



import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
						_snake_case		=  "pt"
elif is_tf_available():
						_snake_case		=  "tf"
else:
						_snake_case		=  "jax"



class   UpperCAmelCase_    (       a   ,					unittest.TestCase):
							lowerCamelCase__   			=		ByTaTokenizer
							lowerCamelCase__   			=		False







							def    snake_case__      (   self):

														'''simple docstring'''

														super().setUp()
														_lowerCAmelCase     :							Union[str, Any]    =    ByTaTokenizer()
														tokenizer.save_pretrained(self.tmpdirname)







							@cached_property
							def    snake_case__      (   self):

														'''simple docstring'''

														return ByTaTokenizer.from_pretrained("google/byt5-small")







							def    snake_case__      (   self,			**__a):

														'''simple docstring'''

														return self.tokenizer_class.from_pretrained(self.tmpdirname,			**__a)







							def    snake_case__      (   self,			__a,			__a=False,			__a=20,			__a=5):

														'''simple docstring'''

														_lowerCAmelCase     :							List[str]    =    []
														for i in range(len(__a)):
																					try:
																												_lowerCAmelCase     :							Tuple    =    tokenizer.decode([i],			clean_up_tokenization_spaces=__a)
																					except UnicodeDecodeError:
																												pass
																					toks.append((i, tok))

														_lowerCAmelCase     :							Tuple    =    list(filter(lambda __a: re.match(R"^[ a-zA-Z]+$",			t[1]),			__a))
														_lowerCAmelCase     :							str    =    list(filter(lambda __a: [t[0]] == tokenizer.encode(t[1],			add_special_tokens=__a),			__a))
														if max_length is not None and len(__a) > max_length:
																					_lowerCAmelCase     :							int    =    toks[:max_length]
														if min_length is not None and len(__a) < min_length and len(__a) > 0:
																					while len(__a) < min_length:
																												_lowerCAmelCase     :							Dict    =    toks + toks
        # toks_str = [t[1] for t in toks]
														_lowerCAmelCase     :							int    =    [t[0] for t in toks]

														# Ensure consistency
														_lowerCAmelCase     :							int    =    tokenizer.decode(__a,			clean_up_tokenization_spaces=__a)
														if " " not in output_txt and len(__a) > 1:
																					_lowerCAmelCase     :							Union[str, Any]    =    (
																					    tokenizer.decode([toks_ids[0]],			clean_up_tokenization_spaces=__a)
																					    + " "
																					    + tokenizer.decode(toks_ids[1:],			clean_up_tokenization_spaces=__a)
																					)
														if with_prefix_space:
																					_lowerCAmelCase     :							Optional[int]    =    " " + output_txt
														_lowerCAmelCase     :							Tuple    =    tokenizer.encode(__a,			add_special_tokens=__a)
														return output_txt, output_ids







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Any    =    self.ta_base_tokenizer
														_lowerCAmelCase     :							Any    =    tokenizer(["hi</s>", "I went to the gym</s>", "</s>"])
														_lowerCAmelCase     :							int    =    tokenizer(["hi", "I went to the gym", ""])
														self.assertListEqual(batch_with_eos_added["input_ids"],			batch_without_eos_added["input_ids"])







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							int    =    self.ta_base_tokenizer
														_lowerCAmelCase     :							int    =    "Unicode €."
														_lowerCAmelCase     :							Dict    =    tokenizer(__a)
														_lowerCAmelCase     :							Union[str, Any]    =    [88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
														self.assertEqual(encoded["input_ids"],			__a)

														# decoding
														_lowerCAmelCase     :							str    =    tokenizer.decode(__a)
														self.assertEqual(__a,			"Unicode €.</s>")

														_lowerCAmelCase     :							Dict    =    tokenizer("e è é ê ë")
														_lowerCAmelCase     :							Tuple    =    [104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
														self.assertEqual(encoded["input_ids"],			__a)
														# decoding
														_lowerCAmelCase     :							Optional[Any]    =    tokenizer.decode(__a)
														self.assertEqual(__a,			"e è é ê ë</s>")

														# encode/decode, but with `encode` instead of `__call__`
														self.assertEqual(tokenizer.decode(tokenizer.encode("e è é ê ë")),			"e è é ê ë</s>")







