





import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 		snake_case_   (							UpperCAmelCase_     ,     unittest.TestCase						):







	'''simple docstring'''
	__UpperCamelCase   =		LEDTokenizer
	__UpperCamelCase   =		LEDTokenizerFast
	__UpperCamelCase   =		True




	def    UpperCAmelCase			(						self							:     Dict   )       -> Optional[Any]:

			'''simple docstring'''




			super().setUp()
			__lowercase											=     [
			    'l',
			    'o',
			    'w',
			    'e',
			    'r',
			    's',
			    't',
			    'i',
			    'd',
			    'n',
			    '\u0120',
			    '\u0120l',
			    '\u0120n',
			    '\u0120lo',
			    '\u0120low',
			    'er',
			    '\u0120lowest',
			    '\u0120newer',
			    '\u0120wider',
			    '<unk>',
			]
			__lowercase											=     dict(zip(__lowerCamelCase					,      range(len(__lowerCamelCase   )   )   )   )
			__lowercase											=     ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
			__lowercase											=     {'unk_token': '<unk>'}

			__lowercase											=     os.path.join(self.tmpdirname					,      VOCAB_FILES_NAMES['vocab_file']   )
			__lowercase											=     os.path.join(self.tmpdirname					,      VOCAB_FILES_NAMES['merges_file']   )
			with open(self.vocab_file					,      'w'					,      encoding='utf-8'   ) as fp:
					fp.write(json.dumps(__lowerCamelCase   ) + '\n'   )
			with open(self.merges_file					,      'w'					,      encoding='utf-8'   ) as fp:
					fp.write('\n'.join(__lowerCamelCase   )   )




	def    UpperCAmelCase			(						self							:     int					,      **__lowerCamelCase							:     str   )       -> Optional[int]:

			'''simple docstring'''




			kwargs.update(self.special_tokens_map   )
			return self.tokenizer_class.from_pretrained(self.tmpdirname					,      **__lowerCamelCase   )




	def    UpperCAmelCase			(						self							:     int					,      **__lowerCamelCase							:     Dict   )       -> str:

			'''simple docstring'''




			kwargs.update(self.special_tokens_map   )
			return self.rust_tokenizer_class.from_pretrained(self.tmpdirname					,      **__lowerCamelCase   )




	def    UpperCAmelCase			(						self							:     Optional[Any]					,      __lowerCamelCase							:     Dict   )       -> Optional[int]:

			'''simple docstring'''




			return "lower newer", "lower newer"




	@cached_property
	def    UpperCAmelCase			(						self							:     Optional[Any]   )       -> List[str]:

			'''simple docstring'''




			return LEDTokenizer.from_pretrained('allenai/led-base-16384'   )




	@cached_property
	def    UpperCAmelCase			(						self							:     int   )       -> str:

			'''simple docstring'''




			return LEDTokenizerFast.from_pretrained('allenai/led-base-16384'   )




	@require_torch
	def    UpperCAmelCase			(						self							:     List[Any]   )       -> List[Any]:

			'''simple docstring'''




			__lowercase											=     ['A long paragraph for summarization.', 'Another paragraph for summarization.']
			__lowercase											=     [0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

			for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					__lowercase											=     tokenizer(__lowerCamelCase					,      max_length=len(__lowerCamelCase   )					,      padding=__lowerCamelCase					,      return_tensors='pt'   )
					self.assertIsInstance(__lowerCamelCase					,      __lowerCamelCase   )

					self.assertEqual((2, 9)					,      batch.input_ids.shape   )
					self.assertEqual((2, 9)					,      batch.attention_mask.shape   )
					__lowercase											=     batch.input_ids.tolist()[0]
					self.assertListEqual(__lowerCamelCase					,      __lowerCamelCase   )




	@require_torch
	def    UpperCAmelCase			(						self							:     Dict   )       -> Optional[Any]:

			'''simple docstring'''




