

'''simple docstring'''

import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


A_       						=							get_tests_dir("fixtures/test_sentencepiece.model")





@require_sentencepiece
class 							_snake_case (       _a	,  unittest.TestCase						):
   _A       :     str       =					XLMProphetNetTokenizer
   _A       :     Union[str, Any]       =					False
   _A       :     List[Any]       =					True
   def     __UpperCamelCase						( self			:      Optional[Any]							):
     super().setUp()

     # We have a SentencePiece fixture for testing
     SCREAMING_SNAKE_CASE:List[str]						      =					XLMProphetNetTokenizer(SCREAMING_SNAKE_CASE__     ,keep_accents=SCREAMING_SNAKE_CASE__							)
     tokenizer.save_pretrained(self.tmpdirname							)
   def     __UpperCamelCase						( self			:      Optional[int]							):
     SCREAMING_SNAKE_CASE:int						      =					"[PAD]"
     SCREAMING_SNAKE_CASE:Any						      =					0

     self.assertEqual(self.get_tokenizer()._convert_token_to_id(SCREAMING_SNAKE_CASE__							)     ,SCREAMING_SNAKE_CASE__							)
     self.assertEqual(self.get_tokenizer()._convert_id_to_token(SCREAMING_SNAKE_CASE__							)     ,SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      Optional[Any]							):
     SCREAMING_SNAKE_CASE:Tuple						      =					list(self.get_tokenizer().get_vocab().keys()							)

     self.assertEqual(vocab_keys[0]     ,"[PAD]"							)
     self.assertEqual(vocab_keys[1]     ,"[CLS]"							)
     self.assertEqual(vocab_keys[-1]     ,"j"							)
     self.assertEqual(len(SCREAMING_SNAKE_CASE__							)     ,1_012							)
   def     __UpperCamelCase						( self			:      Tuple							):
     self.assertEqual(self.get_tokenizer().vocab_size     ,1_012							)
   def     __UpperCamelCase						( self			:      Tuple							):
     SCREAMING_SNAKE_CASE:Any						      =					XLMProphetNetTokenizer(SCREAMING_SNAKE_CASE__     ,keep_accents=SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:Tuple						      =					tokenizer.tokenize("This is a test"							)
     self.assertListEqual(SCREAMING_SNAKE_CASE__     ,["▁This", "▁is", "▁a", "▁t", "est"]							)

     self.assertListEqual(
         tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__							)     ,[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]     ,)

     SCREAMING_SNAKE_CASE:Any						      =					tokenizer.tokenize("I was born in 92000, and this is falsé."							)
     self.assertListEqual(
         SCREAMING_SNAKE_CASE__     ,[
             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",
             ".",
         ]     ,)
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__							)
     self.assertListEqual(
         SCREAMING_SNAKE_CASE__     ,[
             value + tokenizer.fairseq_offset
             for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
         ]     ,)

     SCREAMING_SNAKE_CASE:Optional[int]						      =					tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__							)
     self.assertListEqual(
         SCREAMING_SNAKE_CASE__     ,[
             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     __UpperCamelCase						( self			:      str							):
     return XLMProphetNetTokenizer.from_pretrained("microsoft/xprophetnet-large-wiki100-cased"							)
   @slow
   def     __UpperCamelCase						( self			:      Optional[int]							):
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					"Hello World!"
     SCREAMING_SNAKE_CASE:Any						      =					[35_389, 6_672, 49, 2]
     self.assertListEqual(SCREAMING_SNAKE_CASE__     ,self.big_tokenizer.encode(SCREAMING_SNAKE_CASE__							)							)







