar.exir_op: 1,
"executorch_exir_dialects_edge__ops_aten_full_default": num_exir,
},
num_delegates,
quantize=True,
u55_subset=True,
)
pipeline.run()


@common.parametrize("test_data", Or().test_data)
@common.XfailIfNoCorstone320
def test_bitwise_or_tensor_u85_BI(test_data: input_t2):
Expand All @@ -261,3 +495,21 @@ def test_bitwise_or_tensor_u85_BI(test_data: input_t2):
pipeline.pop_stage("quantize")
pipeline.pop_stage("check.quant_nodes")
pipeline.run()


@common.parametrize("test_data", OrScalar.test_data)
@common.XfailIfNoCorstone320
def test_bitwise_or_scalar_u85_BI(test_data: input_t2):
pipeline = EthosU85PipelineBI[input_t2](
OrScalar(),
test_data(),
OrScalar.aten_op,
OrScalar.exir_op,
run_on_fvp=True,
atol=0,
rtol=0,
qtol=0,
)
pipeline.pop_stage("quantize")
pipeline.pop_stage("check.quant_nodes")
pipeline.run()
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