




"""simple docstring"""

import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class        lowercase      (    __UpperCAmelCase     ,	unittest.TestCase):
				__lowerCAmelCase    :    int         =   GPTaTokenizer
				__lowerCAmelCase    :    Any         =   GPTaTokenizerFast
				__lowerCAmelCase    :    List[Any]         =   True
				__lowerCAmelCase    :    Optional[Any]         =   {"""add_prefix_space""": True}
				__lowerCAmelCase    :    str         =   False







				def 					a_  (							self   :					List[Any]       ):



					"""simple docstring"""

					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					A_  :				int	   =		[
					    '''l''',
					    '''o''',
					    '''w''',
					    '''e''',
					    '''r''',
					    '''s''',
					    '''t''',
					    '''i''',
					    '''d''',
					    '''n''',
					    '''\u0120''',
					    '''\u0120l''',
					    '''\u0120n''',
					    '''\u0120lo''',
					    '''\u0120low''',
					    '''er''',
					    '''\u0120lowest''',
					    '''\u0120newer''',
					    '''\u0120wider''',
					    '''<unk>''',
					    '''<|endoftext|>''',
					]
					A_  :				Optional[int]	   =		dict(zip(_lowerCamelCase      ,     range(len(_lowerCamelCase       )       )       )       )
					A_  :				Tuple	   =		['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
					A_  :				Optional[Any]	   =		{'''unk_token''': '''<unk>'''}

					A_  :				Optional[Any]	   =		os.path.join(self.tmpdirname      ,     VOCAB_FILES_NAMES['''vocab_file''']       )
					A_  :				Dict	   =		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 					a_  (							self   :					str      ,     **_lowerCamelCase   :					str       ):



					"""simple docstring"""

					kwargs.update(self.special_tokens_map       )
					return GPTaTokenizer.from_pretrained(self.tmpdirname      ,     **_lowerCamelCase       )







				def 					a_  (							self   :					Any      ,     **_lowerCamelCase   :					str       ):



					"""simple docstring"""

					kwargs.update(self.special_tokens_map       )
					return GPTaTokenizerFast.from_pretrained(self.tmpdirname      ,     **_lowerCamelCase       )







				def 					a_  (							self   :					Tuple      ,     _lowerCamelCase   :					Any       ):



					"""simple docstring"""

					A_  :				Optional[Any]	   =		'''lower newer'''
					A_  :				List[str]	   =		'''lower newer'''
					return input_text, output_text







				def 					a_  (							self   :					List[str]       ):



					"""simple docstring"""

					A_  :				int	   =		GPTaTokenizer(self.vocab_file      ,     self.merges_file      ,     **self.special_tokens_map       )
					A_  :				int	   =		'''lower newer'''
					A_  :				List[Any]	   =		['''\u0120low''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
					A_  :				Union[str, Any]	   =		tokenizer.tokenize(_lowerCamelCase      ,     add_prefix_space=_lowerCamelCase       )
					self.assertListEqual(_lowerCamelCase      ,     _lowerCamelCase       )

					A_  :				int	   =		tokens + [tokenizer.unk_token]
					A_  :				Optional[Any]	   =		[14, 15, 10, 9, 3, 2, 15, 19]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase       )      ,     _lowerCamelCase       )







				def 					a_  (							self   :					Tuple       ):



					"""simple docstring"""

					if not self.test_rust_tokenizer:
						return

					A_  :				Optional[Any]	   =		self.get_tokenizer()
					A_  :				Optional[Any]	   =		self.get_rust_tokenizer(add_prefix_space=_lowerCamelCase       )

					A_  :				List[str]	   =		'''lower newer'''

					# Testing tokenization
					A_  :				Optional[int]	   =		tokenizer.tokenize(_lowerCamelCase      ,     add_prefix_space=_lowerCamelCase       )
					A_  :				List[Any]	   =		rust_tokenizer.tokenize(_lowerCamelCase       )
					self.assertListEqual(_lowerCamelCase      ,     _lowerCamelCase       )

					# Testing conversion to ids without special tokens
					A_  :				List[str]	   =		tokenizer.encode(_lowerCamelCase      ,     add_special_tokens=_lowerCamelCase      ,     add_prefix_space=_lowerCamelCase       )
					A_  :				Any	   =		rust_tokenizer.encode(_lowerCamelCase      ,     add_special_tokens=_lowerCamelCase       )
					self.assertListEqual(_lowerCamelCase      ,     _lowerCamelCase       )

