

import copy
import os
from typing import Union

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


__A     :					Optional[Any]     = logging.get_logger(__name__)

__A     :					Tuple     = {
    "BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json",
    # See all AltCLIP models at https://huggingface.co/models?filter=altclip
}


class        _SCREAMING_SNAKE_CASE	(   _UpperCAmelCase):
						_UpperCamelCase:List[Any]     =						"altclip_text_model"







						def __init__(       self			,		_SCREAMING_SNAKE_CASE=25_0002			,		_SCREAMING_SNAKE_CASE=1024			,		_SCREAMING_SNAKE_CASE=24			,		_SCREAMING_SNAKE_CASE=16			,		_SCREAMING_SNAKE_CASE=4096			,		_SCREAMING_SNAKE_CASE="gelu"			,		_SCREAMING_SNAKE_CASE=0.1			,		_SCREAMING_SNAKE_CASE=0.1			,		_SCREAMING_SNAKE_CASE=514			,		_SCREAMING_SNAKE_CASE=1			,		_SCREAMING_SNAKE_CASE=0.0_2			,		_SCREAMING_SNAKE_CASE=0.0_2			,		_SCREAMING_SNAKE_CASE=1E-05			,		_SCREAMING_SNAKE_CASE=1			,		_SCREAMING_SNAKE_CASE=0			,		_SCREAMING_SNAKE_CASE=2			,		_SCREAMING_SNAKE_CASE="absolute"			,		_SCREAMING_SNAKE_CASE=True			,		_SCREAMING_SNAKE_CASE=768			,		**_SCREAMING_SNAKE_CASE			,		)->				Any:
													super().__init__(pad_token_id=lowercase_			,		bos_token_id=lowercase_			,		eos_token_id=lowercase_			,		**lowercase_				)

													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_				     =type_vocab_size
													lowerCamelCase_				     =initializer_range
													lowerCamelCase_				     =initializer_factor
													lowerCamelCase_				     =layer_norm_eps
													lowerCamelCase_				     =position_embedding_type
													lowerCamelCase_				     =use_cache
													lowerCamelCase_				     =project_dim


class        _SCREAMING_SNAKE_CASE	(   _UpperCAmelCase):
						_UpperCamelCase:List[str]     =						"altclip_vision_model"







						def __init__(       self			,		_SCREAMING_SNAKE_CASE=768			,		_SCREAMING_SNAKE_CASE=3072			,		_SCREAMING_SNAKE_CASE=512			,		_SCREAMING_SNAKE_CASE=12			,		_SCREAMING_SNAKE_CASE=12			,		_SCREAMING_SNAKE_CASE=3			,		_SCREAMING_SNAKE_CASE=224			,		_SCREAMING_SNAKE_CASE=32			,		_SCREAMING_SNAKE_CASE="quick_gelu"			,		_SCREAMING_SNAKE_CASE=1E-5			,		_SCREAMING_SNAKE_CASE=0.0			,		_SCREAMING_SNAKE_CASE=0.0_2			,		_SCREAMING_SNAKE_CASE=1.0			,		**_SCREAMING_SNAKE_CASE			,		)->				str:
													super().__init__(**lowercase_				)

													lowerCamelCase_				     =hidden_size
													lowerCamelCase_				     =intermediate_size
													lowerCamelCase_				     =projection_dim
													lowerCamelCase_				     =num_hidden_layers
													lowerCamelCase_				     =num_attention_heads
													lowerCamelCase_				     =num_channels
													lowerCamelCase_				     =patch_size
													lowerCamelCase_				     =image_size
													lowerCamelCase_				     =initializer_range
													lowerCamelCase_				     =initializer_factor
													lowerCamelCase_				     =attention_dropout
													lowerCamelCase_				     =layer_norm_eps
													lowerCamelCase_				     =hidden_act







						@classmethod
						def     _snake_case							(       cls			,		_SCREAMING_SNAKE_CASE			,		**_SCREAMING_SNAKE_CASE				)->				Union[str, Any]:
													cls._set_token_in_kwargs(lowercase_				)

													lowerCamelCase_				     =cls.get_config_dict(lowercase_			,		**lowercase_				)

