"""simple docstring"""



from . import __version__

# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
    CLOUDFRONT_DISTRIB_PREFIX,
    CONFIG_NAME,
    DISABLE_TELEMETRY,
    DUMMY_INPUTS,
    DUMMY_MASK,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    FEATURE_EXTRACTOR_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_PREFIX,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    MODEL_CARD_NAME,
    MULTIPLE_CHOICE_DUMMY_INPUTS,
    PYTORCH_PRETRAINED_BERT_CACHE,
    PYTORCH_TRANSFORMERS_CACHE,
    S3_BUCKET_PREFIX,
    SENTENCEPIECE_UNDERLINE,
    SPIECE_UNDERLINE,
    TF2_WEIGHTS_NAME,
    TF_WEIGHTS_NAME,
    TORCH_FX_REQUIRED_VERSION,
    TRANSFORMERS_CACHE,
    TRANSFORMERS_DYNAMIC_MODULE_NAME,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    WEIGHTS_INDEX_NAME,
    WEIGHTS_NAME,
    ContextManagers,
    DummyObject,
    EntryNotFoundError,
    ExplicitEnum,
    ModelOutput,
    PaddingStrategy,
    PushToHubMixin,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    TensorType,
    _LazyModule,
    add_code_sample_docstrings,
    add_end_docstrings,
    add_start_docstrings,
    add_start_docstrings_to_model_forward,
    cached_property,
    copy_func,
    default_cache_path,
    define_sagemaker_information,
    get_cached_models,
    get_file_from_repo,
    get_full_repo_name,
    get_torch_version,
    has_file,
    http_user_agent,
    is_apex_available,
    is_bsa_available,
    is_coloredlogs_available,
    is_datasets_available,
    is_detectrona_available,
    is_faiss_available,
    is_flax_available,
    is_ftfy_available,
    is_in_notebook,
    is_ipex_available,
    is_librosa_available,
    is_offline_mode,
    is_onnx_available,
    is_pandas_available,
    is_phonemizer_available,
    is_protobuf_available,
    is_psutil_available,
    is_pyanvml_available,
    is_pyctcdecode_available,
    is_pytesseract_available,
    is_pytorch_quantization_available,
    is_rjieba_available,
    is_sagemaker_dp_enabled,
    is_sagemaker_mp_enabled,
    is_scipy_available,
    is_sentencepiece_available,
    is_seqio_available,
    is_sklearn_available,
    is_soundfile_availble,
    is_spacy_available,
    is_speech_available,
    is_tensor,
    is_tensorflow_probability_available,
    is_tfaonnx_available,
    is_tf_available,
    is_timm_available,
    is_tokenizers_available,
    is_torch_available,
    is_torch_bfaa_available,
    is_torch_cuda_available,
    is_torch_fx_available,
    is_torch_fx_proxy,
    is_torch_mps_available,
    is_torch_tfaa_available,
    is_torch_tpu_available,
    is_torchaudio_available,
    is_training_run_on_sagemaker,
    is_vision_available,
    replace_return_docstrings,
    requires_backends,
    to_numpy,
    to_py_obj,
    torch_only_method,
)

"""simple docstring"""



from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


SCREAMING_SNAKE_CASE__:List[str]			=	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__:int			=	{
    """microsoft/focalnet-tiny""": """https://huggingface.co/microsoft/focalnet-tiny/resolve/main/config.json""",
}






class 				snake_case__     (   snake_case_,		snake_case_   ):
 _snake_case   :			List[Any]           =		"""focalnet"""


 def __init__(				self  ,						lowerCamelCase=224  ,						lowerCamelCase=4  ,						lowerCamelCase=3  ,						lowerCamelCase=96  ,						lowerCamelCase=False  ,						lowerCamelCase=[192, 384, 768, 768]  ,						lowerCamelCase=[2, 2, 6, 2]  ,						lowerCamelCase=[2, 2, 2, 2]  ,						lowerCamelCase=[3, 3, 3, 3]  ,						lowerCamelCase="gelu"  ,						lowerCamelCase=4.0  ,						lowerCamelCase=0.0  ,						lowerCamelCase=0.1  ,						lowerCamelCase=False  ,						lowerCamelCase=1E-4  ,						lowerCamelCase=False  ,						lowerCamelCase=False  ,						lowerCamelCase=False  ,						lowerCamelCase=0.02  ,						lowerCamelCase=1E-5  ,						lowerCamelCase=32  ,						lowerCamelCase=None  ,						lowerCamelCase=None  ,						**lowerCamelCase  ,						):
        super().__init__(**lowerCamelCase		)

        __a     				=  image_size
        __a     				=  patch_size
        __a     				=  num_channels
        __a     				=  embed_dim
        __a     				=  use_conv_embed
        __a     				=  hidden_sizes
        __a     				=  depths
        __a     				=  focal_levels
        __a     				=  focal_windows
        __a     				=  hidden_act
        __a     				=  mlp_ratio
        __a     				=  hidden_dropout_prob
        __a     				=  drop_path_rate
        __a     				=  use_layerscale
        __a     				=  layerscale_value
        __a     				=  use_post_layernorm
        __a     				=  use_post_layernorm_in_modulation
        __a     				=  normalize_modulator
        __a     				=  initializer_range
        __a     				=  layer_norm_eps
        __a     				=  encoder_stride
        __a     				=  ["stem"] + [F"stage{idx}" for idx in range(1  ,						len(self.depths		) + 1		)]
        __a				, __a     				=  get_aligned_output_features_output_indices(
            out_features=lowerCamelCase  ,						out_indices=lowerCamelCase  ,						stage_names=self.stage_names		)
