


"""simple docstring"""







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

from tabulate import DataRow, TableFormat, tabulate


lowerCamelCase_   :   Optional[Any]									=  TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow("""""", """|""", """|"""),
    datarow=DataRow("""""", """|""", """|"""),
    padding=1,
    with_header_hide=None,
)


lowerCamelCase_   :   List[Any]									=  []
lowerCamelCase_   :   Optional[Any]									=  []

lowerCamelCase_   :   Optional[Any]									=  {"""type""": """section""", """text""": {"""type""": """plain_text""", """text""": """No failed tests! 🤗""", """emoji""": True}}

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

lowerCamelCase_   :   List[Any]									=  0
for log in Path().glob("""*.log"""):
       lowerCamelCase_   :   List[Any]									=  0
       with open(log, """r""") as f:
              for line in f:
                     lowerCamelCase_   :   List[Any]									=  json.loads(line)
                     if line.get("""nodeid""", """""") != "":
                            lowerCamelCase_   :   Any									=  line["""nodeid"""]
                            if line.get("""duration""", None) is not None:
                                   lowerCamelCase_   :   List[Any]									=  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])
       lowerCamelCase_   :   List[str]									=  []
       log.unlink()

lowerCamelCase_   :   List[Any]									=  """"""
lowerCamelCase_   :   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"
                     lowerCamelCase_   :   Optional[Any]									=  []
                     lowerCamelCase_   :   Optional[int]									=  {}
                     for test in failed_tests:
                            lowerCamelCase_   :   Union[str, Any]									=  test[0].split("""::""")
                            lowerCamelCase_   :   Union[str, Any]									=  data[0].split("""/""")[-1]
                            if data[0] not in filesafailed:
                                   lowerCamelCase_   :   str									=  [data[1:]]
                            else:
                                   filesafailed[data[0]] += [data[1:]]
                            failed_table.append(data)

                     lowerCamelCase_   :   Optional[Any]									=  [test[0] for test in failed_table]
                     lowerCamelCase_   :   str									=  list(set(files))
                     # Count number of instances in failed_tests
                     lowerCamelCase_   :   int									=  []
                     for file in individual_files:
                            table.append([file, len(filesafailed[file])])

                     lowerCamelCase_   :   str									=  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) > 3_0_0_0:
              lowerCamelCase_   :   int									=  """Too many failed tests, please see the full report in the Action results."""
              lowerCamelCase_   :   str									=  len(err) + 1_0
              lowerCamelCase_   :   Optional[Any]									=  message[: 3_0_0_0 - offset] + F'\n...\n```\n{err}'
       print(F'### {message}')
else:
       lowerCamelCase_   :   Optional[Any]									=  """No failed tests! 🤗"""
       print(F'## {message}')
       payload.append(no_error_payload)

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

       lowerCamelCase_   :   List[Any]									=  WebClient(token=os.environ["""SLACK_API_TOKEN"""])
       if message != "No failed tests! 🤗":
              lowerCamelCase_   :   Any									=  {
                  """type""": """section""",
                  """text""": {
                      """type""": """mrkdwn""",
                      """text""": message,
                  },
              }
              payload.append(md_report)
              lowerCamelCase_   :   Dict									=  {
                  """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)
              lowerCamelCase_   :   Optional[Any]									=  {
                  """type""": """context""",
                  """elements""": [
                      {
                          """type""": """plain_text""",
                          """text""": F'Nightly {os.environ.get("TEST_TYPE")} test results for {date.today()}',
                      }
                  ],
              }
              payload.append(date_report)
       lowerCamelCase_   :   Optional[int]									=  client.chat_postMessage(channel="""#accelerate-ci-daily""", text=message, blocks=payload)
       lowerCamelCase_   :   Union[str, 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
                     lowerCamelCase_   :   int									=  """"""
                     for i, row in enumerate(test_failures):
                            if row[0] != test_class:
                                   lowerCamelCase_   :   str									=  row[0]
                            else:
                                   lowerCamelCase_   :   str									=  """"""

                     lowerCamelCase_   :   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],
                     )
'''simple docstring'''




import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta 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, filter_roberta_detectors






@require_tokenizers
class 				a__(					lowerCAmelCase__ ,						unittest.TestCase	):


			'''simple docstring'''






			UpperCAmelCase_			:     Dict      =       MvpTokenizer
			UpperCAmelCase_			:     Optional[Any]      =       MvpTokenizerFast
			UpperCAmelCase_			:     str      =       True
			UpperCAmelCase_			:     List[Any]      =       filter_roberta_detectors



			def 							a_       (   self):