													# get the vision config dict if we are loading from AltCLIPConfig
													if config_dict.get("""model_type"""				) == "altclip":
																				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(lowercase_			,		**lowercase_				)


class        _SCREAMING_SNAKE_CASE	(   _UpperCAmelCase):
						_UpperCamelCase:str     =						"altclip"
						_UpperCamelCase:Tuple     =						True







						def __init__(       self			,		_SCREAMING_SNAKE_CASE=None			,		_SCREAMING_SNAKE_CASE=None			,		_SCREAMING_SNAKE_CASE=768			,		_SCREAMING_SNAKE_CASE=2.6_5_9_2			,		**_SCREAMING_SNAKE_CASE				)->				Tuple:
													# If `_config_dict` exist, we use them for the backward compatibility.
													# We pop out these 2 attributes before calling `super().__init__` to avoid them being saved (which causes a lot
													# of confusion!).
													lowerCamelCase_				     =kwargs.pop("""text_config_dict"""			,		lowercase_				)
													lowerCamelCase_				     =kwargs.pop("""vision_config_dict"""			,		lowercase_				)

													super().__init__(**lowercase_				)

													# 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:
																											lowerCamelCase_				     ={}

																				# This is the complete result when using `text_config_dict`.
																				lowerCamelCase_				     =AltCLIPTextConfig(**lowercase_				).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:
																																									lowerCamelCase_				     =(
																																									    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:
																																									lowerCamelCase_				     =(
																																									    f'`text_config_dict` is provided which will be used to initialize `AltCLIPTextConfig`. The '
																																									    f'value `text_config["{key}"]` will be overriden.'
																																									)
																																		logger.warning(lowercase_				)

            # 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:
																											lowerCamelCase_				     ={}

																				# This is the complete result when using `vision_config_dict`.
																				lowerCamelCase_				     =AltCLIPVisionConfig(**lowercase_				).to_dict()
																				# convert keys to string instead of integer
																				if "id2label" in _vision_config_dict:
																											lowerCamelCase_				     ={
																											    str(lowercase_				): 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:
																																									lowerCamelCase_				     =(
																																									    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:
																																									lowerCamelCase_				     =(
																																									    f'`vision_config_dict` is provided which will be used to initialize `AltCLIPVisionConfig`. '
																																									    f'The value `vision_config["{key}"]` will be overriden.'
																																									)
																																		logger.warning(lowercase_				)

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

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

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

													lowerCamelCase_				     =AltCLIPTextConfig(**lowercase_				)
													lowerCamelCase_				     =AltCLIPVisionConfig(**lowercase_				)

													lowerCamelCase_				     =projection_dim
													lowerCamelCase_				     =logit_scale_init_value
													lowerCamelCase_				     =1.0







						@classmethod
						def     _snake_case							(       cls			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		**_SCREAMING_SNAKE_CASE				)->				Union[str, Any]:
													return cls(text_config=text_config.to_dict()			,		vision_config=vision_config.to_dict()			,		**lowercase_				)







						def     _snake_case							(       self				)->				str:
													lowerCamelCase_				     =copy.deepcopy(self.__dict__				)
													lowerCamelCase_				     =self.text_config.to_dict()
													lowerCamelCase_				     =self.vision_config.to_dict()
													lowerCamelCase_				     =self.__class__.model_type
													return output

'''simple docstring'''




import os




def 							lowerCamelCase	(      UpperCAmelCase__       :					str = "input.txt" )			->      int:

							with open(os.path.join(os.path.dirname(UpperCAmelCase__ )      ,      UpperCAmelCase__ ) ) as input_file:
														lowercase_					:			str										=       [
														    [int(UpperCAmelCase__ ) for element in line.split(""",""" )]
														    for line in input_file.readlines()
														]

							lowercase_					:			Optional[Any]										=       len(UpperCAmelCase__ )
							lowercase_					:			Any										=       len(matrix[0] )

							lowercase_					:			Union[str, Any]										=       [[-1 for _ in range(UpperCAmelCase__ )] for _ in range(UpperCAmelCase__ )]
							for i in range(UpperCAmelCase__ ):
														lowercase_					:			int										=       matrix[i][0]

							for j in range(1      ,      UpperCAmelCase__ ):
														for i in range(UpperCAmelCase__ ):
																					lowercase_					:			Union[str, Any]										=       minimal_path_sums[i][j - 1] + matrix[i][j]

														for i in range(1      ,      UpperCAmelCase__ ):
																					lowercase_					:			Tuple										=       min(
																					    minimal_path_sums[i][j]      ,      minimal_path_sums[i - 1][j] + matrix[i][j] )

														for i in range(rows - 2      ,      -1      ,      -1 ):
																					lowercase_					:			Dict										=       min(
																					    minimal_path_sums[i][j]      ,      minimal_path_sums[i + 1][j] + matrix[i][j] )

							return min(minimal_path_sums_row[-1] for minimal_path_sums_row in minimal_path_sums )


if __name__ == "__main__":
						print(f"""{solution() = }""")





