


import json
import os
from datetime import date
from pathlib import Path

from tabulate import DataRow, TableFormat, tabulate


__UpperCamelCase    :						Union[str, Any]     =							TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow('', '|', '|'),
    datarow=DataRow('', '|', '|'),
    padding=1,
    with_header_hide=None,
)


__UpperCamelCase    :						Union[str, Any]     =							[]
__UpperCamelCase    :						List[str]     =							[]

__UpperCamelCase    :						Any     =							{'type': 'section', 'text': {'type': 'plain_text', 'text': 'No failed tests! 🤗', 'emoji': True}}

__UpperCamelCase    :						int     =							[
    {
        'type': 'header',
        'text': {
            'type': 'plain_text',
            'text': F'''🤗 Accelerate nightly {os.environ.get('TEST_TYPE', '')} test results''',
            'emoji': True,
        },
    }
]

__UpperCamelCase    :						Optional[Any]     =							0
for log in Path().glob('*.log'):
    __UpperCamelCase    :						Optional[Any]     =							0
    with open(log, 'r') as f:
        for line in f:
            __UpperCamelCase    :						List[str]     =							json.loads(line)
            if line.get('nodeid', '') != "":
                __UpperCamelCase    :						List[str]     =							line['nodeid']
                if line.get('duration', None) is not None:
                    __UpperCamelCase    :						Tuple     =							F'''{line['duration']:.4f}'''
                    if line.get('outcome', '') == "failed":
                        section_num_failed += 1
                        failed.append([test, duration, log.name.split('_')[0]])
                        total_num_failed += 1
    group_info.append([str(log), section_num_failed, failed])
    __UpperCamelCase    :						Optional[Any]     =							[]
    log.unlink()

__UpperCamelCase    :						List[Any]     =							''
__UpperCamelCase    :						List[Any]     =							[]
if total_num_failed > 0:
    for name, num_failed, failed_tests in group_info:
        if num_failed > 0:
            if num_failed == 1:
                message += F"*{name[1:]}: {num_failed} failed test*\n"
            else:
                message += F"*{name[1:]}: {num_failed} failed tests*\n"
            __UpperCamelCase    :						Optional[Any]     =							[]
            __UpperCamelCase    :						List[str]     =							{}
            for test in failed_tests:
                __UpperCamelCase    :						Optional[int]     =							test[0].split('::')
                __UpperCamelCase    :						Optional[Any]     =							data[0].split('/')[-1]
                if data[0] not in filesafailed:
                    __UpperCamelCase    :						Dict     =							[data[1:]]
                else:
                    filesafailed[data[0]] += [data[1:]]
                failed_table.append(data)

            __UpperCamelCase    :						List[Any]     =							[test[0] for test in failed_table]
            __UpperCamelCase    :						Tuple     =							list(set(files))
            # Count number of instances in failed_tests
            __UpperCamelCase    :						Dict     =							[]
            for file in individual_files:
                table.append([file, len(filesafailed[file])])

            __UpperCamelCase    :						Any     =							tabulate(
                table,
                headers=['Test Location', 'Num Failed'],
                tablefmt=hf_table_format,
                stralign='right',
            )
            message += F"\n```\n{failed_table}\n```"
            all_filesafailed.append(filesafailed)
    if len(message) > 3000:
        __UpperCamelCase    :						Dict     =							'Too many failed tests, please see the full report in the Action results.'
        __UpperCamelCase    :						Optional[Any]     =							len(err) + 10
        __UpperCamelCase    :						Optional[Any]     =							message[: 3000 - offset] + F'''\n...\n```\n{err}'''
    print(F'''### {message}''')
else:
    __UpperCamelCase    :						Union[str, Any]     =							'No failed tests! 🤗'
    print(F'''## {message}''')
    payload.append(no_error_payload)

