# Copyright (c) Meta Platforms, Inc. and affiliates.
# Copyright 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 Callable, List, Optional

import torch
import torch.fx
from executorch.backends.arm.quantizer import arm_quantizer_utils
from executorch.backends.arm.quantizer.quantization_annotation import register_annotator
from executorch.backends.arm.quantizer.quantization_config import QuantizationConfig
from torch.ao.quantization.quantizer import QuantizationAnnotation
from torch.fx import Node


@register_annotator("mul")
def _annotate_mul(
    gm: torch.fx.GraphModule,
    quantization_config: QuantizationConfig,
    filter_fn: Optional[Callable[[Node], bool]] = None,
) -> Optional[List[List[Node]]]:

    annotated_partitions = []
    for node in gm.graph.nodes:
        if node.target not in (torch.ops.aten.mul.Tensor, torch.ops.aten.mul_.Tensor):
            continue
        mul_node = node
        annotated_partitions.append([mul_node])
        if arm_quantizer_utils.is_annotated(mul_node):
            continue

        input_act_qspec = quantization_config.get_input_act_qspec()
        output_act_qspec = quantization_config.get_output_act_qspec()

        input_qspec_map = {}
        input_act0 = mul_node.args[0]
        if isinstance(input_act0, Node):
            if arm_quantizer_utils.is_input_large_scalar(input_act0, gm):
                continue
            if arm_quantizer_utils.is_input_non_float_tensor(input_act0):
                continue
            input_qspec_map[input_act0] = input_act_qspec

        input_act1 = mul_node.args[1]
        if isinstance(input_act1, Node):
            if arm_quantizer_utils.is_input_large_scalar(input_act1, gm):
                continue
            if arm_quantizer_utils.is_input_non_float_tensor(input_act1):
                continue
            input_qspec_map[input_act1] = input_act_qspec

        mul_node.meta["quantization_annotation"] = QuantizationAnnotation(
            input_qspec_map=input_qspec_map,
            output_qspec=output_act_qspec,
            _annotated=True,
        )
    return annotated_partitions