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Merged
merged 2 commits into from
Nov 4, 2025
Merged

Arm backend: Remove FP specific NodeVisitors #15519

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61a9e17
Arm backend: Remove FP specific NodeVisitors
oscarandersson8218 Sep 25, 2025
4d60df2
Merge branch 'main' into remove_fp_specific_node_visitors
oscarandersson8218 Nov 4, 2025
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53 changes: 10 additions & 43 deletions backends/arm/operators/op_avg_pool2d.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,7 @@ class AvgPool2dVisitor(NodeVisitor):

tosa_specs = [
TosaSpecification.create_from_string("TOSA-1.0+INT"),
TosaSpecification.create_from_string("TOSA-1.0+FP"),
]

def __init__(self, *args):
Expand Down Expand Up @@ -105,43 +106,6 @@ def _build_generic_avgpool2d(
attr,
)

def define_node(
self,
node: torch.fx.Node,
tosa_graph: Any,
inputs: List[TosaArg],
output: TosaArg,
) -> None:
validate_num_inputs(self.target, inputs, [3, 4, 5, 6, 7])
validate_same_dtype(self.target, [inputs[0], output], ts)
validate_valid_dtype(
self.target, [inputs[0], output], ts.DType.INT8, output.tosa_spec
)

accumulator_type = ts.DType.INT32

input_qargs = get_input_qparams(node)
input_zp = input_qargs[0].get_zp_per_tensor()

output_qargs = get_output_qparams(node)
output_zp = output_qargs[0].get_zp_per_tensor()

self._build_generic_avgpool2d(
node, tosa_graph, inputs, output, input_zp, output_zp, accumulator_type
)


@register_node_visitor
class AvgPool2dVisitor_FP(AvgPool2dVisitor):
target = "aten.avg_pool2d.default"

tosa_specs = [
TosaSpecification.create_from_string("TOSA-1.0+FP"),
]

def __init__(self, *args):
super().__init__(*args)

def define_node(
self,
node: torch.fx.Node,
Expand All @@ -159,14 +123,17 @@ def define_node(
)

if inputs[0].dtype == ts.DType.INT8:
super().define_node(node, tosa_graph, inputs, output)
accumulator_type = ts.DType.INT32
input_qargs = get_input_qparams(node)
input_zp = input_qargs[0].get_zp_per_tensor()

if inputs[0].dtype == ts.DType.FP32:
output_qargs = get_output_qparams(node)
output_zp = output_qargs[0].get_zp_per_tensor()
else:
accumulator_type = ts.DType.FP32
# Initilize zero point to zero.
input_zp = 0
output_zp = 0

self._build_generic_avgpool2d(
node, tosa_graph, inputs, output, input_zp, output_zp, accumulator_type
)
self._build_generic_avgpool2d(
node, tosa_graph, inputs, output, input_zp, output_zp, accumulator_type
)
111 changes: 29 additions & 82 deletions backends/arm/operators/op_clamp.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
# Copyright 2025 Arm Limited and/or its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree
Expand Down Expand Up @@ -27,18 +26,19 @@


@register_node_visitor
class ClampVisitor_INT(NodeVisitor):
class ClampVisitor(NodeVisitor):
target = "aten.clamp.default"

tosa_specs = [
TosaSpecification.create_from_string("TOSA-1.0+INT"),
TosaSpecification.create_from_string("TOSA-1.0+FP"),
]

def __init__(self, *args):
super().__init__(*args)

def _get_min_max_arguments(
self, node: Node, dtype_min: int | float, dtype_max: int | float
self, node: Node, dtype: torch.dtype
) -> Tuple[int | float, int | float]:

def cast_type(value: Any) -> int | float:
Expand All @@ -48,6 +48,13 @@ def cast_type(value: Any) -> int | float:
# Attempt to cast to float
return float(value)

if dtype.is_floating_point:
dtype_min = torch.finfo(dtype).min
dtype_max = torch.finfo(dtype).max
else:
dtype_min = torch.iinfo(dtype).min
dtype_max = torch.iinfo(dtype).max

min_arg = dtype_min
max_arg = dtype_max

Expand All @@ -60,53 +67,15 @@ def cast_type(value: Any) -> int | float:

return min_arg, max_arg

def define_node(
self,
node: Node,
tosa_graph: Any,
inputs: List[TosaArg],
output: TosaArg,
) -> None:
validate_num_inputs(self.target, inputs, [2, 3])
validate_same_dtype(self.target, [inputs[0], output], ts)
validate_valid_dtype(
self.target, [inputs[0], output], [ts.DType.INT8], output.tosa_spec
)

# NOTE: Quantization of the min/max arguments is handled by QuantizeOperatorArguments
min_int8, max_int8 = self._get_min_max_arguments(
node,
torch.iinfo(torch.int8).min,
torch.iinfo(torch.int8).max,
)

attr = ts.TosaSerializerAttribute()
attr.ClampAttribute(
np.frombuffer(np.int8(min_int8).tobytes(), dtype=np.uint8).tolist(),
np.frombuffer(np.int8(max_int8).tobytes(), dtype=np.uint8).tolist(),
ts.NanPropagationMode.PROPAGATE,
)

self._serialize_operator(
node,
tosa_graph,
ts.Op.CLAMP,
[inputs[0].name],
[output.name],
attr,
)