if os.environ.get('TEST_TYPE', '') != "":
    from slack_sdk import WebClient

    __UpperCamelCase    :						Dict     =							WebClient(token=os.environ['SLACK_API_TOKEN'])
    if message != "No failed tests! 🤗":
        __UpperCamelCase    :						Optional[int]     =							{
            'type': 'section',
            'text': {
                'type': 'mrkdwn',
                'text': message,
            },
        }
        payload.append(md_report)
        __UpperCamelCase    :						str     =							{
            'type': 'section',
            'text': {
                'type': 'mrkdwn',
                'text': '*For more details:*',
            },
            'accessory': {
                'type': 'button',
                'text': {
                    'type': 'plain_text',
                    'text': 'Check Action results',
                    'emoji': True,
                },
                'url': F'''https://github.com/{os.environ['GITHUB_REPOSITORY']}/actions/runs/{os.environ['GITHUB_RUN_ID']}''',
            },
        }
        payload.append(action_button)
        __UpperCamelCase    :						Union[str, Any]     =							{
            'type': 'context',
            'elements': [
                {
                    'type': 'plain_text',
                    'text': F'''Nightly {os.environ.get('TEST_TYPE')} test results for {date.today()}''',
                }
            ],
        }
        payload.append(date_report)
    __UpperCamelCase    :						Optional[Any]     =							client.chat_postMessage(channel='#accelerate-ci-daily', text=message, blocks=payload)
    __UpperCamelCase    :						List[Any]     =							response.data['ts']
    for failed_file in all_filesafailed:
        for test_location, test_failures in failed_file.items():
            # Keep only the first instance of the test name
            __UpperCamelCase    :						Union[str, Any]     =							''
            for i, row in enumerate(test_failures):
                if row[0] != test_class:
                    __UpperCamelCase    :						List[str]     =							row[0]
                else:
                    __UpperCamelCase    :						Dict     =							''

            __UpperCamelCase    :						Dict     =							{
                'type': 'section',
                'text': {
                    'type': 'mrkdwn',
                    'text': F'''Test location: {test_location}\n```\n{tabulate(test_failures, headers=['Class', 'Test'], tablefmt=hf_table_format, stralign='right')}\n```''',
                },
            }

            client.chat_postMessage(
                channel='#accelerate-ci-daily',
                thread_ts=ts,
                blocks=[payload],
            )







import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__UpperCamelCase    :						str     =							get_tests_dir('fixtures/test_sentencepiece.model')



@require_sentencepiece
@require_tokenizers
class 							_UpperCamelCase (						A,unittest.TestCase						):

   '''simple docstring'''







   a_				:							List[Any]    = ReformerTokenizer
   a_				:							Optional[int]    = ReformerTokenizerFast
   a_				:							Optional[int]    = True
   a_				:							List[Any]    = False
   a_				:							Any    = True

   def   _snake_case    (  self  : Optional[int]							):






         '''simple docstring'''



         super().setUp()

         __lowerCamelCase     :      str       						=						ReformerTokenizer(_lowerCamelCase       ,  keep_accents=_lowerCamelCase							)
         tokenizer.save_pretrained(self.tmpdirname							)

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






         '''simple docstring'''



         __lowerCamelCase     :      List[str]       						=						"""<s>"""
         __lowerCamelCase     :      Any       						=						1

         self.assertEqual(self.get_tokenizer()._convert_token_to_id(_lowerCamelCase							)       ,  _lowerCamelCase							)
         self.assertEqual(self.get_tokenizer()._convert_id_to_token(_lowerCamelCase							)       ,  _lowerCamelCase							)

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






         '''simple docstring'''



         __lowerCamelCase     :      Dict       						=						list(self.get_tokenizer().get_vocab().keys()							)

         self.assertEqual(vocab_keys[0]       ,  """<unk>"""							)
         self.assertEqual(vocab_keys[1]       ,  """<s>"""							)
         self.assertEqual(vocab_keys[-1]       ,  """j"""							)
         self.assertEqual(len(_lowerCamelCase							)       ,  1_0_0_0							)

   def   _snake_case    (  self  : str							):






         '''simple docstring'''



         self.assertEqual(self.get_tokenizer().vocab_size       ,  1_0_0_0							)

   def   _snake_case    (  self  : Tuple							):






         '''simple docstring'''



         if not self.test_rust_tokenizer:
               return

         __lowerCamelCase     :      Dict       						=						self.get_tokenizer()
         __lowerCamelCase     :      Optional[int]       						=						self.get_rust_tokenizer()

         __lowerCamelCase     :      Optional[Any]       						=						"""I was born in 92000, and this is falsé."""

         __lowerCamelCase     :      Union[str, Any]       						=						tokenizer.tokenize(_lowerCamelCase							)
         __lowerCamelCase     :      Optional[int]       						=						rust_tokenizer.tokenize(_lowerCamelCase							)
         self.assertListEqual(_lowerCamelCase       ,  _lowerCamelCase							)

         __lowerCamelCase     :      str       						=						tokenizer.encode(_lowerCamelCase       ,  add_special_tokens=_lowerCamelCase							)
         __lowerCamelCase     :      Tuple       						=						rust_tokenizer.encode(_lowerCamelCase       ,  add_special_tokens=_lowerCamelCase							)
         self.assertListEqual(_lowerCamelCase       ,  _lowerCamelCase							)

