'''simple docstring'''

import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
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


lowerCAmelCase_ : str						  =      get_tests_dir("fixtures/test_sentencepiece_no_bos.model")





@require_sentencepiece
@require_tokenizers
class 							lowercase						(						__lowerCamelCase ,				unittest.TestCase ):
   lowerCamelCase_    					=PegasusTokenizer
   lowerCamelCase_    					=PegasusTokenizerFast
   lowerCamelCase_    					=True
   lowerCamelCase_    					=True


   def __UpperCAmelCase       (   self				:	Optional[int])      ->					Union[str, Any]:
         super().setUp()

         # We have a SentencePiece fixture for testing
         lowercase_     =      PegasusTokenizer(__lowerCAmelCase)
         tokenizer.save_pretrained(self.tmpdirname)


   @cached_property
   def __UpperCAmelCase       (   self				:	Optional[Any])      ->					Optional[int]:
         return PegasusTokenizer.from_pretrained("google/pegasus-large")


   def __UpperCAmelCase       (   self				:	Dict   ,		**__lowerCAmelCase				:	Tuple)      ->					PegasusTokenizer:
         return PegasusTokenizer.from_pretrained(self.tmpdirname   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	int   ,		__lowerCAmelCase				:	Optional[int])      ->					List[str]:
         return ("This is a test", "This is a test")


   def __UpperCAmelCase       (   self				:	Union[str, Any])      ->					Tuple:
         lowercase_     =      "</s>"
         lowercase_     =      1

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


   def __UpperCAmelCase       (   self				:	Dict)      ->					Any:
         lowercase_     =      list(self.get_tokenizer().get_vocab().keys())

         self.assertEqual(vocab_keys[0]   ,		"<pad>")
         self.assertEqual(vocab_keys[1]   ,		"</s>")
         self.assertEqual(vocab_keys[-1]   ,		"v")
         self.assertEqual(len(__lowerCAmelCase)   ,		1103)


   def __UpperCAmelCase       (   self				:	Optional[int])      ->					int:
         self.assertEqual(self.get_tokenizer().vocab_size   ,		1103)


   def __UpperCAmelCase       (   self				:	List[Any])      ->					Optional[int]:
         lowercase_     =      self.rust_tokenizer_class.from_pretrained(self.tmpdirname)
         lowercase_     =      self.tokenizer_class.from_pretrained(self.tmpdirname)
         lowercase_     =      (
             "Let's see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"
             " </s> <pad> <pad> <pad>"
         )
         lowercase_     =      rust_tokenizer([raw_input_str]   ,		return_tensors=__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase).input_ids[0]
         lowercase_     =      py_tokenizer([raw_input_str]   ,		return_tensors=__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase).input_ids[0]
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Dict)      ->					Optional[Any]:
         lowercase_     =      self._large_tokenizer
         # <mask_1> masks whole sentence while <mask_2> masks single word
         lowercase_     =      "<mask_1> To ensure a <mask_2> flow of bank resolutions."
         lowercase_     =      [2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
         lowercase_     =      tokenizer([raw_input_str]   ,		return_tensors=__lowerCAmelCase).input_ids[0]
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	List[Any])      ->					Optional[Any]:
         lowercase_     =      self._large_tokenizer
         # The tracebacks for the following asserts are **better** without messages or self.assertEqual
         assert tokenizer.vocab_size == 9_6103
         assert tokenizer.pad_token_id == 0
         assert tokenizer.eos_token_id == 1
         assert tokenizer.offset == 103
         assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
         assert tokenizer.unk_token == "<unk>"
         assert tokenizer.model_max_length == 1024
         lowercase_     =      "To ensure a smooth flow of bank resolutions."
         lowercase_     =      [413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
         lowercase_     =      tokenizer([raw_input_str]   ,		return_tensors=__lowerCAmelCase).input_ids[0]
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)
         assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]


   @require_torch
   def __UpperCAmelCase       (   self				:	Any)      ->					Any:
         lowercase_     =      ["This is going to be way too long." * 150, "short example"]
         lowercase_     =      ["not super long but more than 5 tokens", "tiny"]
         lowercase_     =      self._large_tokenizer(__lowerCAmelCase   ,		padding=__lowerCAmelCase   ,		truncation=__lowerCAmelCase   ,		return_tensors="pt")
         lowercase_     =      self._large_tokenizer(
             text_target=__lowerCAmelCase   ,		max_length=5   ,		padding=__lowerCAmelCase   ,		truncation=__lowerCAmelCase   ,		return_tensors="pt")

         assert batch.input_ids.shape == (2, 1024)
         assert batch.attention_mask.shape == (2, 1024)
         assert targets["input_ids"].shape == (2, 5)
         assert len(__lowerCAmelCase) == 2  # input_ids, attention_mask.