					# Testing conversion to ids with special tokens
					A_  :				Optional[Any]	   =		self.get_rust_tokenizer(add_prefix_space=_lowerCamelCase       )
					A_  :				List[str]	   =		tokenizer.encode(_lowerCamelCase      ,     add_prefix_space=_lowerCamelCase       )
					A_  :				str	   =		rust_tokenizer.encode(_lowerCamelCase       )
					self.assertListEqual(_lowerCamelCase      ,     _lowerCamelCase       )

					# Testing the unknown token
					A_  :				Optional[int]	   =		tokens + [rust_tokenizer.unk_token]
					A_  :				List[Any]	   =		[14, 15, 10, 9, 3, 2, 15, 19]
					self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(_lowerCamelCase       )      ,     _lowerCamelCase       )







				def 					a_  (							self   :					Dict      ,     *_lowerCamelCase   :					List[str]      ,     **_lowerCamelCase   :					Optional[int]       ):



					"""simple docstring"""

					pass







				def 					a_  (							self   :					int      ,     _lowerCamelCase   :					List[str]=15       ):



					"""simple docstring"""

					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""       ):
							A_  :				List[str]	   =		self.rust_tokenizer_class.from_pretrained(_lowerCamelCase      ,     **_lowerCamelCase       )

							# Simple input
							A_  :				Optional[Any]	   =		'''This is a simple input'''
							A_  :				Optional[Any]	   =		['''This is a simple input 1''', '''This is a simple input 2''']
							A_  :				Optional[int]	   =		('''This is a simple input''', '''This is a pair''')
							A_  :				Union[str, Any]	   =		[
							    ('''This is a simple input 1''', '''This is a simple input 2'''),
							    ('''This is a simple pair 1''', '''This is a simple pair 2'''),
							]

							# Simple input tests
							self.assertRaises(_lowerCamelCase      ,     tokenizer_r.encode      ,     _lowerCamelCase      ,     max_length=_lowerCamelCase      ,     padding='''max_length'''       )

							# Simple input
							self.assertRaises(_lowerCamelCase      ,     tokenizer_r.encode_plus      ,     _lowerCamelCase      ,     max_length=_lowerCamelCase      ,     padding='''max_length'''       )

							# Simple input
							self.assertRaises(
							    _lowerCamelCase      ,     tokenizer_r.batch_encode_plus      ,     _lowerCamelCase      ,     max_length=_lowerCamelCase      ,     padding='''max_length'''      ,     )

							# Pair input
							self.assertRaises(_lowerCamelCase      ,     tokenizer_r.encode      ,     _lowerCamelCase      ,     max_length=_lowerCamelCase      ,     padding='''max_length'''       )

							# Pair input
							self.assertRaises(_lowerCamelCase      ,     tokenizer_r.encode_plus      ,     _lowerCamelCase      ,     max_length=_lowerCamelCase      ,     padding='''max_length'''       )

							# Pair input
							self.assertRaises(
							    _lowerCamelCase      ,     tokenizer_r.batch_encode_plus      ,     _lowerCamelCase      ,     max_length=_lowerCamelCase      ,     padding='''max_length'''      ,     )







				def 					a_  (							self   :					Union[str, Any]       ):



					"""simple docstring"""

					A_  :				Dict	   =		GPTaTokenizer.from_pretrained(self.tmpdirname      ,     pad_token='''<pad>'''       )

					# Simple input
					A_  :				Optional[int]	   =		'''This is a simple input'''
					A_  :				Optional[int]	   =		['''This is a simple input looooooooong''', '''This is a simple input''']
					A_  :				Optional[int]	   =		('''This is a simple input''', '''This is a pair''')
					A_  :				int	   =		[
					    ('''This is a simple input loooooong''', '''This is a simple input'''),
					    ('''This is a simple pair loooooong''', '''This is a simple pair'''),
					]

					A_  :				List[Any]	   =		tokenizer.pad_token_id

					A_  :				List[Any]	   =		tokenizer(_lowerCamelCase      ,     padding='''max_length'''      ,     max_length=30      ,     return_tensors='''np'''       )
					A_  :				Optional[int]	   =		tokenizer(_lowerCamelCase      ,     padding=_lowerCamelCase      ,     truncate=_lowerCamelCase      ,     return_tensors='''np'''       )
					A_  :				Optional[int]	   =		tokenizer(*_lowerCamelCase      ,     padding='''max_length'''      ,     max_length=60      ,     return_tensors='''np'''       )
					A_  :				List[Any]	   =		tokenizer(_lowerCamelCase      ,     padding=_lowerCamelCase      ,     truncate=_lowerCamelCase      ,     return_tensors='''np'''       )

					# s
					# test single string max_length padding
					self.assertEqual(out_s['''input_ids'''].shape[-1]      ,     30       )
					self.assertTrue(pad_token_id in out_s['''input_ids''']       )
					self.assertTrue(0 in out_s['''attention_mask''']       )

