



"""simple docstring"""






import unicodedata
from dataclasses import dataclass
from typing import Optional, Union

import numpy as np

from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase


def      _lowercase							(    __snake_case   ,__snake_case   ,__snake_case   ,__snake_case      )		->  str:
			if isinstance(__snake_case   ,__snake_case      ):
						__lowerCAmelCase :    str				=			np.full((len(__snake_case      ), sequence_length, 2)   ,__snake_case      )
			else:
						__lowerCAmelCase :    int				=			np.full((len(__snake_case      ), sequence_length)   ,__snake_case      )

			for i, tensor in enumerate(__snake_case      ):
						if padding_side == "right":
									if isinstance(__snake_case   ,__snake_case      ):
												__lowerCAmelCase :    List[Any]				=			tensor[:sequence_length]
									else:
												__lowerCAmelCase :    str				=			tensor[:sequence_length]
						else:
									if isinstance(__snake_case   ,__snake_case      ):
												__lowerCAmelCase :    Tuple				=			tensor[:sequence_length]
									else:
												__lowerCAmelCase :    str				=			tensor[:sequence_length]

			return out_tensor.tolist()


def      _lowercase							(    __snake_case      )		->  Tuple:
			__lowerCAmelCase :    List[str]				=			ord(__snake_case      )
			if (cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126):
						return True
			__lowerCAmelCase :    Optional[Any]				=			unicodedata.category(__snake_case      )
			if cat.startswith("P"      ):
						return True
			return False





@dataclass
class      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      42
	SCREAMING_SNAKE_CASE        =      True
	SCREAMING_SNAKE_CASE        =      None
	SCREAMING_SNAKE_CASE        =      None
	SCREAMING_SNAKE_CASE        =      -1_0_0
	SCREAMING_SNAKE_CASE        =      "pt"

	def 				_SCREAMING_SNAKE_CASE  (	self:						List[Any]			,     _SCREAMING_SNAKE_CASE:						List[Any])							->			Optional[int]:

				"""simple docstring"""

				import torch

				__lowerCAmelCase :    int				=			"label" if "label" in features[0].keys() else "labels"
				__lowerCAmelCase :    List[Any]				=			[feature[label_name] for feature in features] if label_name in features[0].keys() else None
				__lowerCAmelCase :    Optional[Any]				=			self.tokenizer.pad(
				    _SCREAMING_SNAKE_CASE			,     padding=self.padding			,     max_length=self.max_length			,     pad_to_multiple_of=self.pad_to_multiple_of			,     return_tensors="pt" if labels is None else None			,     )

				if labels is None:
							return batch

				__lowerCAmelCase :    List[str]				=			torch.tensor(batch["entity_ids"]).shape[1]
				__lowerCAmelCase :    List[Any]				=			self.tokenizer.padding_side
				if padding_side == "right":
							__lowerCAmelCase :    Optional[int]				=			[
							    list(_SCREAMING_SNAKE_CASE) + [self.label_pad_token_id] * (sequence_length - len(_SCREAMING_SNAKE_CASE)) for label in labels
							]
				else:
							__lowerCAmelCase :    str				=			[
							    [self.label_pad_token_id] * (sequence_length - len(_SCREAMING_SNAKE_CASE)) + list(_SCREAMING_SNAKE_CASE) for label in labels
							]

				__lowerCAmelCase :    Any				=			[feature["ner_tags"] for feature in features]
				__lowerCAmelCase :    Optional[int]				=			padding_tensor(_SCREAMING_SNAKE_CASE			,     -1			,     _SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    List[Any]				=			[feature["original_entity_spans"] for feature in features]
				__lowerCAmelCase :    Any				=			padding_tensor(_SCREAMING_SNAKE_CASE			,     (-1, -1)			,     _SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    Optional[Any]				=			{k: torch.tensor(_SCREAMING_SNAKE_CASE			,     dtype=torch.intaa) for k, v in batch.items()}

				return batch




"""simple docstring"""






# Function to print upper half of diamond (pyramid)


def      _lowercase							(    __snake_case      )		->  Dict:
			for i in range(0   ,__snake_case      ):
						for _ in range(0   ,n - i - 1      ):  # printing spaces
									print(" "   ,end=""      )
						for _ in range(0   ,i + 1      ):  # printing stars
									print("* "   ,end=""      )
						print()


def      _lowercase							(    __snake_case      )		->  Tuple:
			for i in range(__snake_case   ,0   ,-1      ):
						for _ in range(__snake_case   ,0   ,-1      ):  # printing stars
									print("* "   ,end=""      )
						print()
						for _ in range(n - i + 1   ,0   ,-1      ):  # printing spaces
									print(" "   ,end=""      )


def      _lowercase							(    __snake_case      )		->  Any:
			if n <= 0:
						print("       ...       ....        nothing printing :("      )
						return
			floyd(__snake_case      )  # upper half
			reverse_floyd(__snake_case      )  # lower half


if __name__ == "__main__":
	print(R'| /\ | |- |  |-  |--| |\  /| |-')
	print(R'|/  \| |- |_ |_  |__| | \/ | |_')
	__snake_case				:  Tuple =       1
	while K:
		__snake_case				:  List[str] =       int(input('enter the number and , and see the magic : '))
		print()
		pretty_print(user_number)
		__snake_case				:  Optional[Any] =       int(input('press 0 to exit... and 1 to continue...'))

	print('Good Bye...')