



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase		       =      logging.get_logger(__name__)

lowerCamelCase		       =      {
    """xlm-mlm-en-2048""": """https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json""",
    """xlm-mlm-ende-1024""": """https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json""",
    """xlm-mlm-enfr-1024""": """https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json""",
    """xlm-mlm-enro-1024""": """https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json""",
    """xlm-mlm-tlm-xnli15-1024""": """https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json""",
    """xlm-mlm-xnli15-1024""": """https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json""",
    """xlm-clm-enfr-1024""": """https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json""",
    """xlm-clm-ende-1024""": """https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json""",
    """xlm-mlm-17-1280""": """https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json""",
    """xlm-mlm-100-1280""": """https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json""",
}


class 				_a						(       SCREAMING_SNAKE_CASE			):





							'''simple docstring'''

							A				:Optional[Any] =       "xlm"
							A				:Optional[Any] =       {
							    "hidden_size": "emb_dim",
							    "num_attention_heads": "n_heads",
							    "num_hidden_layers": "n_layers",
							    "n_words": "vocab_size",  # For backward compatibility
							}



							def __init__(							self ,					__UpperCAmelCase=3_0145 ,					__UpperCAmelCase=2048 ,					__UpperCAmelCase=12 ,					__UpperCAmelCase=16 ,					__UpperCAmelCase=0.1 ,					__UpperCAmelCase=0.1 ,					__UpperCAmelCase=True ,					__UpperCAmelCase=False ,					__UpperCAmelCase=False ,					__UpperCAmelCase=False ,					__UpperCAmelCase=1 ,					__UpperCAmelCase=True ,					__UpperCAmelCase=512 ,					__UpperCAmelCase=2048**-0.5 ,					__UpperCAmelCase=1E-12 ,					__UpperCAmelCase=0.0_2 ,					__UpperCAmelCase=0 ,					__UpperCAmelCase=1 ,					__UpperCAmelCase=2 ,					__UpperCAmelCase=3 ,					__UpperCAmelCase=5 ,					__UpperCAmelCase=True ,					__UpperCAmelCase="first" ,					__UpperCAmelCase=True ,					__UpperCAmelCase=None ,					__UpperCAmelCase=True ,					__UpperCAmelCase=0.1 ,					__UpperCAmelCase=5 ,					__UpperCAmelCase=5 ,					__UpperCAmelCase=0 ,					__UpperCAmelCase=0 ,					__UpperCAmelCase=2 ,					__UpperCAmelCase=0 ,					**__UpperCAmelCase ,					):







											"""simple docstring"""



											a__	:							Tuple      						= vocab_size
											a__	:							Optional[Any]      						= emb_dim
											a__	:							Optional[int]      						= n_layers
											a__	:							Optional[int]      						= n_heads
											a__	:							Optional[int]      						= dropout
											a__	:							Any      						= attention_dropout
											a__	:							Optional[Any]      						= gelu_activation
											a__	:							Tuple      						= sinusoidal_embeddings
											a__	:							List[str]      						= causal
											a__	:							str      						= asm
											a__	:							List[Any]      						= n_langs
											a__	:							Tuple      						= use_lang_emb
											a__	:							Dict      						= layer_norm_eps
											a__	:							int      						= bos_index
											a__	:							Optional[int]      						= eos_index
											a__	:							List[Any]      						= pad_index
											a__	:							Optional[Any]      						= unk_index
											a__	:							Optional[int]      						= mask_index
											a__	:							int      						= is_encoder
											a__	:							int      						= max_position_embeddings
											a__	:							Tuple      						= embed_init_std
											a__	:							int      						= init_std
											a__	:							Dict      						= summary_type
											a__	:							Tuple      						= summary_use_proj
											a__	:							Dict      						= summary_activation
											a__	:							Dict      						= summary_proj_to_labels
											a__	:							Tuple      						= summary_first_dropout
											a__	:							Dict      						= start_n_top
											a__	:							Any      						= end_n_top
											a__	:							Any      						= mask_token_id
											a__	:							Dict      						= lang_id

											if "n_words" in kwargs:
															a__	:							int      						= kwargs["n_words"]

											super().__init__(pad_token_id=__UpperCAmelCase ,					bos_token_id=__UpperCAmelCase ,					**__UpperCAmelCase				)





class 				_a						(       SCREAMING_SNAKE_CASE			):





							'''simple docstring'''

							@property
							def 		_A	(							self				):







											"""simple docstring"""



											if self.task == "multiple-choice":
															a__	:							Optional[Any]      						= {0: "batch", 1: "choice", 2: "sequence"}
											else:
															a__	:							int      						= {0: "batch", 1: "sequence"}
											return OrderedDict(
											    [
											        ("input_ids", dynamic_axis),
											        ("attention_mask", dynamic_axis),
											        ("token_type_ids", dynamic_axis),
											    ]				)







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase		       =      {
    """configuration_blip""": [
        """BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlipConfig""",
        """BlipTextConfig""",
        """BlipVisionConfig""",
    ],
    """processing_blip""": ["""BlipProcessor"""],
}

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


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase		       =      [
						    """BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """BlipModel""",
						    """BlipPreTrainedModel""",
						    """BlipForConditionalGeneration""",
						    """BlipForQuestionAnswering""",
						    """BlipVisionModel""",
						    """BlipTextModel""",
						    """BlipForImageTextRetrieval""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase		       =      [
						    """TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TFBlipModel""",
						    """TFBlipPreTrainedModel""",
						    """TFBlipForConditionalGeneration""",
						    """TFBlipForQuestionAnswering""",
						    """TFBlipVisionModel""",
						    """TFBlipTextModel""",
						    """TFBlipForImageTextRetrieval""",
						]

if TYPE_CHECKING:
						from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
						from .processing_blip import BlipProcessor

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_blip import BlipImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_blip import (
												    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BlipForConditionalGeneration,
												    BlipForImageTextRetrieval,
												    BlipForQuestionAnswering,
												    BlipModel,
												    BlipPreTrainedModel,
												    BlipTextModel,
												    BlipVisionModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_blip import (
												    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFBlipForConditionalGeneration,
												    TFBlipForImageTextRetrieval,
												    TFBlipForQuestionAnswering,
												    TFBlipModel,
												    TFBlipPreTrainedModel,
												    TFBlipTextModel,
												    TFBlipVisionModel,
												)

else:
						import sys

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