			__lowercase											=     ['A long paragraph for summarization.', 'Another paragraph for summarization.']
			for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					__lowercase											=     tokenizer(__lowerCamelCase					,      padding=__lowerCamelCase					,      return_tensors='pt'   )
					self.assertIn('input_ids'					,      __lowerCamelCase   )
					self.assertIn('attention_mask'					,      __lowerCamelCase   )
					self.assertNotIn('labels'					,      __lowerCamelCase   )
					self.assertNotIn('decoder_attention_mask'					,      __lowerCamelCase   )




	@require_torch
	def    UpperCAmelCase			(						self							:     List[str]   )       -> List[str]:

			'''simple docstring'''




			__lowercase											=     [
			    'Summary of the text.',
			    'Another summary.',
			]
			for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					__lowercase											=     tokenizer(text_target=__lowerCamelCase					,      max_length=32					,      padding='max_length'					,      return_tensors='pt'   )
					self.assertEqual(32					,      targets['input_ids'].shape[1]   )




	@require_torch
	def    UpperCAmelCase			(						self							:     Union[str, Any]   )       -> List[str]:

			'''simple docstring'''




			for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					__lowercase											=     tokenizer(
					    ['I am a small frog' * 1_024, 'I am a small frog']					,      padding=__lowerCamelCase					,      truncation=__lowerCamelCase					,      return_tensors='pt'   )
					self.assertIsInstance(__lowerCamelCase					,      __lowerCamelCase   )
					self.assertEqual(batch.input_ids.shape					,      (2, 5_122)   )




	@require_torch
	def    UpperCAmelCase			(						self							:     Dict   )       -> Union[str, Any]:

			'''simple docstring'''




			__lowercase											=     ['A long paragraph for summarization.']
			__lowercase											=     [
			    'Summary of the text.',
			]
			for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					__lowercase											=     tokenizer(__lowerCamelCase					,      return_tensors='pt'   )
					__lowercase											=     tokenizer(text_target=__lowerCamelCase					,      return_tensors='pt'   )
					__lowercase											=     inputs['input_ids']
					__lowercase											=     targets['input_ids']
					self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()   )
					self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()   )
					self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()   )
					self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()   )




	@require_torch
	def    UpperCAmelCase			(						self							:     Optional[Any]   )       -> List[Any]:

			'''simple docstring'''




			for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					__lowercase											=     ['Summary of the text.', 'Another summary.']
					__lowercase											=     [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

					__lowercase											=     tokenizer(__lowerCamelCase					,      padding=__lowerCamelCase   )
					__lowercase											=     [[0] * len(__lowerCamelCase   ) for x in encoded_output['input_ids']]
					__lowercase											=     tokenizer.pad(__lowerCamelCase   )
					self.assertSequenceEqual(outputs['global_attention_mask']					,      __lowerCamelCase   )




	def    UpperCAmelCase			(						self							:     List[Any]   )       -> int:

			'''simple docstring'''




			pass






	def    UpperCAmelCase			(						self							:     int   )       -> Optional[int]:

			'''simple docstring'''




			for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
					with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
							__lowercase											=     self.rust_tokenizer_class.from_pretrained(__lowerCamelCase					,      **__lowerCamelCase   )
							__lowercase											=     self.tokenizer_class.from_pretrained(__lowerCamelCase					,      **__lowerCamelCase   )
							__lowercase											=     'A, <mask> AllenNLP sentence.'
							__lowercase											=     tokenizer_r.encode_plus(__lowerCamelCase					,      add_special_tokens=__lowerCamelCase					,      return_token_type_ids=__lowerCamelCase   )
							__lowercase											=     tokenizer_p.encode_plus(__lowerCamelCase					,      add_special_tokens=__lowerCamelCase					,      return_token_type_ids=__lowerCamelCase   )
							self.assertEqual(sum(tokens_r['token_type_ids']   )					,      sum(tokens_p['token_type_ids']   )   )
							self.assertEqual(
							    sum(tokens_r['attention_mask']   ) / len(tokens_r['attention_mask']   )					,      sum(tokens_p['attention_mask']   ) / len(tokens_p['attention_mask']   )					,      )

