# Copyright 2026 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import functools
from typing import Any

import torch

from ..utils.logging import get_logger
from ..utils.torch_utils import unwrap_module


logger = get_logger(__name__)  # pylint: disable=invalid-name


class BaseState:
    def reset(self, *args, **kwargs) -> None:
        raise NotImplementedError(
            "BaseState::reset is not implemented. Please implement this method in the derived class."
        )


class StateManager:
    def __init__(self, state_cls: BaseState, init_args=None, init_kwargs=None):
        self._state_cls = state_cls
        self._init_args = init_args if init_args is not None else ()
        self._init_kwargs = init_kwargs if init_kwargs is not None else {}
        self._state_cache = {}
        self._current_context = None

    def get_state(self):
        if self._current_context is None:
            raise ValueError("No context is set. Please set a context before retrieving the state.")
        if self._current_context not in self._state_cache.keys():
            self._state_cache[self._current_context] = self._state_cls(*self._init_args, **self._init_kwargs)
        return self._state_cache[self._current_context]

    def set_context(self, name: str) -> None:
        self._current_context = name

    def reset(self, *args, **kwargs) -> None:
        for name, state in list(self._state_cache.items()):
            state.reset(*args, **kwargs)
            self._state_cache.pop(name)
        self._current_context = None


class ModelHook:
    r"""
    A hook that contains callbacks to be executed just before and after the forward method of a model.
    """

    _is_stateful = False

    def __init__(self):
        self.fn_ref: "HookFunctionReference" = None

    def initialize_hook(self, module: torch.nn.Module) -> torch.nn.Module:
        r"""
        Hook that is executed when a model is initialized.

        Args:
            module (`torch.nn.Module`):
                The module attached to this hook.
        """
        return module

    def deinitalize_hook(self, module: torch.nn.Module) -> torch.nn.Module:
        r"""
        Hook that is executed when a model is deinitialized.

        Args:
            module (`torch.nn.Module`):
                The module attached to this hook.
        """
        return module

    def pre_forward(self, module: torch.nn.Module, *args, **kwargs) -> tuple[tuple[Any], dict[str, Any]]:
        r"""
        Hook that is executed just before the forward method of the model.

        Args:
            module (`torch.nn.Module`):
                The module whose forward pass will be executed just after this event.
            args (`tuple[Any]`):
                The positional arguments passed to the module.
            kwargs (`dict[Str, Any]`):
                The keyword arguments passed to the module.
        Returns:
            `tuple[tuple[Any], dict[Str, Any]]`:
                A tuple with the treated `args` and `kwargs`.
        """
        return args, kwargs

    def post_forward(self, module: torch.nn.Module, output: Any) -> Any:
        r"""
        Hook that is executed just after the forward method of the model.

        Args:
            module (`torch.nn.Module`):
                The module whose forward pass been executed just before this event.
            output (`Any`):
                The output of the module.
        Returns:
            `Any`: The processed `output`.
        """
        return output

    def detach_hook(self, module: torch.nn.Module) -> torch.nn.Module:
        r"""
        Hook that is executed when the hook is detached from a module.

        Args:
            module (`torch.nn.Module`):
                The module detached from this hook.
        """
        return module

    def reset_state(self, module: torch.nn.Module):
        if self._is_stateful:
            raise NotImplementedError("This hook is stateful and needs to implement the `reset_state` method.")
        return module

    def _set_context(self, module: torch.nn.Module, name: str) -> None:
        # Iterate over all attributes of the hook to see if any of them have the type `StateManager`. If so, call `set_context` on them.
        for attr_name in dir(self):
            attr = getattr(self, attr_name)
            if isinstance(attr, StateManager):
                attr.set_context(name)
        return module


class HookFunctionReference:
    def __init__(self) -> None:
        """A container class that maintains mutable references to forward pass functions in a hook chain.

        Its mutable nature allows the hook system to modify the execution chain dynamically without rebuilding the
        entire forward pass structure.

        Attributes:
            pre_forward: A callable that processes inputs before the main forward pass.
            post_forward: A callable that processes outputs after the main forward pass.
            forward: The current forward function in the hook chain.
            original_forward: The original forward function, stored when a hook provides a custom new_forward.

        The class enables hook removal by allowing updates to the forward chain through reference modification rather
        than requiring reconstruction of the entire chain. When a hook is removed, only the relevant references need to
        be updated, preserving the execution order of the remaining hooks.
        """
        self.pre_forward = None
        self.post_forward = None
        self.forward = None
        self.original_forward = None


class HookRegistry:
    def __init__(self, module_ref: torch.nn.Module) -> None:
        super().__init__()

        self.hooks: dict[str, ModelHook] = {}

        self._module_ref = module_ref
        self._hook_order = []
        self._fn_refs = []

    def register_hook(self, hook: ModelHook, name: str) -> None:
        if name in self.hooks.keys():
            raise ValueError(
                f"Hook with name {name} already exists in the registry. Please use a different name or "
                f"first remove the existing hook and then add a new one."
            )

        self._module_ref = hook.initialize_hook(self._module_ref)

        def create_new_forward(function_reference: HookFunctionReference):
            def new_forward(module, *args, **kwargs):
                args, kwargs = function_reference.pre_forward(module, *args, **kwargs)
                output = function_reference.forward(*args, **kwargs)
                return function_reference.post_forward(module, output)

