






"""simple docstring"""





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

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

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
  _SCREAMING_SNAKE_CASE					:				List[Any]					    =						'pt'
elif is_tf_available():
  _SCREAMING_SNAKE_CASE					:				List[str]					    =						'tf'
else:
  _SCREAMING_SNAKE_CASE					:				Optional[Any]					    =						'jax'






class      a						(					a_  ,      unittest.TestCase		):
    SCREAMING_SNAKE_CASE						:     Dict						= PerceiverTokenizer
    SCREAMING_SNAKE_CASE						:     Optional[int]						= False






    def    UpperCamelCase       (       self     :							Optional[Any]					)     ->		Any:
      super().setUp()
      lowerCamelCase_         =						PerceiverTokenizer()
      tokenizer.save_pretrained(self.tmpdirname					)






    @cached_property
    def    UpperCamelCase       (       self     :							Tuple					)     ->		Union[str, Any]:
      return PerceiverTokenizer.from_pretrained('deepmind/language-perceiver'					)






    def    UpperCamelCase       (       self     :							int       ,						**__SCREAMING_SNAKE_CASE     :							Optional[int]					)     ->		Tuple:
      return self.tokenizer_class.from_pretrained(self.tmpdirname       ,						**_lowerCamelCase					)






    def    UpperCamelCase       (       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]       ,						__SCREAMING_SNAKE_CASE     :							Optional[int]=False       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]=20       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=5					)     ->		str:
      # XXX The default common tokenizer tests assume that every ID is decodable on its own.
      # This assumption is invalid for Perceiver because single bytes might not be
      # valid utf-8 (byte 128 for instance).
      # Here we're overriding the smallest possible method to provide
      # a clean sequence without making the same assumption.

      lowerCamelCase_         =						[]
      for i in range(len(_lowerCamelCase					)					):
        try:
          lowerCamelCase_         =						tokenizer.decode([i]       ,						clean_up_tokenization_spaces=_lowerCamelCase					)
        except UnicodeDecodeError:
          pass
        toks.append((i, tok)					)

      lowerCamelCase_         =						list(filter(lambda __SCREAMING_SNAKE_CASE					: re.match(r'^[ a-zA-Z]+$'       ,						t[1]					)       ,						_lowerCamelCase					)					)
      lowerCamelCase_         =						list(filter(lambda __SCREAMING_SNAKE_CASE					: [t[0]] == tokenizer.encode(t[1]       ,						add_special_tokens=_lowerCamelCase					)       ,						_lowerCamelCase					)					)
      if max_length is not None and len(_lowerCamelCase					) > max_length:
        lowerCamelCase_         =						toks[:max_length]
      if min_length is not None and len(_lowerCamelCase					) < min_length and len(_lowerCamelCase					) > 0:
        while len(_lowerCamelCase					) < min_length:
          lowerCamelCase_         =						toks + toks
        # toks_str = [t[1] for t in toks]
      lowerCamelCase_         =						[t[0] for t in toks]

      # Ensure consistency
      lowerCamelCase_         =						tokenizer.decode(_lowerCamelCase       ,						clean_up_tokenization_spaces=_lowerCamelCase					)
      if " " not in output_txt and len(_lowerCamelCase					) > 1:
        lowerCamelCase_         =						(
            tokenizer.decode([toks_ids[0]]       ,						clean_up_tokenization_spaces=_lowerCamelCase					)
            + ' '
            + tokenizer.decode(toks_ids[1:]       ,						clean_up_tokenization_spaces=_lowerCamelCase					)
        )
      if with_prefix_space:
        lowerCamelCase_         =						' ' + output_txt
      lowerCamelCase_         =						tokenizer.encode(_lowerCamelCase       ,						add_special_tokens=_lowerCamelCase					)
      return output_txt, output_ids






    def    UpperCamelCase       (       self     :							Optional[int]					)     ->		Optional[Any]:
      lowerCamelCase_         =						self.perceiver_tokenizer
      lowerCamelCase_         =						'Unicode €.'
      lowerCamelCase_         =						tokenizer(_lowerCamelCase					)
      lowerCamelCase_         =						[4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
      self.assertEqual(encoded['input_ids']       ,						_lowerCamelCase					)