							__lowercase											=     tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']   )
							__lowercase											=     tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids']   )
							self.assertSequenceEqual(tokens_p['input_ids']					,      [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]   )
							self.assertSequenceEqual(tokens_r['input_ids']					,      [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]   )

							self.assertSequenceEqual(
							    __lowerCamelCase					,      ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']   )
							self.assertSequenceEqual(
							    __lowerCamelCase					,      ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']   )











from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

SCREAMING_SNAKE_CASE_   :      Optional[int]			=   TypeVar('''T''')



def  SCREAMING_SNAKE_CASE				(      snake_case							)		->    int:
		return (position - 1) // 2



def  SCREAMING_SNAKE_CASE				(      snake_case							)		->    int:
		return (2 * position) + 1



def  SCREAMING_SNAKE_CASE				(      snake_case							)		->    int:
		return (2 * position) + 2

class 		snake_case_   (							Generic[T]						):







	'''simple docstring'''




	def __init__(						self							:     Any   )       -> None:

			'''simple docstring'''




			__lowercase											=     []
			__lowercase											=     {}
			__lowercase											=     0




	def __len__(						self							:     Optional[Any]   )       -> int:

			'''simple docstring'''




			return self.elements




	def __repr__(						self							:     Optional[Any]   )       -> str:

			'''simple docstring'''




			return str(self.heap   )




	def    UpperCAmelCase			(						self							:     Union[str, Any]   )       -> bool:

			'''simple docstring'''




			return self.elements == 0




	def    UpperCAmelCase			(						self							:     str					,      __lowerCamelCase							:     T					,      __lowerCamelCase							:     int   )       -> None:

			'''simple docstring'''




			self.heap.append((elem, weight)   )
			__lowercase											=     self.elements
			self.elements += 1
			self._bubble_up(__lowerCamelCase   )




	def    UpperCAmelCase			(						self							:     Dict   )       -> T:

			'''simple docstring'''




			if self.elements > 1:
					self._swap_nodes(0					,      self.elements - 1   )
			__lowercase						,      __lowercase											=     self.heap.pop()
			del self.position_map[elem]
			self.elements -= 1
			if self.elements > 0:
					__lowercase						,      __lowercase											=     self.heap[0]
					self._bubble_down(__lowerCamelCase   )
			return elem




	def    UpperCAmelCase			(						self							:     int					,      __lowerCamelCase							:     T					,      __lowerCamelCase							:     int   )       -> None:

			'''simple docstring'''




			__lowercase											=     self.position_map[elem]
			__lowercase											=     (elem, weight)
			if position > 0:
					__lowercase											=     get_parent_position(__lowerCamelCase   )
					__lowercase						,      __lowercase											=     self.heap[parent_position]
					if parent_weight > weight:
							self._bubble_up(__lowerCamelCase   )
					else:
							self._bubble_down(__lowerCamelCase   )
			else:
					self._bubble_down(__lowerCamelCase   )




	def    UpperCAmelCase			(						self							:     Tuple					,      __lowerCamelCase							:     T   )       -> None:

			'''simple docstring'''




			__lowercase											=     self.position_map[elem]
			if curr_pos == 0:
					return None
			__lowercase											=     get_parent_position(__lowerCamelCase   )
			__lowercase						,      __lowercase											=     self.heap[curr_pos]
			__lowercase						,      __lowercase											=     self.heap[parent_position]
			if parent_weight > weight:
					self._swap_nodes(__lowerCamelCase					,      __lowerCamelCase   )
					return self._bubble_up(__lowerCamelCase   )
			return None




	def    UpperCAmelCase			(						self							:     List[str]					,      __lowerCamelCase							:     T   )       -> None:

			'''simple docstring'''




