



'''simple docstring'''






import copy
import os
from typing import Union

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


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

A_							: List[str]						 =	{
    "google/pix2struct-textcaps-base": (
        "https://huggingface.co/google/pix2struct-textcaps-base/resolve/main/config.json"
    ),
}



class 							lowercase       (  _lowerCamelCase				):


 """simple docstring"""


 UpperCAmelCase							=  """pix2struct_text_model"""
 UpperCAmelCase							=  ["""past_key_values"""]
 UpperCAmelCase							=  {
     """hidden_size""": """hidden_size""",
     """num_attention_heads""": """num_heads""",
     """num_hidden_layers""": """num_layers""",
 }







 def __init__(							self  ,a_=50_244  ,a_=768  ,a_=64  ,a_=2_048  ,a_=12  ,a_=12  ,a_=32  ,a_=128  ,a_=0.1  ,a_=1E-6  ,a_=1.0  ,a_="gelu_new"  ,a_=0  ,a_=False  ,a_=0  ,a_=1  ,a_=False  ,a_=True  ,**a_  ,)		->   Tuple:
        _UpperCAmelCase  :						List[Any]			     = vocab_size
        _UpperCAmelCase  :						List[str]			     = hidden_size
        _UpperCAmelCase  :						Tuple			     = d_kv
        _UpperCAmelCase  :						List[Any]			     = d_ff
        _UpperCAmelCase  :						str			     = num_layers
        _UpperCAmelCase  :						Tuple			     = num_heads
        _UpperCAmelCase  :						int			     = relative_attention_num_buckets
        _UpperCAmelCase  :						Optional[int]			     = relative_attention_max_distance
        _UpperCAmelCase  :						List[str]			     = dropout_rate
        _UpperCAmelCase  :						List[Any]			     = layer_norm_epsilon
        _UpperCAmelCase  :						Union[str, Any]			     = initializer_factor
        _UpperCAmelCase  :						List[str]			     = use_cache

        _UpperCAmelCase  :						str			     = eos_token_id
        _UpperCAmelCase  :						str			     = decoder_start_token_id

        # for backwards compatibility
        _UpperCAmelCase  :						Dict			     = dense_act_fn

        super().__init__(
            pad_token_id=a_  ,eos_token_id=a_  ,decoder_start_token_id=a_  ,tie_word_embeddings=a_  ,is_decoder=a_  ,**a_  ,)







 @classmethod
 def _snake_case (							cls  ,a_  ,**a_							)		->   List[Any]:
        cls._set_token_in_kwargs(a_							)

        _UpperCAmelCase     ,_UpperCAmelCase  :						List[str]			     = cls.get_config_dict(a_  ,**a_							)

        # get the text config dict if we are loading from Pix2StructConfig
        if config_dict.get("""model_type"""							) == "pix2struct":
               _UpperCAmelCase  :						int			     = config_dict["""text_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(a_  ,**a_							)







class 							lowercase       (  _lowerCamelCase				):


 """simple docstring"""


 UpperCAmelCase							=  """pix2struct_vision_model"""







 def __init__(							self  ,a_=768  ,a_=768  ,a_=2_048  ,a_=64  ,a_=12  ,a_=12  ,a_="gelu_new"  ,a_=1E-6  ,a_=0.0  ,a_=0.0  ,a_=1E-1_0  ,a_=1.0  ,a_=4_096  ,a_=32  ,a_=128  ,**a_  ,)		->   Dict:
        super().__init__(**a_							)

        _UpperCAmelCase  :						Union[str, Any]			     = hidden_size
        _UpperCAmelCase  :						Dict			     = patch_embed_hidden_size
        _UpperCAmelCase  :						List[Any]			     = d_ff
        _UpperCAmelCase  :						List[Any]			     = dropout_rate
        _UpperCAmelCase  :						int			     = num_hidden_layers
        _UpperCAmelCase  :						Tuple			     = num_attention_heads
        _UpperCAmelCase  :						str			     = initializer_range
        _UpperCAmelCase  :						Union[str, Any]			     = initializer_factor
        _UpperCAmelCase  :						List[Any]			     = attention_dropout
        _UpperCAmelCase  :						Optional[Any]			     = layer_norm_eps
        _UpperCAmelCase  :						int			     = dense_act_fn
        _UpperCAmelCase  :						List[str]			     = seq_len
        _UpperCAmelCase  :						int			     = relative_attention_num_buckets
        _UpperCAmelCase  :						Any			     = relative_attention_max_distance
        _UpperCAmelCase  :						Union[str, Any]			     = d_kv