      # decoding
      lowerCamelCase_         =						tokenizer.decode(_lowerCamelCase					)
      self.assertEqual(_lowerCamelCase       ,						'[CLS]Unicode €.[SEP]'					)

      lowerCamelCase_         =						tokenizer('e è é ê ë'					)
      lowerCamelCase_         =						[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
      self.assertEqual(encoded['input_ids']       ,						_lowerCamelCase					)
      # decoding
      lowerCamelCase_         =						tokenizer.decode(_lowerCamelCase					)
      self.assertEqual(_lowerCamelCase       ,						'[CLS]e è é ê ë[SEP]'					)

      # encode/decode, but with `encode` instead of `__call__`
      self.assertEqual(tokenizer.decode(tokenizer.encode('e è é ê ë'					)					)       ,						'[CLS]e è é ê ë[SEP]'					)






    def    UpperCamelCase       (       self     :							Tuple					)     ->		str:
      lowerCamelCase_         =						self.perceiver_tokenizer
      lowerCamelCase_         =						['A long paragraph for summarization.', 'Another paragraph for summarization.']
      # fmt: off
      lowerCamelCase_         =						[4, 71, 38, 114, 117, 116, 109, 38, 118, 103, 120, 103, 109, 120, 103, 118, 110, 38, 108, 117, 120, 38, 121, 123, 115, 115, 103, 120, 111, 128, 103, 122, 111, 117, 116, 52, 5, 0]
      # fmt: on
      lowerCamelCase_         =						tokenizer(_lowerCamelCase       ,						padding=_lowerCamelCase       ,						return_tensors=_lowerCamelCase					)
      self.assertIsInstance(_lowerCamelCase       ,						_lowerCamelCase					)

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

      self.assertListEqual(_lowerCamelCase       ,						_lowerCamelCase					)

      self.assertEqual((2, 38)       ,						batch.input_ids.shape					)
      self.assertEqual((2, 38)       ,						batch.attention_mask.shape					)






    def    UpperCamelCase       (       self     :							str					)     ->		Tuple:
      lowerCamelCase_         =						self.perceiver_tokenizer
      lowerCamelCase_         =						['A long paragraph for summarization.', 'Another paragraph for summarization.']
      lowerCamelCase_         =						tokenizer(_lowerCamelCase       ,						padding=_lowerCamelCase       ,						return_tensors=_lowerCamelCase					)
      # check if input_ids are returned and no decoder_input_ids
      self.assertIn('input_ids'       ,						_lowerCamelCase					)
      self.assertIn('attention_mask'       ,						_lowerCamelCase					)
      self.assertNotIn('decoder_input_ids'       ,						_lowerCamelCase					)
      self.assertNotIn('decoder_attention_mask'       ,						_lowerCamelCase					)






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		Dict:
      lowerCamelCase_         =						self.perceiver_tokenizer
      lowerCamelCase_         =						[
          'Summary of the text.',
          'Another summary.',
      ]
      lowerCamelCase_         =						tokenizer(
          text_target=_lowerCamelCase       ,						max_length=32       ,						padding='max_length'       ,						truncation=_lowerCamelCase       ,						return_tensors=_lowerCamelCase					)
      self.assertEqual(32       ,						targets['input_ids'].shape[1]					)






    def    UpperCamelCase       (       self     :							Tuple					)     ->		str:
      # safety check on max_len default value so we are sure the test works
      lowerCamelCase_         =						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_         =						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_         =						tempfile.mkdtemp()

          lowerCamelCase_         =						' He is very happy, UNwant\u00E9d,running'
          lowerCamelCase_         =						tokenizer.encode(_lowerCamelCase       ,						add_special_tokens=_lowerCamelCase					)
          tokenizer.save_pretrained(_lowerCamelCase					)

          lowerCamelCase_         =						tokenizer.__class__.from_pretrained(_lowerCamelCase					)
          lowerCamelCase_         =						after_tokenizer.encode(_lowerCamelCase       ,						add_special_tokens=_lowerCamelCase					)
          self.assertListEqual(_lowerCamelCase       ,						_lowerCamelCase					)