					# s2
					# test automatic padding
					self.assertEqual(out_sa['''input_ids'''].shape[-1]      ,     33       )
					# long slice doesn't have padding
					self.assertFalse(pad_token_id in out_sa['''input_ids'''][0]       )
					self.assertFalse(0 in out_sa['''attention_mask'''][0]       )
					# short slice does have padding
					self.assertTrue(pad_token_id in out_sa['''input_ids'''][1]       )
					self.assertTrue(0 in out_sa['''attention_mask'''][1]       )

					# p
					# test single pair max_length padding
					self.assertEqual(out_p['''input_ids'''].shape[-1]      ,     60       )
					self.assertTrue(pad_token_id in out_p['''input_ids''']       )
					self.assertTrue(0 in out_p['''attention_mask''']       )

					# p2
					# test automatic padding pair
					self.assertEqual(out_pa['''input_ids'''].shape[-1]      ,     52       )
					# long slice pair doesn't have padding
					self.assertFalse(pad_token_id in out_pa['''input_ids'''][0]       )
					self.assertFalse(0 in out_pa['''attention_mask'''][0]       )
					# short slice pair does have padding
					self.assertTrue(pad_token_id in out_pa['''input_ids'''][1]       )
					self.assertTrue(0 in out_pa['''attention_mask'''][1]       )







				def 					a_  (							self   :					Any       ):



					"""simple docstring"""

					A_  :				Optional[Any]	   =		'''$$$'''
					A_  :				Tuple	   =		GPTaTokenizer.from_pretrained(self.tmpdirname      ,     bos_token=_lowerCamelCase      ,     add_bos_token=_lowerCamelCase       )

					A_  :				Any	   =		'''This is a simple input'''
					A_  :				Optional[Any]	   =		['''This is a simple input 1''', '''This is a simple input 2''']

					A_  :				Dict	   =		tokenizer.bos_token_id

					A_  :				Optional[Any]	   =		tokenizer(_lowerCamelCase       )
					A_  :				str	   =		tokenizer(_lowerCamelCase       )

					self.assertEqual(out_s.input_ids[0]      ,     _lowerCamelCase       )
					self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids       )       )

					A_  :				Dict	   =		tokenizer.decode(out_s.input_ids       )
					A_  :				Any	   =		tokenizer.batch_decode(out_sa.input_ids       )

					self.assertEqual(decode_s.split()[0]      ,     _lowerCamelCase       )
					self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa       )       )







				def 					a_  (							self   :					Any       ):



					"""simple docstring"""

					pass







				def 					a_  (							self   :					Optional[int]       ):



					"""simple docstring"""

					A_  :				List[str]	   =		[self.get_tokenizer(do_lower_case=_lowerCamelCase      ,     add_bos_token=_lowerCamelCase       )]
					for tokenizer in tokenizers:
						with self.subTest(F"""{tokenizer.__class__.__name__}"""       ):
							A_  :				Union[str, Any]	   =		'''Encode this.'''
							A_  :				Dict	   =		'''This one too please.'''
							A_  :				Optional[int]	   =		tokenizer.encode(_lowerCamelCase      ,     add_special_tokens=_lowerCamelCase       )
							encoded_sequence += tokenizer.encode(_lowerCamelCase      ,     add_special_tokens=_lowerCamelCase       )
							A_  :				Tuple	   =		tokenizer.encode_plus(
							    _lowerCamelCase      ,     _lowerCamelCase      ,     add_special_tokens=_lowerCamelCase      ,     return_special_tokens_mask=_lowerCamelCase      ,     )
							A_  :				List[Any]	   =		encoded_sequence_dict['''input_ids''']
							A_  :				Optional[Any]	   =		encoded_sequence_dict['''special_tokens_mask''']
							self.assertEqual(len(_lowerCamelCase       )      ,     len(_lowerCamelCase       )       )

							A_  :				Optional[int]	   =		[
							    (x if not special_tokens_mask[i] else None) for i, x in enumerate(_lowerCamelCase       )
							]
							A_  :				Optional[Any]	   =		[x for x in filtered_sequence if x is not None]
							self.assertEqual(_lowerCamelCase      ,     _lowerCamelCase       )

@require_tokenizers
class        lowercase      (    unittest.TestCase):







				def 					a_  (							self   :					int       ):



					"""simple docstring"""

					A_  :				Union[str, Any]	   =		AutoTokenizer.from_pretrained('''facebook/opt-350m'''      ,     from_slow=_lowerCamelCase       )
					A_  :				Tuple	   =		'''A photo of a cat'''