   @slow
   def __UpperCAmelCase       (   self				:	List[Any])      ->					Tuple:
         # fmt: off
         lowercase_     =      {"input_ids": [[3_8979, 143, 1_8485, 606, 130, 2_6669, 8_7686, 121, 5_4189, 1129, 111, 2_6669, 8_7686, 121, 9114, 1_4787, 121, 1_3249, 158, 592, 956, 121, 1_4621, 3_1576, 143, 6_2613, 108, 9688, 930, 4_3430, 1_1562, 6_2613, 304, 108, 1_1443, 897, 108, 9314, 1_7415, 6_3399, 108, 1_1443, 7614, 1_8316, 118, 4284, 7148, 1_2430, 143, 1400, 2_5703, 158, 111, 4284, 7148, 1_1772, 143, 2_1297, 1064, 158, 122, 204, 3506, 1754, 1133, 1_4787, 1581, 115, 3_3224, 4482, 111, 1355, 110, 2_9173, 317, 5_0833, 108, 2_0147, 9_4665, 111, 7_7198, 107, 1], [110, 6_2613, 117, 638, 112, 1133, 121, 2_0098, 1355, 7_9050, 1_3872, 135, 1596, 5_3541, 1352, 141, 1_3039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 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], [139, 1235, 2799, 1_8289, 1_7780, 204, 109, 9474, 1296, 107, 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]], "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, 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, 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=__lowerCAmelCase   ,		model_name="google/bigbird-pegasus-large-arxiv"   ,		revision="ba85d0851d708441f91440d509690f1ab6353415"   ,		)





@require_sentencepiece
@require_tokenizers
class 							lowercase						(						__lowerCamelCase ,				unittest.TestCase ):
   lowerCamelCase_    					=PegasusTokenizer
   lowerCamelCase_    					=PegasusTokenizerFast
   lowerCamelCase_    					=True
   lowerCamelCase_    					=True


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Dict:
         super().setUp()

         # We have a SentencePiece fixture for testing
         lowercase_     =      PegasusTokenizer(__lowerCAmelCase   ,		offset=0   ,		mask_token_sent=__lowerCAmelCase   ,		mask_token="[MASK]")
         tokenizer.save_pretrained(self.tmpdirname)


   @cached_property
   def __UpperCAmelCase       (   self				:	Union[str, Any])      ->					int:
         return PegasusTokenizer.from_pretrained("google/bigbird-pegasus-large-arxiv")


   def __UpperCAmelCase       (   self				:	int   ,		**__lowerCAmelCase				:	List[str])      ->					PegasusTokenizer:
         return PegasusTokenizer.from_pretrained(self.tmpdirname   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	Dict)      ->					str:
         return ("This is a test", "This is a test")


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Union[str, Any]:
         lowercase_     =      self.rust_tokenizer_class.from_pretrained(self.tmpdirname)
         lowercase_     =      self.tokenizer_class.from_pretrained(self.tmpdirname)
         lowercase_     =      (
             "Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"
             " <pad> <pad> <pad>"
         )
         lowercase_     =      rust_tokenizer([raw_input_str]   ,		return_tensors=__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase).input_ids[0]
         lowercase_     =      py_tokenizer([raw_input_str]   ,		return_tensors=__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase).input_ids[0]
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)


   @require_torch
   def __UpperCAmelCase       (   self				:	List[Any])      ->					Dict:
         lowercase_     =      ["This is going to be way too long." * 1000, "short example"]
         lowercase_     =      ["not super long but more than 5 tokens", "tiny"]
         lowercase_     =      self._large_tokenizer(__lowerCAmelCase   ,		padding=__lowerCAmelCase   ,		truncation=__lowerCAmelCase   ,		return_tensors="pt")
         lowercase_     =      self._large_tokenizer(
             text_target=__lowerCAmelCase   ,		max_length=5   ,		padding=__lowerCAmelCase   ,		truncation=__lowerCAmelCase   ,		return_tensors="pt")

         assert batch.input_ids.shape == (2, 4096)
         assert batch.attention_mask.shape == (2, 4096)
         assert targets["input_ids"].shape == (2, 5)
         assert len(__lowerCAmelCase) == 2  # input_ids, attention_mask.


