





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


UpperCamelCase__											= logging.get_logger(__name__)

class        __SCREAMING_SNAKE_CASE					(     _a   ,		_a       ):
							snake_case     :      Optional[int]						     =       """maskformer-swin"""

							snake_case     :      List[str]						     =       {
							    """num_attention_heads""": """num_heads""",
							    """num_hidden_layers""": """num_layers""",
							}






							def __init__(						self  , __lowerCAmelCase=224  , __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=None  , __lowerCAmelCase=None  , **__lowerCAmelCase  , ):
														super().__init__(**__lowerCAmelCase  )

														UpperCamelCase__				     =			image_size
														UpperCamelCase__				     =			patch_size
														UpperCamelCase__				     =			num_channels
														UpperCamelCase__				     =			embed_dim
														UpperCamelCase__				     =			depths
														UpperCamelCase__				     =			len(__lowerCAmelCase  )
														UpperCamelCase__				     =			num_heads
														UpperCamelCase__				     =			window_size
														UpperCamelCase__				     =			mlp_ratio
														UpperCamelCase__				     =			qkv_bias
														UpperCamelCase__				     =			hidden_dropout_prob
														UpperCamelCase__				     =			attention_probs_dropout_prob
														UpperCamelCase__				     =			drop_path_rate
														UpperCamelCase__				     =			hidden_act
														UpperCamelCase__				     =			use_absolute_embeddings
														UpperCamelCase__				     =			layer_norm_eps
														UpperCamelCase__				     =			initializer_range
														# we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
														# this indicates the channel dimension after the last stage of the model
														UpperCamelCase__				     =			int(embed_dim * 2 ** (len(__lowerCAmelCase  ) - 1)  )
														UpperCamelCase__				     =			["""stem"""] + [f"""stage{idx}""" for idx in range(1  , len(__lowerCAmelCase  ) + 1  )]
														UpperCamelCase__     ,     UpperCamelCase__				     =			get_aligned_output_features_output_indices(
														    out_features=__lowerCAmelCase  , out_indices=__lowerCAmelCase  , stage_names=self.stage_names  )











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCamelCase__											= {
    "configuration_pix2struct": [
        "PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Pix2StructConfig",
        "Pix2StructTextConfig",
        "Pix2StructVisionConfig",
    ],
    "processing_pix2struct": ["Pix2StructProcessor"],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__											= ["Pix2StructImageProcessor"]


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__											= [
					    "PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "Pix2StructPreTrainedModel",
					    "Pix2StructForConditionalGeneration",
					    "Pix2StructVisionModel",
					    "Pix2StructTextModel",
					]

if TYPE_CHECKING:
					from .configuration_pixastruct import (
					    PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    PixaStructConfig,
					    PixaStructTextConfig,
					    PixaStructVisionConfig,
					)
					from .processing_pixastruct import PixaStructProcessor

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_pixastruct import PixaStructImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_pixastruct import (
										    PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    PixaStructForConditionalGeneration,
										    PixaStructPreTrainedModel,
										    PixaStructTextModel,
										    PixaStructVisionModel,
										)

else:
					import sys

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




