backends/arm/operators/op_sum.py

# Copyright 2023-2024 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.

# pyre-unsafe

from typing import cast, List

import executorch.backends.arm.tosa_quant_utils as tqutils
import executorch.backends.arm.tosa_utils as tutils

import serializer.tosa_serializer as ts
from executorch.backends.arm.operators.node_visitor import (
    NodeVisitor,
    register_node_visitor,
)
from executorch.backends.arm.tosa_mapping import TosaArg
from serializer.tosa_serializer import TosaOp
from torch.fx import Node


@register_node_visitor
class AddVisitor(NodeVisitor):
    target = "aten.sum.dim_IntList"

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

    def define_node(
        self,
        node: Node,
        tosa_graph: ts.TosaSerializer,
        inputs: List[TosaArg],
        output: TosaArg,
        is_quant_node: bool,
    ) -> None:
        input_node = inputs[0]
        input_shape = list(input_node.shape)
        dim_list = cast(list[int], inputs[1].special)
        dim_list = [dim % len(input_node.shape) for dim in dim_list]
        keep_dim = cast(bool, inputs[2].number if len(inputs) > 2 else False)
        assert keep_dim, "This case should be handled by InsertSqueezeAfterSumPass"

        if is_quant_node:

            # Rescale input to 32 bit
            rescaled_inputs, scale = tqutils.rescale_nodes_to_int32(
                [node.all_input_nodes[0]], tosa_graph
            )

            prev_node = rescaled_inputs[0]
            reduced_shape = input_shape

            # Reduce all dims in dim_list one-by-one.
            for dim in dim_list:
                # When reduced, the size of the dim becomes 1.
                reduced_shape[dim] = 1

                attr = ts.TosaSerializerAttribute()
                attr.AxisAttribute(input_node.dim_order.index(dim))

                next_node = tosa_graph.addIntermediate(
                    tutils.tosa_shape(reduced_shape, input_node.dim_order),
                    dtype=ts.DType.INT32,
                )

                tosa_graph.addOperator(
                    TosaOp.Op().REDUCE_SUM, [prev_node.name], [next_node.name], attr
                )

                prev_node = next_node
            tqutils.rescale_node_back_to_int8(node, prev_node, scale, tosa_graph)
        else:
            input_name = input_node.name
            reduced_shape = input_shape

            # Reduce all dims in dim_list one-by-one.
            for dim in dim_list:
                # When reduced, the size of the dim becomes 1
                reduced_shape[dim] = 1

                attr = ts.TosaSerializerAttribute()
                attr.AxisAttribute(input_node.dim_order.index(dim))

                if dim == dim_list[-1]:
                    output_name = output.name
                else:
                    output_name = tosa_graph.addIntermediate(
                        tutils.tosa_shape(reduced_shape, input_node.dim_order),
                        dtype=ts.DType.FP32,
                    ).name

                tosa_graph.addOperator(
                    TosaOp.Op().REDUCE_SUM, [input_name], [output_name], attr
                )

                input_name = output_name