   @slow
   def     __UpperCamelCase						( self			:      int							):
     # fmt: off
     SCREAMING_SNAKE_CASE:Tuple						      =					{"input_ids": [[11_073, 82_783, 18, 26, 82_783, 549, 51_540, 248, 17_209, 1_301, 217, 20, 215_186, 1_325, 147, 17_209, 1_301, 217, 20, 56_370, 53, 122_020, 20, 16_477, 27, 87_355, 4_548, 20, 4_728, 78_392, 17, 159_969, 18, 26, 24_491, 629, 15, 538, 22_704, 5_439, 15, 2_788, 24_491, 9_885, 15, 43_534, 605, 15, 814, 18_403, 33_200, 29, 15, 43_534, 24_458, 12_410, 111, 24_966, 83_669, 9_637, 144_068, 26, 850, 22_346, 27, 147, 24_966, 83_669, 83_490, 26, 39_113, 735, 27, 689, 656, 2_800, 1_339, 4_600, 53, 122_020, 115_785, 34, 816, 1_339, 46_887, 18, 147, 53_905, 1_951, 42_238, 41_170, 17_732, 834, 436, 15, 27_523, 98_733, 217, 147, 5_542, 4_981, 930, 17_347, 16, 2], [20_091, 629, 94, 82_786, 58, 490, 20, 1_528, 84, 53_905, 344, 80_592, 110_128, 18_822, 5_267, 1_306, 62, 152_537, 308, 7_997, 401, 124_427, 549, 35_442, 225, 109, 15_055, 25_748, 147, 7_119, 43_712, 34, 767, 135_366, 18, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [592, 63_784, 119_466, 17, 147_808, 88_214, 18, 656, 81, 32, 3_296, 10_280, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "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, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
     # fmt: on

     self.tokenizer_integration_test_util(
         expected_encoding=SCREAMING_SNAKE_CASE__     ,model_name="microsoft/xprophetnet-large-wiki100-cased"     ,revision="1acad1643ddd54a44df6a1b797ada8373685d90e"     ,)









'''simple docstring'''

import inspect
import re
from hashlib import shaaaa
from typing import Dict, List

from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql  # noqa F401
from .text import text





def    A_  ( snake_case ):
  SCREAMING_SNAKE_CASE:List[Any]						      =					[]
  for line in lines:
    SCREAMING_SNAKE_CASE:Any						      =					re.sub(r"#.*"      ,       ""      ,       snake_case )  # remove comments
    if line:
      filtered_lines.append(snake_case )
  SCREAMING_SNAKE_CASE:int						      =					"\n".join(snake_case )

  # Make a hash from all this code
  SCREAMING_SNAKE_CASE:str						      =					full_str.encode("utf-8" )
  return shaaaa(snake_case ).hexdigest()


# get importable module names and hash for caching
A_       						=							{
    "csv": (csv.__name__, _hash_python_lines(inspect.getsource(csv).splitlines())),
    "json": (json.__name__, _hash_python_lines(inspect.getsource(json).splitlines())),
    "pandas": (pandas.__name__, _hash_python_lines(inspect.getsource(pandas).splitlines())),
    "parquet": (parquet.__name__, _hash_python_lines(inspect.getsource(parquet).splitlines())),
    "arrow": (arrow.__name__, _hash_python_lines(inspect.getsource(arrow).splitlines())),
    "text": (text.__name__, _hash_python_lines(inspect.getsource(text).splitlines())),
    "imagefolder": (imagefolder.__name__, _hash_python_lines(inspect.getsource(imagefolder).splitlines())),
    "audiofolder": (audiofolder.__name__, _hash_python_lines(inspect.getsource(audiofolder).splitlines())),
}

# Used to infer the module to use based on the data files extensions
A_       						=							{
    ".csv": ("csv", {}),
    ".tsv": ("csv", {"sep": "\t"}),
    ".json": ("json", {}),
    ".jsonl": ("json", {}),
    ".parquet": ("parquet", {}),
    ".arrow": ("arrow", {}),
    ".txt": ("text", {}),
}
_EXTENSION_TO_MODULE.update({ext: ("imagefolder", {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext.upper(): ("imagefolder", {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext: ("audiofolder", {}) for ext in audiofolder.AudioFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext.upper(): ("audiofolder", {}) for ext in audiofolder.AudioFolder.EXTENSIONS})
A_       						=							{"imagefolder", "audiofolder"}

# Used to filter data files based on extensions given a module name
A_       						=							{}
for _ext, (_module, _) in _EXTENSION_TO_MODULE.items():
    _MODULE_TO_EXTENSIONS.setdefault(_module, []).append(_ext)

_MODULE_TO_EXTENSIONS["imagefolder"].append(".zip")


_MODULE_TO_EXTENSIONS["audiofolder"].append(".zip")






