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Arm backend: Add support for aten.clone.default #15980

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2 changes: 2 additions & 0 deletions backends/arm/operator_support/tosa_profile_supported_op_lists.py
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Original file line number Diff line number Diff line change
Expand Up @@ -119,6 +119,7 @@
exir_ops.edge.aten.elu.default,
exir_ops.edge.aten.bitwise_not.default,
exir_ops.edge.aten.copy.default,
exir_ops.edge.aten.clone.default,
}


Expand Down Expand Up @@ -235,6 +236,7 @@
exir_ops.edge.aten.acos.default,
exir_ops.edge.aten.elu.default,
exir_ops.edge.aten.copy.default,
exir_ops.edge.aten.clone.default,
exir_ops.edge.aten.floor_divide.default,
}

Expand Down
1 change: 1 addition & 0 deletions backends/arm/operators/ops_identity.py
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Original file line number Diff line number Diff line change
Expand Up @@ -59,3 +59,4 @@ def define_node(


identity_operator_factory("aten.alias_copy.default")
identity_operator_factory("aten.clone.default")
120 changes: 114 additions & 6 deletions backends/arm/test/ops/test_clone.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,13 +17,45 @@
TosaPipelineINT,
VgfPipeline,
)
from executorch.exir import EdgeCompileConfig

aten_op = "torch.ops.aten.clone.default"
exir_op = "executorch_exir_dialects_edge__ops_dim_order_ops__clone_dim_order_default"
clone_identity_edge = "executorch_exir_dialects_edge__ops_aten_clone_default"
clone_dim_order_edge = (
"executorch_exir_dialects_edge__ops_dim_order_ops__clone_dim_order_default"
)

input_t = Tuple[torch.Tensor]


def _run_with_skip_dim_order(pipeline):
config = EdgeCompileConfig(_skip_dim_order=True)
if pipeline.has_stage("to_edge_transform_and_lower"):
pipeline.change_args("to_edge_transform_and_lower", edge_compile_config=config)
elif pipeline.has_stage("to_edge"):
pipeline.change_args("to_edge", config=config)
else:
raise AssertionError("Pipeline lacks a stage to apply _skip_dim_order.")
pipeline.run()


class CloneIdentity(torch.nn.Module):
"""
Mirrors the alias-copy identity coverage but exercises ``aten.clone`` without
any memory-format change so it lowers directly to a TOSA IDENTITY op.
"""

test_data: dict[str, input_t] = {
"1d_ramp": lambda: (torch.arange(-8, 8, 0.5),),
"2d_ones": lambda: (torch.ones(5, 5),),
"3d_rand": lambda: (torch.rand(3, 4, 4),),
"4d_zeros": lambda: (torch.zeros(1, 4, 4, 4),),
}

def forward(self, x: torch.Tensor):
return torch.clone(x) * 1 # Keep the op through partitioning.


class CloneFirstArg(torch.nn.Module):
def forward(self, x):
return x.clone() + x
Expand Down Expand Up @@ -87,7 +119,7 @@ def test_clone_tosa_INT(input_data):
module(),
input_tensor,
aten_op,
exir_op,
clone_dim_order_edge,
)
pipeline.run()

Expand All @@ -101,7 +133,7 @@ def test_clone_u55_INT(input_data):
module(),
input_tensor,
aten_op,
exir_op,
clone_dim_order_edge,
)

pipeline.run()
Expand All @@ -116,7 +148,7 @@ def test_clone_u85_INT(input_data):
module(),
input_tensor,
aten_op,
exir_op,
clone_dim_order_edge,
)

pipeline.run()
Expand All @@ -127,7 +159,11 @@ def test_clone_u85_INT(input_data):
def test_clone_vgf_FP(test_data):
module, input_tensor = test_data()
pipeline = VgfPipeline[input_t](
module(), input_tensor, aten_op, exir_op, tosa_version="TOSA-1.0+FP"
module(),
input_tensor,
aten_op,
clone_dim_order_edge,
tosa_version="TOSA-1.0+FP",
)
pipeline.run()

Expand All @@ -140,7 +176,79 @@ def test_clone_vgf_INT(test_data):
module(),
input_tensor,
aten_op,
exir_op,
clone_dim_order_edge,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()


@common.parametrize("test_data", CloneIdentity.test_data)
def test_clone_tosa_FP_identity(test_data: input_t):
pipeline = TosaPipelineFP[input_t](
CloneIdentity(),
test_data(),
aten_op,
clone_identity_edge,
)
_run_with_skip_dim_order(pipeline)


@common.parametrize("test_data", CloneIdentity.test_data)
def test_clone_tosa_INT_identity(test_data: input_t):
pipeline = TosaPipelineINT[input_t](
CloneIdentity(),
test_data(),
aten_op,
clone_identity_edge,
)
_run_with_skip_dim_order(pipeline)


@common.parametrize("test_data", CloneIdentity.test_data)
@common.XfailIfNoCorstone300
def test_clone_u55_INT_identity(test_data: input_t):
pipeline = EthosU55PipelineINT[input_t](
CloneIdentity(),
test_data(),
aten_op,
clone_identity_edge,
)
_run_with_skip_dim_order(pipeline)


@common.parametrize("test_data", CloneIdentity.test_data)
@common.XfailIfNoCorstone320
def test_clone_u85_INT_identity(test_data: input_t):
pipeline = EthosU85PipelineINT[input_t](
CloneIdentity(),
test_data(),
aten_op,
clone_identity_edge,
)
_run_with_skip_dim_order(pipeline)


@common.parametrize("test_data", CloneIdentity.test_data)
@common.SkipIfNoModelConverter
def test_clone_vgf_FP_identity(test_data: input_t):
pipeline = VgfPipeline[input_t](
CloneIdentity(),
test_data(),
aten_op,
clone_identity_edge,
tosa_version="TOSA-1.0+FP",
)
_run_with_skip_dim_order(pipeline)


@common.parametrize("test_data", CloneIdentity.test_data)
@common.SkipIfNoModelConverter
def test_clone_vgf_INT_identity(test_data: input_t):
pipeline = VgfPipeline[input_t](
CloneIdentity(),
test_data(),
aten_op,
clone_identity_edge,
tosa_version="TOSA-1.0+INT",
)
_run_with_skip_dim_order(pipeline)