


"""simple docstring"""


import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING


A     :   int			    =			logging.get_logger(__name__)

A     :   Tuple			    =			{
    "Salesforce/instruct-blip-flan-t5": "https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json",
}
class   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							__UpperCAmelCase						:    Any				      ="""instructblip_vision_model"""

							def __init__(     self    ,   __a=14_08    ,   __a=61_44    ,   __a=39    ,   __a=16    ,   __a=2_24    ,   __a=14    ,   __a="gelu"    ,   __a=1e-6    ,   __a=0.0    ,   __a=1e-1_0    ,   __a=True    ,   **__a    ,   ):
										super().__init__(**__a	)

										__lowerCAmelCase				    =			hidden_size
										__lowerCAmelCase				    =			intermediate_size
										__lowerCAmelCase				    =			num_hidden_layers
										__lowerCAmelCase				    =			num_attention_heads
										__lowerCAmelCase				    =			patch_size
										__lowerCAmelCase				    =			image_size
										__lowerCAmelCase				    =			initializer_range
										__lowerCAmelCase				    =			attention_dropout
										__lowerCAmelCase				    =			layer_norm_eps
										__lowerCAmelCase				    =			hidden_act
										__lowerCAmelCase				    =			qkv_bias



							@classmethod
							def 			snake_case				(     cls    ,   __a    ,   **__a	):
										cls._set_token_in_kwargs(__a	)

										__lowerCAmelCase    ,	__lowerCAmelCase				    =			cls.get_config_dict(__a    ,   **__a	)

										# get the vision config dict if we are loading from InstructBlipConfig
										if config_dict.get("model_type"	) == "instructblip":
													__lowerCAmelCase				    =			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   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							__UpperCAmelCase						:    str				      ="""instructblip_qformer"""

							def __init__(     self    ,   __a=3_05_22    ,   __a=7_68    ,   __a=12    ,   __a=12    ,   __a=30_72    ,   __a="gelu"    ,   __a=0.1    ,   __a=0.1    ,   __a=5_12    ,   __a=0.0_2    ,   __a=1e-1_2    ,   __a=0    ,   __a="absolute"    ,   __a=2    ,   __a=14_08    ,   **__a    ,   ):
										super().__init__(pad_token_id=__a    ,   **__a	)

										__lowerCAmelCase				    =			vocab_size
										__lowerCAmelCase				    =			hidden_size
										__lowerCAmelCase				    =			num_hidden_layers
										__lowerCAmelCase				    =			num_attention_heads
										__lowerCAmelCase				    =			hidden_act
										__lowerCAmelCase				    =			intermediate_size
										__lowerCAmelCase				    =			hidden_dropout_prob
										__lowerCAmelCase				    =			attention_probs_dropout_prob
										__lowerCAmelCase				    =			max_position_embeddings
										__lowerCAmelCase				    =			initializer_range
										__lowerCAmelCase				    =			layer_norm_eps
										__lowerCAmelCase				    =			position_embedding_type
										__lowerCAmelCase				    =			cross_attention_frequency
										__lowerCAmelCase				    =			encoder_hidden_size



							@classmethod
							def 			snake_case				(     cls    ,   __a    ,   **__a	):
										cls._set_token_in_kwargs(__a	)

										__lowerCAmelCase    ,	__lowerCAmelCase				    =			cls.get_config_dict(__a    ,   **__a	)

										# get the qformer config dict if we are loading from InstructBlipConfig
										if config_dict.get("model_type"	) == "instructblip":
													__lowerCAmelCase				    =			config_dict["qformer_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   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							__UpperCAmelCase						:    Dict				      ="""instructblip"""
							__UpperCAmelCase						:    Tuple				      =True

							def __init__(     self    ,   __a=None    ,   __a=None    ,   __a=None    ,   __a=32    ,   **__a	):
										super().__init__(**__a	)

										if vision_config is None:
													__lowerCAmelCase				    =			{}
													logger.info("vision_config is None. initializing the InstructBlipVisionConfig with default values."	)

										if qformer_config is None:
													__lowerCAmelCase				    =			{}
													logger.info("qformer_config is None. Initializing the InstructBlipQFormerConfig with default values."	)

										if text_config is None:
													__lowerCAmelCase				    =			{}
													logger.info("text_config is None. Initializing the text config with default values (`OPTConfig`)."	)

										__lowerCAmelCase				    =			InstructBlipVisionConfig(**__a	)
										__lowerCAmelCase				    =			InstructBlipQFormerConfig(**__a	)
										__lowerCAmelCase				    =			text_config["model_type"] if "model_type" in text_config else "opt"
										__lowerCAmelCase				    =			CONFIG_MAPPING[text_model_type](**__a	)

										__lowerCAmelCase				    =			self.text_config.tie_word_embeddings
										__lowerCAmelCase				    =			self.text_config.is_encoder_decoder

										__lowerCAmelCase				    =			num_query_tokens
										__lowerCAmelCase				    =			self.vision_config.hidden_size
										__lowerCAmelCase				    =			self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
										__lowerCAmelCase				    =			1.0
										__lowerCAmelCase				    =			0.0_2

							@classmethod
							def 			snake_case				(     cls    ,   __a    ,   __a    ,   __a    ,   **__a    ,   ):
										return cls(
										    vision_config=vision_config.to_dict()    ,   qformer_config=qformer_config.to_dict()    ,   text_config=text_config.to_dict()    ,   **__a    ,   )



							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			copy.deepcopy(self.__dict__	)
										__lowerCAmelCase				    =			self.vision_config.to_dict()
										__lowerCAmelCase				    =			self.qformer_config.to_dict()
										__lowerCAmelCase				    =			self.text_config.to_dict()
										__lowerCAmelCase				    =			self.__class__.model_type
										return output








"""simple docstring"""


from __future__ import annotations


def _lowerCamelCase	(		_UpperCamelCase = 4      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			abs(_UpperCamelCase      ) or 4
			return [[1 + x + y * row_size for x in range(_UpperCamelCase      )] for y in range(_UpperCamelCase      )]


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			return reverse_row(transpose(_UpperCamelCase      )      )
			# OR.. transpose(reverse_column(matrix))


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			return reverse_row(reverse_column(_UpperCamelCase      )      )
			# OR.. reverse_column(reverse_row(matrix))


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			return reverse_column(transpose(_UpperCamelCase      )      )
			# OR.. transpose(reverse_row(matrix))


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			[list(_UpperCamelCase      ) for x in zip(*_UpperCamelCase      )]
			return matrix


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			matrix[::-1]
			return matrix


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			[x[::-1] for x in matrix]
			return matrix


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			for i in matrix:
						print(*_UpperCamelCase      )


if __name__ == "__main__":
	A     :   Dict			    =			make_matrix()
	print("\norigin:\n")
	print_matrix(matrix)
	print("\nrotate 90 counterclockwise:\n")
	print_matrix(rotate_aa(matrix))

	A     :   List[str]			    =			make_matrix()
	print("\norigin:\n")
	print_matrix(matrix)
	print("\nrotate 180:\n")
	print_matrix(rotate_aaa(matrix))

	A     :   str			    =			make_matrix()
	print("\norigin:\n")
	print_matrix(matrix)
	print("\nrotate 270 counterclockwise:\n")
	print_matrix(rotate_aaa(matrix))