					"""simple docstring"""


					super().setUp()
					lowerCAmelCase   					=  [
					    """l""",
					    """o""",
					    """w""",
					    """e""",
					    """r""",
					    """s""",
					    """t""",
					    """i""",
					    """d""",
					    """n""",
					    """\u0120""",
					    """\u0120l""",
					    """\u0120n""",
					    """\u0120lo""",
					    """\u0120low""",
					    """er""",
					    """\u0120lowest""",
					    """\u0120newer""",
					    """\u0120wider""",
					    """<unk>""",
					]
					lowerCAmelCase   					=  dict(zip(__lowerCAmelCase       ,    range(len(__lowerCAmelCase))))
					lowerCAmelCase   					=  ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
					lowerCAmelCase   					=  {"""unk_token""": """<unk>"""}

					lowerCAmelCase   					=  os.path.join(self.tmpdirname       ,    VOCAB_FILES_NAMES["""vocab_file"""])
					lowerCAmelCase   					=  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       ,    **__lowerCAmelCase):




					"""simple docstring"""


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



			def 							a_       (   self       ,    **__lowerCAmelCase):




					"""simple docstring"""


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



			def 							a_       (   self       ,    __lowerCAmelCase):




					"""simple docstring"""


					return "lower newer", "lower newer"



			@cached_property
			def 							a_       (   self):




					"""simple docstring"""


					return MvpTokenizer.from_pretrained("""RUCAIBox/mvp""")



			@cached_property
			def 							a_       (   self):




					"""simple docstring"""


					return MvpTokenizerFast.from_pretrained("""RUCAIBox/mvp""")



			@require_torch
			def 							a_       (   self):




					"""simple docstring"""


					lowerCAmelCase   					=  ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
					lowerCAmelCase   					=  [0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
							lowerCAmelCase   					=  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)
							lowerCAmelCase   					=  batch.input_ids.tolist()[0]
							self.assertListEqual(__lowerCAmelCase       ,    __lowerCAmelCase)
							# Test that special tokens are reset



			@require_torch
			def 							a_       (   self):




					"""simple docstring"""


					lowerCAmelCase   					=  ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
							lowerCAmelCase   					=  tokenizer(__lowerCAmelCase       ,    padding=__lowerCAmelCase       ,    return_tensors="""pt""")
							# check if input_ids are returned and no labels
							self.assertIn("""input_ids"""       ,    __lowerCAmelCase)
							self.assertIn("""attention_mask"""       ,    __lowerCAmelCase)
							self.assertNotIn("""labels"""       ,    __lowerCAmelCase)
							self.assertNotIn("""decoder_attention_mask"""       ,    __lowerCAmelCase)



			@require_torch
			def 							a_       (   self):




					"""simple docstring"""


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



			@require_torch
			def 							a_       (   self):




					"""simple docstring"""


					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
							lowerCAmelCase   					=  tokenizer(
							    ["""I am a small frog""" * 1024, """I am a small frog"""]       ,    padding=__lowerCAmelCase       ,    truncation=__lowerCAmelCase       ,    return_tensors="""pt""")
							self.assertIsInstance(__lowerCAmelCase       ,    __lowerCAmelCase)
							self.assertEqual(batch.input_ids.shape       ,    (2, 1024))



			@require_torch
			def 							a_       (   self):




					"""simple docstring"""


					lowerCAmelCase   					=  ["""A long paragraph for summarization."""]
					lowerCAmelCase   					=  [
					    """Summary of the text.""",
					]
					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
							lowerCAmelCase   					=  tokenizer(__lowerCAmelCase       ,    text_target=__lowerCAmelCase       ,    return_tensors="""pt""")
							lowerCAmelCase   					=  inputs["""input_ids"""]
							lowerCAmelCase   					=  inputs["""labels"""]
							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())



			def 							a_       (   self):




					"""simple docstring"""


					pass







			def 							a_       (   self):




					"""simple docstring"""


					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
									lowerCAmelCase   					=  self.rust_tokenizer_class.from_pretrained(__lowerCAmelCase       ,    **__lowerCAmelCase)
									lowerCAmelCase   					=  self.tokenizer_class.from_pretrained(__lowerCAmelCase       ,    **__lowerCAmelCase)
									lowerCAmelCase   					=  """A, <mask> AllenNLP sentence."""
									lowerCAmelCase   					=  tokenizer_r.encode_plus(__lowerCAmelCase       ,    add_special_tokens=__lowerCAmelCase       ,    return_token_type_ids=__lowerCAmelCase)
									lowerCAmelCase   					=  tokenizer_p.encode_plus(__lowerCAmelCase       ,    add_special_tokens=__lowerCAmelCase       ,    return_token_type_ids=__lowerCAmelCase)

									# token_type_ids should put 0 everywhere
									self.assertEqual(sum(tokens_r["""token_type_ids"""])       ,    sum(tokens_p["""token_type_ids"""]))

									# attention_mask should put 1 everywhere, so sum over length should be 1
									self.assertEqual(
									    sum(tokens_r["""attention_mask"""]) / len(tokens_r["""attention_mask"""])       ,    sum(tokens_p["""attention_mask"""]) / len(tokens_p["""attention_mask"""])       ,    )

									lowerCAmelCase   					=  tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""])
									lowerCAmelCase   					=  tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""])

									# Rust correctly handles the space before the mask while python doesnt
									self.assertSequenceEqual(tokens_p["""input_ids"""]       ,    [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2])
									self.assertSequenceEqual(tokens_r["""input_ids"""]       ,    [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2])

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