          shutil.rmtree(_lowerCamelCase					)

      lowerCamelCase_         =						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_         =						tempfile.mkdtemp()

          lowerCamelCase_         =						' He is very happy, UNwant\u00E9d,running'
          tokenizer.add_tokens(['bim', 'bambam']					)
          lowerCamelCase_         =						tokenizer.additional_special_tokens
          additional_special_tokens.append('new_additional_special_token'					)
          tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}					)
          lowerCamelCase_         =						tokenizer.encode(_lowerCamelCase       ,						add_special_tokens=_lowerCamelCase					)
          tokenizer.save_pretrained(_lowerCamelCase					)

          lowerCamelCase_         =						tokenizer.__class__.from_pretrained(_lowerCamelCase					)
          lowerCamelCase_         =						after_tokenizer.encode(_lowerCamelCase       ,						add_special_tokens=_lowerCamelCase					)
          self.assertListEqual(_lowerCamelCase       ,						_lowerCamelCase					)
          self.assertIn('new_additional_special_token'       ,						after_tokenizer.additional_special_tokens					)
          self.assertEqual(after_tokenizer.model_max_length       ,						42					)

          lowerCamelCase_         =						tokenizer.__class__.from_pretrained(_lowerCamelCase       ,						model_max_length=43					)
          self.assertEqual(tokenizer.model_max_length       ,						43					)

          shutil.rmtree(_lowerCamelCase					)






    def    UpperCamelCase       (       self     :							str					)     ->		List[Any]:
      lowerCamelCase_         =						[]
      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(_lowerCamelCase					)

          with open(os.path.join(_lowerCamelCase       ,						'special_tokens_map.json'					)       ,						encoding='utf-8'					) as json_file:
            lowerCamelCase_         =						json.load(_lowerCamelCase					)

          with open(os.path.join(_lowerCamelCase       ,						'tokenizer_config.json'					)       ,						encoding='utf-8'					) as json_file:
            lowerCamelCase_         =						json.load(_lowerCamelCase					)

          lowerCamelCase_         =						[F'''<extra_id_{i}>''' for i in range(125					)]

          lowerCamelCase_         =						added_tokens_extra_ids + [
              'an_additional_special_token'
          ]
          lowerCamelCase_         =						added_tokens_extra_ids + [
              'an_additional_special_token'
          ]

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

          # 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_         =						tokenizer_class.from_pretrained(
              _lowerCamelCase       ,						)
          self.assertIn(
              'an_additional_special_token'       ,						tokenizer_without_change_in_init.additional_special_tokens					)
          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_         =						added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'       ,						lstrip=_lowerCamelCase					)]
          lowerCamelCase_         =						tokenizer_class.from_pretrained(
              _lowerCamelCase       ,						additional_special_tokens=_lowerCamelCase       ,						)

          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    UpperCamelCase       (       self     :							Union[str, Any]					)     ->		Optional[Any]:
      lowerCamelCase_         =						self.perceiver_tokenizer
      self.assertEqual(tokenizer.decode([178]					)       ,						'�'					)






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






    def    UpperCamelCase       (       self     :							Tuple					)     ->		Dict:
      pass






    def    UpperCamelCase       (       self     :							Optional[Any]					)     ->		List[str]:
      pass






    def    UpperCamelCase       (       self     :							Dict					)     ->		str:
      pass






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		int:
      # The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
      # strings and special added tokens as tokens
      lowerCamelCase_         =						self.get_tokenizers(fast=_lowerCamelCase       ,						do_lower_case=_lowerCamelCase					)
      for tokenizer in tokenizers:
        with self.subTest(F'''{tokenizer.__class__.__name__}'''					):
          lowerCamelCase_         =						['[CLS]', 't', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 's', 't', '[SEP]']
          lowerCamelCase_         =						tokenizer.convert_tokens_to_string(_lowerCamelCase					)

          self.assertIsInstance(_lowerCamelCase       ,						_lowerCamelCase					)












