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#           This file was automatically generated from src/transformers/models/cosmos3_omni/modular_cosmos3_omni.py.
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#                          modular_cosmos3_omni.py file directly. One of our CI enforces this.
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# Copyright 2026 NVIDIA Corporation and The HuggingFace Inc. 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.

from huggingface_hub.dataclasses import strict

from ...configuration_utils import PreTrainedConfig
from ...utils import auto_docstring
from ..auto import CONFIG_MAPPING, AutoConfig


@auto_docstring(checkpoint="nvidia/Cosmos3-Nano")
@strict
class Cosmos3OmniConfig(PreTrainedConfig):
    r"""
    Example:

    ```python
    >>> from transformers import Cosmos3OmniForConditionalGeneration, Cosmos3OmniConfig

    >>> # Initializing a Cosmos3 style configuration
    >>> configuration = Cosmos3OmniConfig()

    >>> # Initializing a model from the Cosmos3 style configuration
    >>> model = Cosmos3OmniForConditionalGeneration(configuration)

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

    model_type = "cosmos3_omni"
    sub_configs = {"vision_config": AutoConfig, "text_config": AutoConfig}
    keys_to_ignore_at_inference = ["past_key_values"]

    text_config: dict | PreTrainedConfig | None = None
    vision_config: dict | PreTrainedConfig | None = None
    image_token_id: int = 151655
    video_token_id: int = 151656
    vision_start_token_id: int = 151652
    vision_end_token_id: int = 151653
    tie_word_embeddings: bool = False

    def __post_init__(self, **kwargs):
        if isinstance(self.vision_config, dict):
            model_type = self.vision_config.pop("model_type", "qwen3_vl_vision")
            if model_type == "qwen3_vl":
                model_type = "qwen3_vl_vision"
            self.vision_config = CONFIG_MAPPING[model_type](**self.vision_config)
        elif self.vision_config is None:
            self.vision_config = CONFIG_MAPPING["qwen3_vl_vision"]()

        if isinstance(self.text_config, dict):
            model_type = self.text_config.get("model_type", "qwen3_vl_text")
            self.text_config = CONFIG_MAPPING[model_type](**self.text_config)
        elif self.text_config is None:
            self.text_config = CONFIG_MAPPING["qwen3_vl_text"]()

        super().__post_init__(**kwargs)


__all__ = ["Cosmos3OmniConfig"]