			__lowercase											=     self.position_map[elem]
			__lowercase						,      __lowercase											=     self.heap[curr_pos]
			__lowercase											=     get_child_left_position(__lowerCamelCase   )
			__lowercase											=     get_child_right_position(__lowerCamelCase   )
			if child_left_position < self.elements and child_right_position < self.elements:
					__lowercase						,      __lowercase											=     self.heap[child_left_position]
					__lowercase						,      __lowercase											=     self.heap[child_right_position]
					if child_right_weight < child_left_weight and child_right_weight < weight:
							self._swap_nodes(__lowerCamelCase					,      __lowerCamelCase   )
							return self._bubble_down(__lowerCamelCase   )
			if child_left_position < self.elements:
					__lowercase						,      __lowercase											=     self.heap[child_left_position]
					if child_left_weight < weight:
							self._swap_nodes(__lowerCamelCase					,      __lowerCamelCase   )
							return self._bubble_down(__lowerCamelCase   )
			else:
					return None
			if child_right_position < self.elements:
					__lowercase						,      __lowercase											=     self.heap[child_right_position]
					if child_right_weight < weight:
							self._swap_nodes(__lowerCamelCase					,      __lowerCamelCase   )
							return self._bubble_down(__lowerCamelCase   )
			return None






	def    UpperCAmelCase			(						self							:     Optional[int]					,      __lowerCamelCase							:     int					,      __lowerCamelCase							:     int   )       -> None:

			'''simple docstring'''




			__lowercase											=     self.heap[nodea_pos][0]
			__lowercase											=     self.heap[nodea_pos][0]
			__lowercase						,      __lowercase											=     (
			    self.heap[nodea_pos],
			    self.heap[nodea_pos],
			)
			__lowercase											=     nodea_pos
			__lowercase											=     nodea_pos





class 		snake_case_   (							Generic[T]						):







	'''simple docstring'''




	def __init__(						self							:     Optional[Any]   )       -> None:

			'''simple docstring'''




			__lowercase											=     {}
			__lowercase											=     0




	def __repr__(						self							:     Union[str, Any]   )       -> str:

			'''simple docstring'''




			return str(self.connections   )




	def __len__(						self							:     int   )       -> int:

			'''simple docstring'''




			return self.nodes




	def    UpperCAmelCase			(						self							:     Optional[int]					,      __lowerCamelCase							:     T   )       -> None:

			'''simple docstring'''




			if node not in self.connections:
					__lowercase											=     {}
					self.nodes += 1






	def    UpperCAmelCase			(						self							:     List[Any]					,      __lowerCamelCase							:     T					,      __lowerCamelCase							:     T					,      __lowerCamelCase							:     int   )       -> None:

			'''simple docstring'''




			self.add_node(__lowerCamelCase   )
			self.add_node(__lowerCamelCase   )
			__lowercase											=     weight
			__lowercase											=     weight





def  SCREAMING_SNAKE_CASE				(      snake_case						,   )		->    tuple[dict[T, int], dict[T, T | None]]:
		__lowercase											=     {node: maxsize for node in graph.connections}
		__lowercase											=     {node: None for node in graph.connections}

		__lowercase											=     MinPriorityQueue()
		for node, weight in dist.items():
				priority_queue.push(snake_case						,   snake_case							)

		if priority_queue.is_empty():
				return dist, parent

		# initialization
		__lowercase											=     priority_queue.extract_min()
		__lowercase											=     0
		for neighbour in graph.connections[node]:
				if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
						__lowercase											=     dist[node] + graph.connections[node][neighbour]
						priority_queue.update_key(snake_case						,   dist[neighbour]							)
						__lowercase											=     node

    # running prim's algorithm
		while not priority_queue.is_empty():
				__lowercase											=     priority_queue.extract_min()
				for neighbour in graph.connections[node]:
						if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
								__lowercase											=     dist[node] + graph.connections[node][neighbour]
								priority_queue.update_key(snake_case						,   dist[neighbour]							)
								__lowercase											=     node
		return dist, parent




