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from typing import Any, Dict, Mapping, cast

import torch.nn as nn
import torch.optim as optim

from compressai.registry import register_optimizer


@register_optimizer("net_aux")
def net_aux_optimizer(
    net: nn.Module, conf: Mapping[str, Any]
) -> Dict[str, optim.Optimizer]:
    """Returns separate optimizers for net and auxiliary losses.

    Each optimizer operates on a mutually exclusive set of parameters.
    """
    parameters = {
        "net": {
            name
            for name, param in net.named_parameters()
            if param.requires_grad and not name.endswith(".quantiles")
        },
        "aux": {
            name
            for name, param in net.named_parameters()
            if param.requires_grad and name.endswith(".quantiles")
        },
    }

    # Make sure we don't have an intersection of parameters
    params_dict = dict(net.named_parameters())
    inter_params = parameters["net"] & parameters["aux"]
    union_params = parameters["net"] | parameters["aux"]
    assert len(inter_params) == 0
    assert len(union_params) - len(params_dict.keys()) == 0

    optimizer = {
        "net": optim.Adam(
            (params_dict[name] for name in sorted(parameters["net"])),
            lr=conf["net"]["lr"],
        ),
        "aux": optim.Adam(
            (params_dict[name] for name in sorted(parameters["aux"])),
            lr=conf["aux"]["lr"],
        ),
    }

    return cast(Dict[str, optim.Optimizer], optimizer)
