


import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__			:      Union[str, Any]								=logging.get_logger(__name__)

lowerCAmelCase__			:      List[Any]								={
    'BAAI/AltCLIP': 'https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json',
    # See all AltCLIP models at https://huggingface.co/models?filter=altclip
}







class 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							_UpperCAmelCase      =						"""altclip_text_model"""






							def __init__(      self			,						lowerCAmelCase__=2_5_0_0_0_2			,						lowerCAmelCase__=1_0_2_4			,						lowerCAmelCase__=2_4			,						lowerCAmelCase__=1_6			,						lowerCAmelCase__=4_0_9_6			,						lowerCAmelCase__="gelu"			,						lowerCAmelCase__=0.1			,						lowerCAmelCase__=0.1			,						lowerCAmelCase__=5_1_4			,						lowerCAmelCase__=1			,						lowerCAmelCase__=0.02			,						lowerCAmelCase__=0.02			,						lowerCAmelCase__=1E-05			,						lowerCAmelCase__=1			,						lowerCAmelCase__=0			,						lowerCAmelCase__=2			,						lowerCAmelCase__="absolute"			,						lowerCAmelCase__=True			,						lowerCAmelCase__=7_6_8			,						**lowerCAmelCase__			,						):





										"""simple docstring"""




										super().__init__(pad_token_id=lowerCAmelCase__			,						bos_token_id=lowerCAmelCase__			,						eos_token_id=lowerCAmelCase__			,						**lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Any					=					vocab_size
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					hidden_size
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					num_hidden_layers
										SCREAMING_SNAKE_CASE_		:     Tuple					=					num_attention_heads
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					hidden_act
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					intermediate_size
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					hidden_dropout_prob
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE_		:     Any					=					max_position_embeddings
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					type_vocab_size
										SCREAMING_SNAKE_CASE_		:     Any					=					initializer_range
										SCREAMING_SNAKE_CASE_		:     int					=					initializer_factor
										SCREAMING_SNAKE_CASE_		:     List[str]					=					layer_norm_eps
										SCREAMING_SNAKE_CASE_		:     int					=					position_embedding_type
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					use_cache
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					project_dim







class 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							_UpperCAmelCase      =						"""altclip_vision_model"""






							def __init__(      self			,						lowerCAmelCase__=7_6_8			,						lowerCAmelCase__=3_0_7_2			,						lowerCAmelCase__=5_1_2			,						lowerCAmelCase__=1_2			,						lowerCAmelCase__=1_2			,						lowerCAmelCase__=3			,						lowerCAmelCase__=2_2_4			,						lowerCAmelCase__=3_2			,						lowerCAmelCase__="quick_gelu"			,						lowerCAmelCase__=1E-5			,						lowerCAmelCase__=0.0			,						lowerCAmelCase__=0.02			,						lowerCAmelCase__=1.0			,						**lowerCAmelCase__			,						):





										"""simple docstring"""




										super().__init__(**lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Tuple					=					hidden_size
										SCREAMING_SNAKE_CASE_		:     Any					=					intermediate_size
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					projection_dim
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					num_hidden_layers
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					num_attention_heads
										SCREAMING_SNAKE_CASE_		:     Tuple					=					num_channels
										SCREAMING_SNAKE_CASE_		:     int					=					patch_size
										SCREAMING_SNAKE_CASE_		:     Dict					=					image_size
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					initializer_range
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					initializer_factor
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					attention_dropout
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					layer_norm_eps
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					hidden_act






							@classmethod
							def 					UpperCamelCase__     (      cls			,						lowerCAmelCase__			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										cls._set_token_in_kwargs(lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		:     Tuple					=					cls.get_config_dict(lowerCAmelCase__			,						**lowerCAmelCase__       )

										# get the vision config dict if we are loading from AltCLIPConfig
										if config_dict.get('model_type'       ) == "altclip":
													SCREAMING_SNAKE_CASE_		:     Any					=					config_dict['vision_config']

										if "model_type" in config_dict and hasattr(cls			,						'model_type'       ) and config_dict["model_type"] != cls.model_type:
													logger.warning(
													    F'''You are using a model of type {config_dict['model_type']} to instantiate a model of type '''
													    F'''{cls.model_type}. This is not supported for all configurations of models and can yield errors.'''       )

										return cls.from_dict(lowerCAmelCase__			,						**lowerCAmelCase__       )







class 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							_UpperCAmelCase      =						"""altclip"""
							_UpperCAmelCase      =						True






							def __init__(      self			,						lowerCAmelCase__=None			,						lowerCAmelCase__=None			,						lowerCAmelCase__=7_6_8			,						lowerCAmelCase__=2.6_592			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     List[str]					=					kwargs.pop('text_config_dict'			,						lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     str					=					kwargs.pop('vision_config_dict'			,						lowerCAmelCase__       )

										super().__init__(**lowerCAmelCase__       )

										# Instead of simply assigning `[text|vision]_config_dict` to `[text|vision]_config`, we use the values in
										# `[text|vision]_config_dict` to update the values in `[text|vision]_config`. The values should be same in most
										# cases, but we don't want to break anything regarding `_config_dict` that existed before commit `8827e1b2`.
										if text_config_dict is not None:
													if text_config is None:
																SCREAMING_SNAKE_CASE_		:     Tuple					=					{}