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							List[Any]    =    self.ta_base_tokenizer
														_lowerCAmelCase     :							Tuple    =    ["A long paragraph for summarization.", "Another paragraph for summarization."]
														# fmt: off
														_lowerCAmelCase     :							List[str]    =    [68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
														# fmt: on
														_lowerCAmelCase     :							Tuple    =    tokenizer(__a,			padding=__a,			return_tensors=__a)
														self.assertIsInstance(__a,			__a)

														if FRAMEWORK != "jax":
																					_lowerCAmelCase     :							int    =    list(batch.input_ids.numpy()[0])
														else:
																					_lowerCAmelCase     :							Tuple    =    list(batch.input_ids.tolist()[0])

														self.assertListEqual(__a,			__a)

														self.assertEqual((2, 37),			batch.input_ids.shape)
														self.assertEqual((2, 37),			batch.attention_mask.shape)







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							List[str]    =    self.ta_base_tokenizer
														_lowerCAmelCase     :							List[str]    =    ["A long paragraph for summarization.", "Another paragraph for summarization."]
														_lowerCAmelCase     :							int    =    tokenizer(__a,			padding=__a,			return_tensors=__a)
														# check if input_ids are returned and no decoder_input_ids
														self.assertIn("input_ids",			__a)
														self.assertIn("attention_mask",			__a)
														self.assertNotIn("decoder_input_ids",			__a)
														self.assertNotIn("decoder_attention_mask",			__a)







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Dict    =    self.ta_base_tokenizer
														_lowerCAmelCase     :							List[str]    =    [
														    "Summary of the text.",
														    "Another summary.",
														]
														_lowerCAmelCase     :							Optional[int]    =    tokenizer(
														    text_target=__a,			max_length=32,			padding="max_length",			truncation=__a,			return_tensors=__a)
														self.assertEqual(32,			targets["input_ids"].shape[1])







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							List[str]    =    self.ta_base_tokenizer
														_lowerCAmelCase     :							str    =    ["A long paragraph for summarization. </s>"]
														_lowerCAmelCase     :							List[str]    =    ["Summary of the text. </s>"]
														# fmt: off
														_lowerCAmelCase     :							Dict    =    [68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
														_lowerCAmelCase     :							List[Any]    =    [86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
														# fmt: on

														_lowerCAmelCase     :							Tuple    =    tokenizer(__a,			text_target=__a)

														self.assertEqual(__a,			batch["input_ids"][0])
														self.assertEqual(__a,			batch["labels"][0])







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							str    =    self.get_tokenizers()
														for tokenizer in tokenizers:
																					with self.subTest(f"{tokenizer.__class__.__name__}"):
																												self.assertNotEqual(tokenizer.model_max_length,			42)

        # Now let's start the test
														_lowerCAmelCase     :							int    =    self.get_tokenizers()
														for tokenizer in tokenizers:
																					with self.subTest(f"{tokenizer.__class__.__name__}"):
																												# Isolate this from the other tests because we save additional tokens/etc
																												_lowerCAmelCase     :							Any    =    tempfile.mkdtemp()

																												_lowerCAmelCase     :							Tuple    =    " He is very happy, UNwant\u00E9d,running"
																												_lowerCAmelCase     :							int    =    tokenizer.encode(__a,			add_special_tokens=__a)
																												tokenizer.save_pretrained(__a)

																												_lowerCAmelCase     :							Union[str, Any]    =    tokenizer.__class__.from_pretrained(__a)
																												_lowerCAmelCase     :							Optional[int]    =    after_tokenizer.encode(__a,			add_special_tokens=__a)
																												self.assertListEqual(__a,			__a)

																												shutil.rmtree(__a)

														_lowerCAmelCase     :							Optional[int]    =    self.get_tokenizers(model_max_length=42)
														for tokenizer in tokenizers:
																					with self.subTest(f"{tokenizer.__class__.__name__}"):
																												# Isolate this from the other tests because we save additional tokens/etc
																												_lowerCAmelCase     :							str    =    tempfile.mkdtemp()

																												_lowerCAmelCase     :							Union[str, Any]    =    " He is very happy, UNwant\u00E9d,running"
																												tokenizer.add_tokens(["bim", "bambam"])
																												_lowerCAmelCase     :							str    =    tokenizer.additional_special_tokens
																												additional_special_tokens.append("new_additional_special_token")
																												tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens})
																												_lowerCAmelCase     :							Optional[int]    =    tokenizer.encode(__a,			add_special_tokens=__a)
																												tokenizer.save_pretrained(__a)

