# Copyright 2023-2025 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.

# pyre-unsafe

from typing import Any, List

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

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 executorch.backends.arm.tosa_specification import TosaSpecification
from torch.fx import Node


@register_node_visitor
class SubVisitor_080_BI(NodeVisitor):
    target = "aten.sub.Tensor"

    tosa_specs = [
        TosaSpecification.create_from_string("TOSA-0.80+BI"),
    ]

    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  # type: ignore

        validate_num_inputs(self.target, inputs, 2)
        validate_same_dtype(self.target, [*inputs, output])

        # Handle int8 (quantized) and int32
        supported_dtypes = [ts.DType.INT8, ts.DType.INT32]
        if inputs[0].dtype not in supported_dtypes:
            raise TypeError(
                f'IO data type needs to be {supported_dtypes}, got "{inputs[0].dtype}"'
            )

        scale_back = 1.0
        if inputs[0].dtype == ts.DType.INT8:
            rescaled_inputs, scale_back = tqutils.insert_rescale_ops_to_int32(
                tosa_graph, inputs, node
            )
        else:
            # input[0].dtype == ts.DType.INT32
            # Non quantized input, natively support by TOSA.SUB
            rescaled_inputs = inputs

        if output.dtype == ts.DType.INT8:
            broadcasted_shape = tutils.tosa_shape(output.shape, output.dim_order)
            sub_output = tosa_graph.addIntermediate(broadcasted_shape, ts.DType.INT32)
        else:
            # output.dtype == ts.DType.INT32
            sub_output = output

        # Do the INT32 Sub
        tosa_graph.addOperator(
            ts.TosaOp.Op().SUB,
            [
                rescaled_inputs[0].name,
                rescaled_inputs[1].name,
            ],
            [sub_output.name],
            None,
        )

        if output.dtype == ts.DType.INT8:
            # Scale output back to 8 bit
            # pyre-ignore
            tqutils.insert_rescale_op_to_int8(
                tosa_graph, sub_output, scale_back, node
            )  # type: ignore[possibly-undefined]


@register_node_visitor
class SubVisitor_080_MI(SubVisitor_080_BI):
    # inheriting 'target' from BI class

    tosa_specs = [
        TosaSpecification.create_from_string("TOSA-0.80+MI"),
    ]

    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  # type: ignore

        validate_num_inputs(self.target, inputs, 2)
        validate_same_dtype(self.target, [*inputs, output])

        if inputs[0].dtype in [ts.DType.INT8, ts.DType.INT32]:
            # Call the inherited define_node for handling integers
            super().define_node(node, tosa_graph, inputs, output)
        else:
            # FP32 Sub lowering
            if (
                inputs[0].dtype != ts.DType.FP32
                or inputs[1].dtype != ts.DType.FP32
                or output.dtype != ts.DType.FP32
            ):
                raise TypeError(
                    f"All IO needs to have data type fp32. Got: {inputs[0].dtype}, "
                    f"input 2: {inputs[1].dtype} and output: {output.dtype}"
                )

            # MI lowering
            tosa_graph.addOperator(
                ts.TosaOp.Op().SUB,
                [inputs[0].name, inputs[1].name],
                [output.name],
                None,
            )


@register_node_visitor
class SubVisitor_INT(NodeVisitor):
    target = "aten.sub.Tensor"

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

    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  # type: ignore

        validate_num_inputs(self.target, inputs, 2)
        validate_same_dtype(self.target, [*inputs, output])

        # Handle int8 (quantized) and int32
        supported_dtypes = [ts.DType.INT8, ts.DType.INT32]
        if inputs[0].dtype not in supported_dtypes:
            raise TypeError(
                f'IO data type needs to be {supported_dtypes}, got "{inputs[0].dtype}"'
            )

        scale_back = 1.0
        if inputs[0].dtype == ts.DType.INT8:
            rescaled_inputs, scale_back = tqutils.insert_rescale_ops_to_int32(
                tosa_graph, inputs, node, self.tosa_spec
            )
        else:
            # input[0].dtype == ts.DType.INT32
            # Non quantized input, natively support by TOSA.SUB
            rescaled_inputs = inputs

        if output.dtype == ts.DType.INT8:
            broadcasted_shape = tutils.tosa_shape(output.shape, output.dim_order)
            sub_output = tosa_graph.addIntermediate(broadcasted_shape, ts.DType.INT32)
        else:
            # output.dtype == ts.DType.INT32
            sub_output = output

        # Do the INT32 Sub
        tosa_graph.addOperator(
            ts.TosaOp.Op().SUB,
            [
                rescaled_inputs[0].name,
                rescaled_inputs[1].name,
            ],
            [sub_output.name],
            None,
        )

        if output.dtype == ts.DType.INT8:
            # Scale output back to 8 bit
            # pyre-ignore
            tqutils.insert_rescale_op_to_int8(
                tosa_graph, sub_output, scale_back, node, self.tosa_spec
            )  # type: ignore[possibly-undefined]


@register_node_visitor
class SubVisitor_FP(SubVisitor_INT):
    # inheriting 'target' from INT class

    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:

        import serializer.tosa_serializer as ts  # type: ignore

        validate_num_inputs(self.target, inputs, 2)
        validate_same_dtype(self.target, [*inputs, output])

        if inputs[0].dtype in [ts.DType.INT8, ts.DType.INT32]:
            # Call the inherited define_node for handling integers
            super().define_node(node, tosa_graph, inputs, output)
        else:
            # FP32 Sub lowering
            if (
                inputs[0].dtype != ts.DType.FP32
                or inputs[1].dtype != ts.DType.FP32
                or output.dtype != ts.DType.FP32
            ):
                raise TypeError(
                    f"All IO needs to have data type fp32. Got: {inputs[0].dtype}, "
                    f"input 2: {inputs[1].dtype} and output: {output.dtype}"
                )

            # MI lowering
            tosa_graph.addOperator(
                ts.TosaOp.Op().SUB,
                [inputs[0].name, inputs[1].name],
                [output.name],
                None,
            )