            return new_forward

        forward = self._module_ref.forward

        fn_ref = HookFunctionReference()
        fn_ref.pre_forward = hook.pre_forward
        fn_ref.post_forward = hook.post_forward
        fn_ref.forward = forward

        if hasattr(hook, "new_forward"):
            fn_ref.original_forward = forward
            fn_ref.forward = functools.update_wrapper(
                functools.partial(hook.new_forward, self._module_ref), hook.new_forward
            )

        rewritten_forward = create_new_forward(fn_ref)
        # Wrap from the original `forward` so `inspect.signature` follows `__wrapped__` to the real
        # signature instead of the generic `(module, *args, **kwargs)`, which breaks `torch.export`.
        self._module_ref.forward = functools.update_wrapper(
            functools.partial(rewritten_forward, self._module_ref), forward
        )

        hook.fn_ref = fn_ref
        self.hooks[name] = hook
        self._hook_order.append(name)
        self._fn_refs.append(fn_ref)

    def get_hook(self, name: str) -> ModelHook | None:
        return self.hooks.get(name, None)

    def remove_hook(self, name: str, recurse: bool = True) -> None:
        if name in self.hooks.keys():
            num_hooks = len(self._hook_order)
            hook = self.hooks[name]
            index = self._hook_order.index(name)
            fn_ref = self._fn_refs[index]

            old_forward = fn_ref.forward
            if fn_ref.original_forward is not None:
                old_forward = fn_ref.original_forward

            if index == num_hooks - 1:
                self._module_ref.forward = old_forward
            else:
                self._fn_refs[index + 1].forward = old_forward

            self._module_ref = hook.deinitalize_hook(self._module_ref)
            del self.hooks[name]
            self._hook_order.pop(index)
            self._fn_refs.pop(index)

        if recurse:
            for module_name, module in self._module_ref.named_modules():
                if module_name == "":
                    continue
                if hasattr(module, "_diffusers_hook"):
                    module._diffusers_hook.remove_hook(name, recurse=False)

    def reset_stateful_hooks(self, recurse: bool = True) -> None:
        for hook_name in reversed(self._hook_order):
            hook = self.hooks[hook_name]
            if hook._is_stateful:
                hook.reset_state(self._module_ref)

        if recurse:
            for module_name, module in unwrap_module(self._module_ref).named_modules():
                if module_name == "":
                    continue
                module = unwrap_module(module)
                if hasattr(module, "_diffusers_hook"):
                    module._diffusers_hook.reset_stateful_hooks(recurse=False)

    @classmethod
    def check_if_exists_or_initialize(cls, module: torch.nn.Module) -> "HookRegistry":
        if not hasattr(module, "_diffusers_hook"):
            module._diffusers_hook = cls(module)
        return module._diffusers_hook

    def _set_context(self, name: str | None = None) -> None:
        for hook_name in reversed(self._hook_order):
            hook = self.hooks[hook_name]
            if hook._is_stateful:
                hook._set_context(self._module_ref, name)

        for registry in self._get_child_registries():
            registry._set_context(name)

    def invalidate_child_registries_cache(self) -> None:
        """Invalidate the cached child-registry list across this module's tree.

        `_get_child_registries` caches the registries it finds by walking `named_modules()`, keyed on the registry that
        built it. Registering or removing hooks on descendant modules (e.g. block hooks added by `enable_cache`)
        changes which modules carry a `_diffusers_hook`, which stales that cache. Call this after any operation that
        adds or removes hooks in the subtree so the list is rebuilt on next use. Clears the cache on every registry in
        the tree, since the same registries appear in ancestor caches.
        """
        for _, module in unwrap_module(self._module_ref).named_modules():
            module = unwrap_module(module)
            if hasattr(module, "_diffusers_hook"):
                module._diffusers_hook._child_registries_cache = None

    def _get_child_registries(self) -> list["HookRegistry"]:
        """Return registries of child modules, using a cached list when available.

        The cache is built on first call and reused for subsequent calls. This avoids the cost of walking the full
        module tree via named_modules() on every _set_context call, which is significant for large models (e.g. ~2.7ms
        per call on Flux2).
        """
        if not hasattr(self, "_child_registries_cache"):
            self._child_registries_cache = None

        if self._child_registries_cache is not None:
            return self._child_registries_cache

        registries = []
        for module_name, module in unwrap_module(self._module_ref).named_modules():
            if module_name == "":
                continue
            module = unwrap_module(module)
            if hasattr(module, "_diffusers_hook"):
                registries.append(module._diffusers_hook)
        self._child_registries_cache = registries
        return registries

    def __repr__(self) -> str:
        registry_repr = ""
        for i, hook_name in enumerate(self._hook_order):
            if self.hooks[hook_name].__class__.__repr__ is not object.__repr__:
                hook_repr = self.hooks[hook_name].__repr__()
            else:
                hook_repr = self.hooks[hook_name].__class__.__name__
            registry_repr += f"  ({i}) {hook_name} - {hook_repr}"
            if i < len(self._hook_order) - 1:
                registry_repr += "\n"
        return f"HookRegistry(\n{registry_repr}\n)"