																												_lowerCAmelCase     :							Optional[Any]    =    tokenizer.__class__.from_pretrained(__a)
																												_lowerCAmelCase     :							str    =    after_tokenizer.encode(__a,			add_special_tokens=__a)
																												self.assertListEqual(__a,			__a)
																												self.assertIn("new_additional_special_token",			after_tokenizer.additional_special_tokens)
																												self.assertEqual(after_tokenizer.model_max_length,			42)

																												_lowerCAmelCase     :							Any    =    tokenizer.__class__.from_pretrained(__a,			model_max_length=43)
																												self.assertEqual(tokenizer.model_max_length,			43)

																												shutil.rmtree(__a)







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Optional[int]    =    []
														if self.test_slow_tokenizer:
																					tokenizer_list.append((self.tokenizer_class, self.get_tokenizer()))

														if self.test_rust_tokenizer:
																					tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer()))

														for tokenizer_class, tokenizer_utils in tokenizer_list:
																					with tempfile.TemporaryDirectory() as tmp_dir:
																												tokenizer_utils.save_pretrained(__a)

																												with open(os.path.join(__a,			"special_tokens_map.json"),			encoding="utf-8") as json_file:
																																			_lowerCAmelCase     :							Union[str, Any]    =    json.load(__a)

																												with open(os.path.join(__a,			"tokenizer_config.json"),			encoding="utf-8") as json_file:
																																			_lowerCAmelCase     :							Union[str, Any]    =    json.load(__a)

																												_lowerCAmelCase     :							str    =    [f"<extra_id_{i}>" for i in range(125)]

																												_lowerCAmelCase     :							Dict    =    added_tokens_extra_ids + [
																												    "an_additional_special_token"
																												]
																												_lowerCAmelCase     :							Optional[Any]    =    added_tokens_extra_ids + [
																												    "an_additional_special_token"
																												]

																												with open(os.path.join(__a,			"special_tokens_map.json"),			"w",			encoding="utf-8") as outfile:
																																			json.dump(__a,			__a)
																												with open(os.path.join(__a,			"tokenizer_config.json"),			"w",			encoding="utf-8") as outfile:
																																			json.dump(__a,			__a)

																												# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
																												# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
																												# "special_tokens_map.json" files
																												_lowerCAmelCase     :							Dict    =    tokenizer_class.from_pretrained(
																												    __a,			)
																												self.assertIn(
																												    "an_additional_special_token",			tokenizer_without_change_in_init.additional_special_tokens)
																												# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
																												self.assertEqual(
																												    ["an_additional_special_token"],			tokenizer_without_change_in_init.convert_ids_to_tokens(
																												        tokenizer_without_change_in_init.convert_tokens_to_ids(["an_additional_special_token"])),			)

																												# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																												_lowerCAmelCase     :							List[Any]    =    added_tokens_extra_ids + [AddedToken("a_new_additional_special_token",			lstrip=__a)]
																												_lowerCAmelCase     :							Optional[Any]    =    tokenizer_class.from_pretrained(
																												    __a,			additional_special_tokens=__a,			)

																												self.assertIn("a_new_additional_special_token",			tokenizer.additional_special_tokens)
																												self.assertEqual(
																												    ["a_new_additional_special_token"],			tokenizer.convert_ids_to_tokens(
																												        tokenizer.convert_tokens_to_ids(["a_new_additional_special_token"])),			)







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							List[Any]    =    []
														if self.test_slow_tokenizer:
																					tokenizer_list.append((self.tokenizer_class, self.get_tokenizer()))

														if self.test_rust_tokenizer:
																					tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer()))

														for tokenizer_class, tokenizer_utils in tokenizer_list:
																					with tempfile.TemporaryDirectory() as tmp_dir:
																												tokenizer_utils.save_pretrained(__a)

																												_lowerCAmelCase     :							List[Any]    =    tokenizer_class.from_pretrained(__a)

																												self.assertTrue(tokenizer.decode([255]) == "")







							def    snake_case__      (   self):

														'''simple docstring'''

														pass







							def    snake_case__      (   self):

														'''simple docstring'''

														pass







							def    snake_case__      (   self):

														'''simple docstring'''

														pass







							def    snake_case__      (   self):