         __lowerCamelCase     :      str       						=						self.get_rust_tokenizer()
         __lowerCamelCase     :      Dict       						=						tokenizer.encode(_lowerCamelCase							)
         __lowerCamelCase     :      Dict       						=						rust_tokenizer.encode(_lowerCamelCase							)
         self.assertListEqual(_lowerCamelCase       ,  _lowerCamelCase							)

   def   _snake_case    (  self  : Any       ,  _lowerCamelCase  : int=1_5							):






         '''simple docstring'''



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

                     # Simple input
                     __lowerCamelCase     :      Any       						=						"""This is a simple input"""
                     __lowerCamelCase     :      Optional[Any]       						=						["""This is a simple input 1""", """This is a simple input 2"""]
                     __lowerCamelCase     :      Union[str, Any]       						=						("""This is a simple input""", """This is a pair""")
                     __lowerCamelCase     :      Optional[int]       						=						[
                         ("""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   _snake_case    (  self  : List[str]							):






         '''simple docstring'''



         pass

   def   _snake_case    (  self  : Tuple							):






         '''simple docstring'''



         __lowerCamelCase     :      Any       						=						ReformerTokenizer(_lowerCamelCase       ,  keep_accents=_lowerCamelCase							)

         __lowerCamelCase     :      List[Any]       						=						tokenizer.tokenize("""This is a test"""							)
         self.assertListEqual(_lowerCamelCase       ,  ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]							)

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(_lowerCamelCase							)       ,  [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]       ,  )

         __lowerCamelCase     :      List[Any]       						=						tokenizer.tokenize("""I was born in 92000, and this is falsé."""							)
         self.assertListEqual(
             _lowerCamelCase       ,  [
                 SPIECE_UNDERLINE + """I""",
                 SPIECE_UNDERLINE + """was""",
                 SPIECE_UNDERLINE + """b""",
                 """or""",
                 """n""",
                 SPIECE_UNDERLINE + """in""",
                 SPIECE_UNDERLINE + """""",
                 """9""",
                 """2""",
                 """0""",
                 """0""",
                 """0""",
                 """,""",
                 SPIECE_UNDERLINE + """and""",
                 SPIECE_UNDERLINE + """this""",
                 SPIECE_UNDERLINE + """is""",
                 SPIECE_UNDERLINE + """f""",
                 """al""",
                 """s""",
                 """é""",
                 """.""",
             ]       ,  )
         __lowerCamelCase     :      Union[str, Any]       						=						tokenizer.convert_tokens_to_ids(_lowerCamelCase							)
         self.assertListEqual(
             _lowerCamelCase       ,  [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]       ,  )

         __lowerCamelCase     :      List[str]       						=						tokenizer.convert_ids_to_tokens(_lowerCamelCase							)
         self.assertListEqual(
             _lowerCamelCase       ,  [
                 SPIECE_UNDERLINE + """I""",
                 SPIECE_UNDERLINE + """was""",
                 SPIECE_UNDERLINE + """b""",
                 """or""",
                 """n""",
                 SPIECE_UNDERLINE + """in""",
                 SPIECE_UNDERLINE + """""",
                 """<unk>""",
                 """2""",
                 """0""",
                 """0""",
                 """0""",
                 """,""",
                 SPIECE_UNDERLINE + """and""",
                 SPIECE_UNDERLINE + """this""",
                 SPIECE_UNDERLINE + """is""",
                 SPIECE_UNDERLINE + """f""",
                 """al""",
                 """s""",
                 """<unk>""",
                 """.""",
             ]       ,  )

   @cached_property
   def   _snake_case    (  self  : List[str]							):






         '''simple docstring'''



         return ReformerTokenizer.from_pretrained("""google/reformer-crime-and-punishment"""							)

   @slow
   def   _snake_case    (  self  : str							):






         '''simple docstring'''



         __lowerCamelCase     :      Dict       						=						"""Hello World!"""
         __lowerCamelCase     :      Any       						=						[1_2_6, 3_2, 2_6_2, 1_5_2, 3_8, 7_2, 2_8_7]

         self.assertListEqual(_lowerCamelCase       ,  self.big_tokenizer.encode(_lowerCamelCase							)							)

   @slow
   def   _snake_case    (  self  : Tuple							):






         '''simple docstring'''