					A_  :				str	   =		tokenizer.encode(
					    _lowerCamelCase      ,     )
					self.assertEqual(_lowerCamelCase      ,     [2, 2_50, 13_45, 9, 10, 47_58]       )
					tokenizer.save_pretrained('''test_opt'''       )

					A_  :				str	   =		AutoTokenizer.from_pretrained('''./test_opt'''       )
					A_  :				Any	   =		tokenizer.encode(
					    _lowerCamelCase      ,     )
					self.assertEqual(_lowerCamelCase      ,     [2, 2_50, 13_45, 9, 10, 47_58]       )







				def 					a_  (							self   :					Tuple       ):



					"""simple docstring"""

					A_  :				int	   =		AutoTokenizer.from_pretrained('''facebook/opt-350m'''      ,     use_slow=_lowerCamelCase       )
					A_  :				Optional[Any]	   =		'''A photo of a cat'''

					A_  :				Any	   =		tokenizer.encode(
					    _lowerCamelCase      ,     )
					# Same as above
					self.assertEqual(_lowerCamelCase      ,     [2, 2_50, 13_45, 9, 10, 47_58]       )







				@unittest.skip('''This test is failing because of a bug in the fast tokenizer'''       )
				def 					a_  (							self   :					Optional[int]       ):



					"""simple docstring"""

					A_  :				Any	   =		AutoTokenizer.from_pretrained('''facebook/opt-350m'''      ,     from_slow=_lowerCamelCase       )

					A_  :				Union[str, Any]	   =		'''bos'''
					A_  :				Optional[int]	   =		tokenizer.get_vocab()['''bos''']

					A_  :				Union[str, Any]	   =		'''A photo of a cat'''
					A_  :				List[str]	   =		tokenizer.encode(
					    _lowerCamelCase      ,     )
					# We changed the bos token
					self.assertEqual(_lowerCamelCase      ,     [3_19_57, 2_50, 13_45, 9, 10, 47_58]       )
					tokenizer.save_pretrained('''./tok'''       )
					A_  :				Optional[Any]	   =		AutoTokenizer.from_pretrained('''./tok'''       )
					self.assertTrue(tokenizer.is_fast       )
					A_  :				Union[str, Any]	   =		tokenizer.encode(
					    _lowerCamelCase      ,     )
					self.assertEqual(_lowerCamelCase      ,     [3_19_57, 2_50, 13_45, 9, 10, 47_58]       )











"""simple docstring"""

from queue import PriorityQueue
from typing import Any

import numpy as np

def 		lowercase_      (		_UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      ):




	"""simple docstring"""






	for nxt, d in graph[v]:
		if nxt in visited_forward:
			continue
		A_  :				Tuple	   =		cst_fwd.get(_UpperCAmelCase  ,      np.inf	)
		A_  :				Any	   =		cst_fwd[v] + d
		if new_cost_f < old_cost_f:
			queue.put((new_cost_f, nxt)	)
			A_  :				Tuple	   =		new_cost_f
			A_  :				Dict	   =		v
		if nxt in visited_backward:
			if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
				A_  :				Optional[Any]	   =		cst_fwd[v] + d + cst_bwd[nxt]
	return shortest_distance

def 		lowercase_      (		_UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase	):




	"""simple docstring"""






	A_  :				Tuple	   =		-1

	A_  :				Any	   =		set()
	A_  :				Tuple	   =		set()
	A_  :				Optional[int]	   =		{source: 0}
	A_  :				Dict	   =		{destination: 0}
	A_  :				Any	   =		{source: None}
	A_  :				Optional[Any]	   =		{destination: None}
	A_  :				PriorityQueue[Any]	   =		PriorityQueue()
	A_  :				PriorityQueue[Any]	   =		PriorityQueue()

	A_  :				Union[str, Any]	   =		np.inf

	queue_forward.put((0, source)	)
	queue_backward.put((0, destination)	)

	if source == destination:
		return 0

	while not queue_forward.empty() and not queue_backward.empty():
		A_   , A_  :				Union[str, Any]	   =		queue_forward.get()
		visited_forward.add(_UpperCAmelCase	)

		A_   , A_  :				Optional[int]	   =		queue_backward.get()
		visited_backward.add(_UpperCAmelCase	)

		A_  :				Any	   =		pass_and_relaxation(
		    _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      )

		A_  :				Dict	   =		pass_and_relaxation(
		    _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      )

		if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
			break

	if shortest_distance != np.inf:
		A_  :				Optional[Any]	   =		shortest_distance
	return shortest_path_distance


_lowerCamelCase  :			Optional[Any]        =       {
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
_lowerCamelCase  :			Any        =       {
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
		import doctest

		doctest.testmod()