														'''simple docstring'''

														pass







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							int    =    self.get_tokenizers(fast=__a,			do_lower_case=__a)
														for tokenizer in tokenizers:
																					with self.subTest(f"{tokenizer.__class__.__name__}"):
																												_lowerCAmelCase     :							Tuple    =    ["t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "x", "t", "</s>"]
																												_lowerCAmelCase     :							Union[str, Any]    =    tokenizer.convert_tokens_to_string(__a)

																												self.assertIsInstance(__a,			__a)







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Optional[int]    =    self.get_tokenizers()
														for tokenizer in tokenizers:
																					with self.subTest(f"{tokenizer.__class__.__name__}"):
																												_lowerCAmelCase     :							Tuple    =    [
																												    "bos_token",
																												    "eos_token",
																												    "unk_token",
																												    "sep_token",
																												    "pad_token",
																												    "cls_token",
																												    "mask_token",
																												]

																												_lowerCAmelCase     :							Optional[int]    =    0
																												_lowerCAmelCase     :							List[str]    =    tokenizer.convert_ids_to_tokens(
																												    __a,			skip_special_tokens=__a)

																												for attr in attributes_list:
																																			setattr(__a,			attr + "_id",			__a)
																																			self.assertEqual(getattr(__a,			__a),			__a)
																																			self.assertEqual(getattr(__a,			attr + "_id"),			__a)

																																			setattr(__a,			attr + "_id",			__a)
																																			self.assertEqual(getattr(__a,			__a),			__a)
																																			self.assertEqual(getattr(__a,			attr + "_id"),			__a)

																												setattr(__a,			"additional_special_tokens_ids",			[])
																												self.assertListEqual(getattr(__a,			"additional_special_tokens"),			[])
																												self.assertListEqual(getattr(__a,			"additional_special_tokens_ids"),			[])

																												setattr(__a,			"additional_special_tokens_ids",			[token_id_to_test_setters])
																												self.assertListEqual(getattr(__a,			"additional_special_tokens"),			[token_to_test_setters])
																												self.assertListEqual(getattr(__a,			"additional_special_tokens_ids"),			[token_id_to_test_setters])






lowerCamelCase				:		Tuple     =   [
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

def 			_SCREAMING_SNAKE_CASE			(							lowercase	:       Optional[Any]	,							lowercase	:       int	,							lowercase	:       Optional[Any]	,							lowercase	:       List[Any]     ):


      '''simple docstring'''



      lowerCamelCase_		     =    [False] * len(lowercase     )
      lowerCamelCase_		     =    [s]
      lowerCamelCase_		     =    True

      while queue:
            lowerCamelCase_		     =    queue.pop(0     )
            for ind in range(len(graph[u]     )     ):
                  if visited[ind] is False and graph[u][ind] > 0:
                        queue.append(lowercase     )
                        lowerCamelCase_		     =    True
                        lowerCamelCase_		     =    u

      return visited[t]

def 			_SCREAMING_SNAKE_CASE			(							lowercase	:       List[str]	,							lowercase	:       Tuple	,							lowercase	:       Tuple     ):


      '''simple docstring'''



      lowerCamelCase_		     =    [-1] * (len(lowercase     ))
      lowerCamelCase_		     =    0
      lowerCamelCase_		     =    []
      lowerCamelCase_		     =    [i[:] for i in graph]  # Record original cut, copy.
      while bfs(lowercase	,							lowercase	,							lowercase	,							lowercase     ):
            lowerCamelCase_		     =    float('Inf'     )
            lowerCamelCase_		     =    sink

            while s != source:
                  # Find the minimum value in select path
                  lowerCamelCase_		     =    min(lowercase	,							graph[parent[s]][s]     )
                  lowerCamelCase_		     =    parent[s]

            max_flow += path_flow
            lowerCamelCase_		     =    sink

            while v != source:
                  lowerCamelCase_		     =    parent[v]
                  graph[u][v] -= path_flow
                  graph[v][u] += path_flow
                  lowerCamelCase_		     =    parent[v]

      for i in range(len(lowercase     )     ):
            for j in range(len(graph[0]     )     ):
                  if graph[i][j] == 0 and temp[i][j] > 0:
                        res.append((i, j)     )

      return res


if __name__ == "__main__":
 print(mincut(test_graph, source=0, sink=5))