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Optional[int]:
         lowercase_     =      (
             "This is an example string that is used to test the original TF implementation against the HF"
             " implementation"
         )

         lowercase_     =      self._large_tokenizer(__lowerCAmelCase).input_ids

         self.assertListEqual(
             __lowerCAmelCase   ,		[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 2_5016, 3137, 464, 109, 2_6955, 3137, 1]   ,		)







'''simple docstring'''

import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa
import pyarrow.json as paj

import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline


lowerCAmelCase_ : Union[str, Any]						  =      datasets.utils.logging.get_logger(__name__)





@dataclass
class 							lowercase						(						datasets.BuilderConfig ):
   lowerCamelCase_    					=None
   lowerCamelCase_    					="utf-8"
   lowerCamelCase_    					=None
   lowerCamelCase_    					=None
   lowerCamelCase_    					=True  # deprecated
   lowerCamelCase_    					=None  # deprecated
   lowerCamelCase_    					=1_0 << 2_0  # 10MB
   lowerCamelCase_    					=None





class 							lowercase						(						datasets.ArrowBasedBuilder ):
   lowerCamelCase_    					=JsonConfig


   def __UpperCAmelCase       (   self				:	int)      ->					List[str]:
         if self.config.block_size is not None:
               logger.warning("The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead")
               lowercase_     =      self.config.block_size
         if self.config.use_threads is not True:
               logger.warning(
                   "The JSON loader parameter `use_threads` is deprecated and doesn't have any effect anymore.")
         if self.config.newlines_in_values is not None:
               raise ValueError("The JSON loader parameter `newlines_in_values` is no longer supported")
         return datasets.DatasetInfo(features=self.config.features)


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	int)      ->					Any:
         if not self.config.data_files:
               raise ValueError(F'At least one data file must be specified, but got data_files={self.config.data_files}')
         lowercase_     =      dl_manager.download_and_extract(self.config.data_files)
         if isinstance(__lowerCAmelCase   ,		(str, list, tuple)):
               lowercase_     =      data_files
               if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase):
                     lowercase_     =      [files]
               lowercase_     =      [dl_manager.iter_files(__lowerCAmelCase) for file in files]
               return [datasets.SplitGenerator(name=datasets.Split.TRAIN   ,		gen_kwargs={"files": files})]
         lowercase_     =      []
         for split_name, files in data_files.items():
               if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase):
                     lowercase_     =      [files]
               lowercase_     =      [dl_manager.iter_files(__lowerCAmelCase) for file in files]
               splits.append(datasets.SplitGenerator(name=__lowerCAmelCase   ,		gen_kwargs={"files": files}))
         return splits


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	pa.Table)      ->					pa.Table:
         if self.config.features is not None:
               # adding missing columns
               for column_name in set(self.config.features) - set(pa_table.column_names):
                     lowercase_     =      self.config.features.arrow_schema.field(__lowerCAmelCase).type
                     lowercase_     =      pa_table.append_column(__lowerCAmelCase   ,		pa.array([None] * len(__lowerCAmelCase)   ,		type=__lowerCAmelCase))
               # more expensive cast to support nested structures with keys in a different order
               # allows str <-> int/float or str to Audio for example
               lowercase_     =      table_cast(__lowerCAmelCase   ,		self.config.features.arrow_schema)
         return pa_table


   def __UpperCAmelCase       (   self				:	List[Any]   ,		__lowerCAmelCase				:	List[Any])      ->					List[Any]:
         for file_idx, file in enumerate(itertools.chain.from_iterable(__lowerCAmelCase)):
               # If the file is one json object and if we need to look at the list of items in one specific field
               if self.config.field is not None:
                     with open(__lowerCAmelCase   ,		encoding=self.config.encoding   ,		errors=self.config.encoding_errors) as f:
                           lowercase_     =      json.load(__lowerCAmelCase)