@register_node_visitor
class ClampVisitor_FP(ClampVisitor_INT):
# inheriting 'target' from INT class

tosa_specs = [
TosaSpecification.create_from_string("TOSA-1.0+FP"),
]

def __init__(self, *args):
super().__init__(*args)
def _to_bytes(self, value: int | float, dtype: torch.dtype) -> bytes:
if dtype == torch.float32:
return np.frombuffer(np.float32(value).tobytes(), dtype=np.uint8).tolist()
elif dtype == torch.float16:
return np.frombuffer(np.float16(value).tobytes(), dtype=np.uint8).tolist()
elif dtype == torch.int8:
return np.frombuffer(np.int8(value).tobytes(), dtype=np.uint8).tolist()
else:
raise ValueError(f"Unsupported dtype for to_bytes: {dtype}")

def define_node(
self,
Expand All @@ -120,42 +89,20 @@ def define_node(
validate_valid_dtype(
self.target,
[inputs[0], output],
[ts.DType.FP16, ts.DType.FP32],
[ts.DType.INT8, ts.DType.FP16, ts.DType.FP32],
output.tosa_spec,
)

node_input_dtype = node.meta["val"].dtype
# NOTE: Quantization of the min/max arguments is handled by QuantizeOperatorArguments
min_val, max_val = self._get_min_max_arguments(node, node_input_dtype)

attr = ts.TosaSerializerAttribute()
match inputs[0].dtype:
case ts.DType.FP16:
min_f, max_f = self._get_min_max_arguments(
node,
torch.finfo(torch.float16).min,
torch.finfo(torch.float16).max,
)
min_bytes = np.frombuffer(
np.float16(min_f).tobytes(), dtype=np.uint8
).tolist()
max_bytes = np.frombuffer(
np.float16(max_f).tobytes(), dtype=np.uint8
).tolist()
case ts.DType.FP32:
min_f, max_f = self._get_min_max_arguments(
node,
torch.finfo(torch.float32).min,
torch.finfo(torch.float32).max,
)
min_bytes = np.frombuffer(
np.float32(min_f).tobytes(), dtype=np.uint8
).tolist()
max_bytes = np.frombuffer(
np.float32(max_f).tobytes(), dtype=np.uint8
).tolist()
case _:
raise RuntimeError(
f"Internal error: Unsupported dtype {inputs[0].dtype} in {self.target}"
)

attr.ClampAttribute(min_bytes, max_bytes, ts.NanPropagationMode.PROPAGATE)
attr.ClampAttribute(
self._to_bytes(min_val, node_input_dtype),
self._to_bytes(max_val, node_input_dtype),
nan_mode=ts.NanPropagationMode.PROPAGATE,
)

self._serialize_operator(
node,
Expand Down
66 changes: 15 additions & 51 deletions backends/arm/operators/op_where.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.

from typing import Any, List, Sequence
from typing import Any, List

import tosa_serializer as ts

Expand All @@ -23,25 +23,36 @@


@register_node_visitor
class WhereVisitor_INT(NodeVisitor):
class WhereVisitor(NodeVisitor):
target = "aten.where.self"

tosa_specs = [
TosaSpecification.create_from_string("TOSA-1.0+INT"),
TosaSpecification.create_from_string("TOSA-1.0+FP"),
]

def __init__(self, *args):
super().__init__(*args)

def _add_node_to_tosa_graph(
def define_node(
self,
node: Node,
tosa_graph: Any,
inputs: List[TosaArg],
output: TosaArg,
supported_dtypes: Sequence,
) -> None:

supported_dtypes = []
if output.tosa_spec.support_integer():
supported_dtypes += [
ts.DType.BOOL,
ts.DType.INT8,
ts.DType.INT16,
ts.DType.INT32,
]
if output.tosa_spec.support_float():
supported_dtypes += [ts.DType.BOOL, ts.DType.FP16, ts.DType.FP32]

validate_num_inputs(self.target, inputs, 3)
# Not first input, which is condition tensor.
validate_same_dtype(self.target, inputs[1:], ts)
Expand All @@ -63,50 +74,3 @@ def _add_node_to_tosa_graph(
[output.name],
attr,
)

def define_node(
self,
node: Node,
tosa_graph: Any,
inputs: List[TosaArg],
output: TosaArg,
) -> None:
bi_supported_dtypes = [
ts.DType.INT8,
ts.DType.INT16,
ts.DType.INT32,
ts.DType.BOOL,
]
self._add_node_to_tosa_graph(
node, tosa_graph, inputs, output, bi_supported_dtypes
)


@register_node_visitor
class WhereVisitor_FP(WhereVisitor_INT):

tosa_specs = [
TosaSpecification.create_from_string("TOSA-1.0+FP"),
]

def __init__(self, *args):
super().__init__(*args)

def define_node(
self,
node: Node,
tosa_graph: Any,
inputs: List[TosaArg],
output: TosaArg,
) -> None:
mi_supported_dtypes = [
ts.DType.FP16,
ts.DType.FP32,
ts.DType.INT8,
ts.DType.INT16,
ts.DType.INT32,
ts.DType.BOOL,
]
self._add_node_to_tosa_graph(
node, tosa_graph, inputs, output, mi_supported_dtypes
)
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