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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
#     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,
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from huggingface_hub.dataclasses import strict

from ...configuration_utils import PreTrainedConfig, SubConfigSpec
from ...modeling_rope_utils import RopeParameters
from ...utils import auto_docstring
from ..auto import AutoConfig
from ..timm_wrapper import TimmWrapperConfig


@auto_docstring(checkpoint="facebook/pe-av-large")
@strict
class PeVideoEncoderConfig(PreTrainedConfig):
    r"""
    Example:

    ```python
    >>> from transformers import PeAudioEncoder, PeAudioEncoderConfig

    >>> # Initializing a PeAudioEncoder style configuration
    >>> configuration = PeAudioEncoderConfig()

    >>> # Initializing a model from the pe-av-large style configuration
    >>> model = PeAudioEncoder(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```"""

    model_type = "pe_video_encoder"
    default_theta = 20000
    sub_configs_defaults = {
        "vision_config": SubConfigSpec(
            config_class=TimmWrapperConfig,
            init_kwargs={
                "architecture": "vit_pe_core_large_patch14_336",
                "do_pooling": True,
                "num_classes": 1024,
                "global_pool": "map",
                "initializer_range": 0.02,
            },
        ),
    }
    base_config_key = "audio_video_config"

    vision_config: dict | PreTrainedConfig | None = None
    hidden_size: int = 1792
    intermediate_size: int = 4800
    num_hidden_layers: int = 6
    num_attention_heads: int = 14
    num_key_value_heads: int | None = None
    head_dim: int = 128
    hidden_act: str = "silu"
    max_position_embeddings: int = 10000
    initializer_range: float = 0.02
    rms_norm_eps: float = 1e-5
    rope_parameters: RopeParameters | dict | None = None
    attention_bias: bool = False
    attention_dropout: float | int = 0.0

    def __post_init__(self, **kwargs):
        if self.num_key_value_heads is None:
            self.num_key_value_heads = self.num_attention_heads
        # Keep for BC only - shouldn't appear in new releases!
        if isinstance(self.vision_config, dict):
            self.vision_config = {**self.sub_configs_defaults["vision_config"].init_kwargs, **self.vision_config}
        super().__post_init__(**kwargs)


@auto_docstring(checkpoint="facebook/pe-av-large")
@strict
class PeVideoConfig(PreTrainedConfig):
    r"""
    video_config (`dict` or `PreTrainedConfig`, *optional*):
        Configuration for the video encoder component.

    ```python
    >>> from transformers import PeVideoModel, PeVideoConfig

    >>> # Initializing a PeVideoModel style configuration
    >>> configuration = PeVideoConfig()

    >>> # Initializing a model from the pe-av-large style configuration
    >>> model = PeVideoModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```"""

    model_type = "pe_video"
    sub_configs_defaults = {
        "text_config": SubConfigSpec(
            config_class=AutoConfig,
            model_type="modernbert",
            init_kwargs={
                "hidden_size": 1024,
                "intermediate_size": 2624,
                "num_hidden_layers": 22,
                "num_attention_heads": 16,
            },
        ),
        "video_config": SubConfigSpec(config_class=PeVideoEncoderConfig),
    }
    base_config_key = "audio_video_config"

    text_config: dict | PreTrainedConfig | None = None
    video_config: dict | PreTrainedConfig | None = None

    def __post_init__(self, **kwargs):
        # Keep for BC only - shouldn't appear in new releases!
        if isinstance(self.text_config, dict):
            self.text_config = {**self.sub_configs_defaults["text_config"].init_kwargs, **self.text_config}
        super().__post_init__(**kwargs)


__all__ = ["PeVideoEncoderConfig", "PeVideoConfig"]