# 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.
from typing import Any, List

from executorch.backends.arm._passes.arm_pass_utils import get_first_fake_tensor
from executorch.backends.arm.operators.node_visitor import (
    NodeVisitor,
    register_node_visitor,
)
from executorch.backends.arm.operators.operator_validation_utils import (
    validate_num_inputs,
    validate_same_dtype,
)
from executorch.backends.arm.tosa_mapping import TosaArg
from torch.fx import Node


@register_node_visitor
class MaxVisitor_0_80(NodeVisitor):
    target = "aten.amax.default"

    tosa_specs = NodeVisitor.tosa_specs_0_80

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

    def define_node(
        self,
        node: Node,
        tosa_graph: Any,
        inputs: List[TosaArg],
        output: TosaArg,
    ) -> None:
        import tosa_tools.v0_80.serializer.tosa_serializer as ts

        validate_num_inputs(self.target, inputs, 3)
        validate_same_dtype(self.target, [inputs[0], output])

        input = inputs[0]
        dim = inputs[1].number

        if dim < 0:
            tensor = get_first_fake_tensor(node)
            rank = len(tensor.size())
            dim = rank + dim

        keep_dims = inputs[2].number
        if not keep_dims:
            raise RuntimeError(
                "TOSA only supports keepdims == True; Did you run the convert_minmax pass?"
            )

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

        tosa_graph.addOperator(
            ts.TosaOp.Op().REDUCE_MAX, [input.name], [output.name], attr
        )


@register_node_visitor
class MaxVisitor(NodeVisitor):
    target = "aten.amax.default"

    tosa_specs = NodeVisitor.tosa_specs_1_00

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

    def define_node(
        self,
        node: Node,
        tosa_graph: Any,
        inputs: List[TosaArg],
        output: TosaArg,
    ) -> None:
        import serializer.tosa_serializer as ts

        validate_num_inputs(self.target, inputs, 3)
        validate_same_dtype(self.target, [inputs[0], output])

        input = inputs[0]
        dim = inputs[1].number

        if dim < 0:
            tensor = get_first_fake_tensor(node)
            rank = len(tensor.size())
            dim = rank + dim

        keep_dims = inputs[2].number
        if not keep_dims:
            raise RuntimeError(
                "TOSA only supports keepdims == True; Did you run the convert_minmax pass?"
            )

        attr = ts.TosaSerializerAttribute()
        attr.ReduceMaxAttribute(axis=input.dim_order.index(dim), nan_mode=1)
        tosa_graph.addOperator(
            ts.TosaOp.Op().REDUCE_MAX, [input.name], [output.name], attr
        )