         __lowerCamelCase     :      Any       						=						(
             """This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"""
             """ add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"""
         )
         __lowerCamelCase     :      List[str]       						=						[
             1_0_8,
             2_6_5,
             2_4,
             1_1_1,
             4,
             2_5_8,
             1_5_6,
             3_5,
             2_8,
             2_7_5,
             3,
             2_5_9,
             2_9_7,
             2_6_0,
             8_4,
             4,
             3_5,
             1_1_0,
             4_4,
             8,
             2_5_9,
             9_1,
             2_6_8,
             2_1,
             1_1,
             2_0_9,
             2_7_4,
             1_0_9,
             2_6_6,
             2_7_7,
             1_1_7,
             8_6,
             9_3,
             3_1_5,
             2_5_8,
             2_7_8,
             2_5_8,
             2_7_7,
             2_5_8,
             0,
             2_5_8,
             2_8_8,
             2_5_8,
             3_1_9,
             2_5_8,
             0,
             2_5_8,
             0,
             2_5_8,
             0,
             2_5_8,
             0,
             2_5_8,
             2_8_7,
             2_5_8,
             3_1_5,
             2_5_8,
             2_8_9,
             2_5_8,
             2_7_8,
             9_9,
             2_6_9,
             2_6_6,
             2_6_2,
             8,
             2_5_9,
             2_4_1,
             4,
             2_1_7,
             2_3_0,
             2_6_8,
             2_6_6,
             5_5,
             1_6_8,
             1_0_6,
             7_5,
             1_9_3,
             2_6_6,
             2_2_3,
             2_7,
             4_9,
             2_6,
             2_8_2,
             2_5,
             2_6_4,
             2_9_9,
             1_9,
             2_6,
             0,
             2_5_8,
             2_7_7,
             1_1_7,
             8_6,
             9_3,
             1_7_6,
             1_8_3,
             2_7_0,
             1_1,
             2_6_2,
             4_2,
             6_1,
             2_6_5,
         ]

         self.assertListEqual(_lowerCamelCase       ,  self.big_tokenizer.encode(_lowerCamelCase							)							)

   @require_torch
   @slow
   def   _snake_case    (  self  : Optional[int]							):






         '''simple docstring'''



         import torch

         from transformers import ReformerConfig, ReformerModel

         # Build sequence
         __lowerCamelCase     :      int       						=						list(self.big_tokenizer.get_vocab().keys()							)[:1_0]
         __lowerCamelCase     :      Union[str, Any]       						=						""" """.join(_lowerCamelCase							)
         __lowerCamelCase     :      Union[str, Any]       						=						self.big_tokenizer.encode_plus(_lowerCamelCase       ,  return_tensors="""pt"""							)
         __lowerCamelCase     :      Union[str, Any]       						=						self.big_tokenizer.batch_encode_plus([sequence, sequence]       ,  return_tensors="""pt"""							)

         __lowerCamelCase     :      List[Any]       						=						ReformerConfig()
         # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
         __lowerCamelCase     :      List[str]       						=						encoded_sequence["""input_ids"""].shape
         __lowerCamelCase     :      Optional[Any]       						=						ReformerModel(_lowerCamelCase							)

         # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
         assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

         with torch.no_grad():
               model(**_lowerCamelCase							)
               model(**_lowerCamelCase							)


   @slow
   def   _snake_case    (  self  : List[Any]							):






         '''simple docstring'''



         __lowerCamelCase     :      Tuple       						=						{"""input_ids""": [[1_0_8, 2_6_5, 2_4, 1_1_1, 4, 2_5_8, 1_5_6, 7, 5_1, 2_7_9, 5_8, 7, 7_6, 2_5, 6_9, 2_7_8], [1_4_0, 2_4_3, 2_6_4, 1_3_4, 1_7, 2_6_7, 7_7, 2_6_3, 2_2, 2_6_2, 2_9_7, 2_5_8, 3_0_4, 1_7_7, 2_7_9, 2_6_6, 1_4, 8_9, 1_3, 3_5, 2_6_1, 2_9_9, 2_7_2, 1_3_7, 2_7_5, 2_7_8]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
         # fmt: on

         # This tokenizer does not know some characters like ")".
         # That is the reason why we use very simple texts here.
         # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
         __lowerCamelCase     :      int       						=						[
             """This is a very simple sentence.""",
             """The quick brown fox jumps over the lazy dog.""",
         ]

         self.tokenizer_integration_test_util(
             expected_encoding=_lowerCamelCase       ,  model_name="""google/reformer-crime-and-punishment"""       ,  revision="""0e6c3decb8211d49bf881013425dc8b0448b3f5a"""       ,  padding=_lowerCamelCase       ,  sequences=_lowerCamelCase       ,  )



