"""simple docstring"""
from typing import TYPE_CHECKING

from ..utils import _LazyModule


SCREAMING_SNAKE_CASE__   =					{
    "config": [
        "EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
        "OnnxConfig",
        "OnnxConfigWithPast",
        "OnnxSeq2SeqConfigWithPast",
        "PatchingSpec",
    ],
    "convert": ["export", "validate_model_outputs"],
    "features": ["FeaturesManager"],
    "utils": ["ParameterFormat", "compute_serialized_parameters_size"],
}


if TYPE_CHECKING:
					from .config import (
					    EXTERNAL_DATA_FORMAT_SIZE_LIMIT,
					    OnnxConfig,
					    OnnxConfigWithPast,
					    OnnxSeqaSeqConfigWithPast,
					    PatchingSpec,
					)
					from .convert import export, validate_model_outputs
					from .features import FeaturesManager
					from .utils import ParameterFormat, compute_serialized_parameters_size

else:
					import sys

					SCREAMING_SNAKE_CASE__   =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__   =					logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   =					{
    "microsoft/swinv2-tiny-patch4-window8-256": (
        "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
    ),
}



class 					lowerCAmelCase_      (     lowerCAmelCase   ):



				"""simple docstring"""
				_lowerCAmelCase       :      Tuple     					=  """swinv2"""

				_lowerCAmelCase       :      Any     					=  {
				    """num_attention_heads""": """num_heads""",
				    """num_hidden_layers""": """num_layers""",
				}

				def __init__(			self						,      lowerCAmelCase=2_24						,      lowerCAmelCase=4						,      lowerCAmelCase=3						,      lowerCAmelCase=96						,      lowerCAmelCase=[2, 2, 6, 2]						,      lowerCAmelCase=[3, 6, 12, 24]						,      lowerCAmelCase=7						,      lowerCAmelCase=4.0						,      lowerCAmelCase=True						,      lowerCAmelCase=0.0						,      lowerCAmelCase=0.0						,      lowerCAmelCase=0.1						,      lowerCAmelCase="gelu"						,      lowerCAmelCase=False						,      lowerCAmelCase=0.02						,      lowerCAmelCase=1E-5						,      lowerCAmelCase=32						,      **lowerCAmelCase						,      ):






										"""simple docstring"""

										super().__init__(**lowerCAmelCase      )

										snake_case        =     image_size
										snake_case        =     patch_size
										snake_case        =     num_channels
										snake_case        =     embed_dim
										snake_case        =     depths
										snake_case        =     len(lowerCAmelCase      )
										snake_case        =     num_heads
										snake_case        =     window_size
										snake_case        =     mlp_ratio
										snake_case        =     qkv_bias
										snake_case        =     hidden_dropout_prob
										snake_case        =     attention_probs_dropout_prob
										snake_case        =     drop_path_rate
										snake_case        =     hidden_act
										snake_case        =     use_absolute_embeddings
										snake_case        =     layer_norm_eps
										snake_case        =     initializer_range
										snake_case        =     encoder_stride
										# we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
										# this indicates the channel dimension after the last stage of the model
										snake_case        =     int(embed_dim * 2 ** (len(lowerCAmelCase      ) - 1)      )
										snake_case        =     (0, 0, 0, 0)