"""simple docstring"""



import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
_UpperCamelCase		:  Tuple						=		logging.getLogger()
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Path		,					__snake_case			:  list    ):





  '''simple docstring'''





  lowercase							    =       '\n'.join(__snake_case    )
  Path(__snake_case    ).open('w'    ).writelines(__snake_case    )


_UpperCamelCase		:  Union[str, Any]						=		'patrickvonplaten/t5-tiny-random'
_UpperCamelCase		:  Union[str, Any]						=		'sshleifer/bart-tiny-random'
_UpperCamelCase		:  Tuple						=		'sshleifer/tiny-mbart'

_UpperCamelCase		:  Union[str, Any]						=		logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks



class        a     (   a_	):







    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      lowercase							    =       Path(self.get_auto_remove_tmp_dir()       ) / 'utest_input.source'
      lowercase							    =       input_file_name.parent / 'utest_output.txt'
      assert not output_file_name.exists()
      lowercase							    =       [' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
      _dump_articles(_lowerCamelCase							,		_lowerCamelCase       )

      lowercase							    =       str(Path(self.get_auto_remove_tmp_dir()       ) / 'scores.json'       )
      lowercase							    =       'translation_en_to_de' if model == T5_TINY else 'summarization'
      lowercase							    =       F'\n            run_eval_search.py\n            {model}\n            {input_file_name}\n            {output_file_name}\n            --score_path {score_path}\n            --task {task}\n            --num_beams 2\n            --length_penalty 2.0\n            '.split()

      with patch.object(_lowerCamelCase							,		'argv'							,		_lowerCamelCase       ):
        run_generate()
        assert Path(_lowerCamelCase       ).exists()
        # os.remove(Path(output_file_name))







    def 			UpperCamelCase_      (			self       ):
      self.run_eval_tester(_lowerCamelCase       )







    @parameterized.expand([BART_TINY, MBART_TINY]       )
    @slow
    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      self.run_eval_tester(_lowerCamelCase       )







    @parameterized.expand([T5_TINY, MBART_TINY]       )
    @slow
    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      lowercase							    =       Path(self.get_auto_remove_tmp_dir()       ) / 'utest_input.source'
      lowercase							    =       input_file_name.parent / 'utest_output.txt'
      assert not output_file_name.exists()

      lowercase							    =       {
          'en': ['Machine learning is great, isn\'t it?', 'I like to eat bananas', 'Tomorrow is another great day!'],
          'de': [
              'Maschinelles Lernen ist großartig, oder?',
              'Ich esse gerne Bananen',
              'Morgen ist wieder ein toller Tag!',
          ],
      }

      lowercase							    =       Path(self.get_auto_remove_tmp_dir()       )
      lowercase							    =       str(tmp_dir / 'scores.json'       )
      lowercase							    =       str(tmp_dir / 'val.target'       )
      _dump_articles(_lowerCamelCase							,		text['en']       )
      _dump_articles(_lowerCamelCase							,		text['de']       )
      lowercase							    =       'translation_en_to_de' if model == T5_TINY else 'summarization'
      lowercase							    =       F'\n            run_eval_search.py\n            {model}\n            {str(_lowerCamelCase       )}\n            {str(_lowerCamelCase       )}\n            --score_path {score_path}\n            --reference_path {reference_path}\n            --task {task}\n            '.split()
      testargs.extend(['--search', 'num_beams=1:2 length_penalty=0.9:1.0']       )

      with patch.object(_lowerCamelCase							,		'argv'							,		_lowerCamelCase       ):
        with CaptureStdout() as cs:
          run_search()
        lowercase							    =       [' num_beams | length_penalty', model, 'Best score args']
        lowercase							    =       ['Info']
        if "translation" in task:
          expected_strings.append('bleu'       )
        else:
          expected_strings.extend(_lowerCamelCase       )
        for w in expected_strings:
          assert w in cs.out
        for w in un_expected_strings:
          assert w not in cs.out
        assert Path(_lowerCamelCase       ).exists()
        os.remove(Path(_lowerCamelCase       )       )