													# This is the complete result when using `text_config_dict`.
													SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					AltCLIPTextConfig(**lowerCAmelCase__       ).to_dict()

													# Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
													for key, value in _text_config_dict.items():
																if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
																			# If specified in `text_config_dict`
																			if key in text_config_dict:
																						SCREAMING_SNAKE_CASE_		:     int					=					(
																						    F'''`{key}` is found in both `text_config_dict` and `text_config` but with different values. '''
																						    F'''The value `text_config_dict["{key}"]` will be used instead.'''
																						)
																			# If inferred from default argument values (just to be super careful)
																			else:
																						SCREAMING_SNAKE_CASE_		:     Tuple					=					(
																						    F'''`text_config_dict` is provided which will be used to initialize `AltCLIPTextConfig`. The '''
																						    F'''value `text_config["{key}"]` will be overriden.'''
																						)
																			logger.warning(lowerCAmelCase__       )

            # Update all values in `text_config` with the ones in `_text_config_dict`.
													text_config.update(_text_config_dict       )

										if vision_config_dict is not None:
													if vision_config is None:
																SCREAMING_SNAKE_CASE_		:     int					=					{}

													# This is the complete result when using `vision_config_dict`.
													SCREAMING_SNAKE_CASE_		:     Dict					=					AltCLIPVisionConfig(**lowerCAmelCase__       ).to_dict()
													# convert keys to string instead of integer
													if "id2label" in _vision_config_dict:
																SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					{
																    str(lowerCAmelCase__       ): value for key, value in _vision_config_dict['id2label'].items()
																}

													# Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
													for key, value in _vision_config_dict.items():
																if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
																			# If specified in `vision_config_dict`
																			if key in vision_config_dict:
																						SCREAMING_SNAKE_CASE_		:     List[str]					=					(
																						    F'''`{key}` is found in both `vision_config_dict` and `vision_config` but with different '''
																						    F'''values. The value `vision_config_dict["{key}"]` will be used instead.'''
																						)
																			# If inferred from default argument values (just to be super careful)
																			else:
																						SCREAMING_SNAKE_CASE_		:     str					=					(
																						    F'''`vision_config_dict` is provided which will be used to initialize `AltCLIPVisionConfig`. '''
																						    F'''The value `vision_config["{key}"]` will be overriden.'''
																						)
																			logger.warning(lowerCAmelCase__       )

            # Update all values in `vision_config` with the ones in `_vision_config_dict`.
													vision_config.update(_vision_config_dict       )

										if text_config is None:
													SCREAMING_SNAKE_CASE_		:     Any					=					{}
													logger.info('`text_config` is `None`. Initializing the `AltCLIPTextConfig` with default values.'       )

										if vision_config is None:
													SCREAMING_SNAKE_CASE_		:     Dict					=					{}
													logger.info('`vision_config` is `None`. initializing the `AltCLIPVisionConfig` with default values.'       )

										SCREAMING_SNAKE_CASE_		:     str					=					AltCLIPTextConfig(**lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     str					=					AltCLIPVisionConfig(**lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					projection_dim
										SCREAMING_SNAKE_CASE_		:     List[str]					=					logit_scale_init_value
										SCREAMING_SNAKE_CASE_		:     List[str]					=					1.0






							@classmethod
							def 					UpperCamelCase__     (      cls			,						lowerCAmelCase__			,						lowerCAmelCase__			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										return cls(text_config=text_config.to_dict()			,						vision_config=vision_config.to_dict()			,						**lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					copy.deepcopy(self.__dict__       )
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.text_config.to_dict()
										SCREAMING_SNAKE_CASE_		:     Tuple					=					self.vision_config.to_dict()
										SCREAMING_SNAKE_CASE_		:     Dict					=					self.__class__.model_type
										return output











from typing import TYPE_CHECKING

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


__magic_name__  :  Any					=       {
    """configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LayoutLMv2Config"""],
    """processing_layoutlmv2""": ["""LayoutLMv2Processor"""],
    """tokenization_layoutlmv2""": ["""LayoutLMv2Tokenizer"""],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  List[str]					=       ["""LayoutLMv2TokenizerFast"""]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  Any					=       ["""LayoutLMv2FeatureExtractor"""]
      __magic_name__  :  Any					=       ["""LayoutLMv2ImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  Any					=       [
          """LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """LayoutLMv2ForQuestionAnswering""",
          """LayoutLMv2ForSequenceClassification""",
          """LayoutLMv2ForTokenClassification""",
          """LayoutLMv2Layer""",
          """LayoutLMv2Model""",
          """LayoutLMv2PreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
      from .processing_layoutlmva import LayoutLMvaProcessor
      from .tokenization_layoutlmva import LayoutLMvaTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_layoutlmva import (
                LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
                LayoutLMvaForQuestionAnswering,
                LayoutLMvaForSequenceClassification,
                LayoutLMvaForTokenClassification,
                LayoutLMvaLayer,
                LayoutLMvaModel,
                LayoutLMvaPreTrainedModel,
            )
else:
      import sys

      __magic_name__  :  Union[str, Any]					=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