                     # We keep only the field we are interested in
                     lowercase_     =      dataset[self.config.field]

                     # We accept two format: a list of dicts or a dict of lists
                     if isinstance(__lowerCAmelCase   ,		(list, tuple)):
                           lowercase_     =      set().union(*[row.keys() for row in dataset])
                           lowercase_     =      {col: [row.get(__lowerCAmelCase) for row in dataset] for col in keys}
                     else:
                           lowercase_     =      dataset
                     lowercase_     =      pa.Table.from_pydict(__lowerCAmelCase)
                     yield file_idx, self._cast_table(__lowerCAmelCase)

               # If the file has one json object per line
               else:
                     with open(__lowerCAmelCase   ,		"rb") as f:
                           lowercase_     =      0
                           # Use block_size equal to the chunk size divided by 32 to leverage multithreading
                           # Set a default minimum value of 16kB if the chunk size is really small
                           lowercase_     =      max(self.config.chunksize // 32   ,		16 << 10)
                           lowercase_     =      (
                               self.config.encoding_errors if self.config.encoding_errors is not None else "strict"
                           )
                           while True:
                                 lowercase_     =      f.read(self.config.chunksize)
                                 if not batch:
                                       break
                                 # Finish current line
                                 try:
                                       batch += f.readline()
                                 except (AttributeError, io.UnsupportedOperation):
                                       batch += readline(__lowerCAmelCase)
                                 # PyArrow only accepts utf-8 encoded bytes
                                 if self.config.encoding != "utf-8":
                                       lowercase_     =      batch.decode(self.config.encoding   ,		errors=__lowerCAmelCase).encode("utf-8")
                                 try:
                                       while True:
                                             try:
                                                   lowercase_     =      paj.read_json(
                                                       io.BytesIO(__lowerCAmelCase)   ,		read_options=paj.ReadOptions(block_size=__lowerCAmelCase))
                                                   break
                                             except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
                                                   if (
                                                       isinstance(__lowerCAmelCase   ,		pa.ArrowInvalid)
                                                       and "straddling" not in str(__lowerCAmelCase)
                                                       or block_size > len(__lowerCAmelCase)
                                                   ):
                                                         raise
                                                   else:
                                                         # Increase the block size in case it was too small.
                                                         # The block size will be reset for the next file.
                                                         logger.debug(
                                                             F'Batch of {len(__lowerCAmelCase)} bytes couldn\'t be parsed with block_size={block_size}. Retrying with block_size={block_size * 2}.')
                                                         block_size *= 2
                                 except pa.ArrowInvalid as e:
                                       try:
                                             with open(
                                                 __lowerCAmelCase   ,		encoding=self.config.encoding   ,		errors=self.config.encoding_errors) as f:
                                                   lowercase_     =      json.load(__lowerCAmelCase)
                                       except json.JSONDecodeError:
                                             logger.error(F'Failed to read file \'{file}\' with error {type(__lowerCAmelCase)}: {e}')
                                             raise e
                                       # If possible, parse the file as a list of json objects and exit the loop
                                       if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase):  # list is the only sequence type supported in JSON
                                             try:
                                                   lowercase_     =      set().union(*[row.keys() for row in dataset])
                                                   lowercase_     =      {col: [row.get(__lowerCAmelCase) for row in dataset] for col in keys}
                                                   lowercase_     =      pa.Table.from_pydict(__lowerCAmelCase)
                                             except (pa.ArrowInvalid, AttributeError) as e:
                                                   logger.error(F'Failed to read file \'{file}\' with error {type(__lowerCAmelCase)}: {e}')
                                                   raise ValueError(F'Not able to read records in the JSON file at {file}.') from None
                                             yield file_idx, self._cast_table(__lowerCAmelCase)
                                             break
                                       else:
                                             logger.error(F'Failed to read file \'{file}\' with error {type(__lowerCAmelCase)}: {e}')
                                             raise ValueError(
                                                 F'Not able to read records in the JSON file at {file}. '
                                                 F'You should probably indicate the field of the JSON file containing your records. '
                                                 F'This JSON file contain the following fields: {str(list(dataset.keys()))}. '
                                                 F'Select the correct one and provide it as `field=\'XXX\'` to the dataset loading method. ') from None
                        # Uncomment for debugging (will print the Arrow table size and elements)
                        # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                        # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                                 yield (file_idx, batch_idx), self._cast_table(__lowerCAmelCase)
                                 batch_idx += 1