 @classmethod
 def _snake_case (							cls  ,a_  ,**a_							)		->   List[Any]:
        cls._set_token_in_kwargs(a_							)

        _UpperCAmelCase     ,_UpperCAmelCase  :						Union[str, Any]			     = cls.get_config_dict(a_  ,**a_							)

        # get the vision config dict if we are loading from Pix2StructConfig
        if config_dict.get("""model_type"""							) == "pix2struct":
               _UpperCAmelCase  :						List[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(a_  ,**a_							)







class 							lowercase       (  _lowerCamelCase				):


 """simple docstring"""


 UpperCAmelCase							=  """pix2struct"""
 UpperCAmelCase							=  True







 def __init__(							self  ,a_=None  ,a_=None  ,a_=1.0  ,a_=0.02  ,a_=False  ,a_=False  ,a_=True  ,**a_  ,)		->   str:
        super().__init__(tie_word_embeddings=a_  ,is_encoder_decoder=a_  ,**a_							)

        if text_config is None:
               _UpperCAmelCase  :						Tuple			     = {}
               logger.info("""text_config is None. Initializing the Pix2StructTextConfig with default values."""							)

        if vision_config is None:
               _UpperCAmelCase  :						List[Any]			     = {}
               logger.info("""vision_config is None. Initializing the Pix2StructVisionConfig with default values."""							)

        _UpperCAmelCase  :						List[Any]			     = PixaStructTextConfig(**a_							)
        _UpperCAmelCase  :						str			     = PixaStructVisionConfig(**a_							)

        _UpperCAmelCase  :						List[Any]			     = self.text_config.decoder_start_token_id
        _UpperCAmelCase  :						str			     = self.text_config.pad_token_id
        _UpperCAmelCase  :						Union[str, Any]			     = self.text_config.eos_token_id

        _UpperCAmelCase  :						Dict			     = initializer_factor
        _UpperCAmelCase  :						Dict			     = initializer_range

        _UpperCAmelCase  :						Optional[int]			     = self.initializer_range
        _UpperCAmelCase  :						Any			     = self.initializer_range

        _UpperCAmelCase  :						Optional[Any]			     = is_vqa







 @classmethod
 def _snake_case (							cls  ,a_  ,a_  ,**a_							)		->   Tuple:
        return cls(text_config=text_config.to_dict()  ,vision_config=vision_config.to_dict()  ,**a_							)







 def _snake_case (							self							)		->   Dict:
        _UpperCAmelCase  :						Tuple			     = copy.deepcopy(self.__dict__							)
        _UpperCAmelCase  :						Dict			     = self.text_config.to_dict()
        _UpperCAmelCase  :						Optional[int]			     = self.vision_config.to_dict()
        _UpperCAmelCase  :						Optional[Any]			     = self.__class__.model_type
        return output









def 		__A		(	__lowerCamelCase							,			__lowerCamelCase    )      ->       str:
	if not isinstance(__lowerCamelCase							,			__lowerCamelCase    ):
		raise ValueError("""iterations must be defined as integers"""    )
	if not isinstance(__lowerCamelCase							,			__lowerCamelCase    ) or not number >= 1:
		raise ValueError(
		    """starting number must be
                         and integer and be more than 0"""    )
	if not iterations >= 1:
		raise ValueError("""Iterations must be done more than 0 times to play FizzBuzz"""    )

	a										=							""""""
	while number <= iterations:
		if number % 3 == 0:
			out += "Fizz"
		if number % 5 == 0:
			out += "Buzz"
		if 0 not in (number % 3, number % 5):
			out += str(__lowerCamelCase    )

		# print(out)
		number += 1
		out += " "
	return out


if __name__ == "__main__":
		import doctest

		doctest.testmod()

