





import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin







class        __lowerCAmelCase (					UpperCamelCase__		,       unittest.TestCase):
      _lowercase       :      Union[str, Any]        =    SpeechaTextaTokenizer
      _lowercase       :      List[str]        =    False







      def      _lowercase						(					self							)     ->		int:



        '''simple docstring'''




        super().setUp()

        a__			:      int            ="<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab".split(" "							)
        a__			:      str            =["he re</w> 123", "here a 1456"]
        a__			:      Any            =dict(zip(lowerCAmelCase__	,   range(len(lowerCAmelCase__							)							)							)							)

        a__			:      Optional[int]            ={"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

        a__			:      Union[str, Any]            =tempfile.mkdtemp()
        a__			:      int            =os.path.join(self.tmpdirname	,   VOCAB_FILES_NAMES["vocab_file"]							)
        a__			:      List[str]            =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"							) as fp:
          fp.write("\n".join(lowerCAmelCase__							)							)







      def      _lowercase						(					self							)     ->		int:



        '''simple docstring'''




        a__			:      Optional[Any]            =list(self.get_tokenizer().get_vocab().keys()							)

        self.assertEqual(vocab_keys[0]	,   "<s>"							)
        self.assertEqual(vocab_keys[1]	,   "<pad>"							)
        self.assertEqual(vocab_keys[-1]	,   "vocab"							)
        self.assertEqual(len(lowerCAmelCase__							)	,   1_4							)







      def      _lowercase						(					self							)     ->		Optional[Any]:



        '''simple docstring'''




        self.assertEqual(self.get_tokenizer().vocab_size	,   1_4							)







      def      _lowercase						(					self							)     ->		Optional[int]:



        '''simple docstring'''




        a__			:      List[Any]            =SpeechaTextaTokenizer.from_pretrained(self.tmpdirname							)

        # make sure @@ is correctly concatenated
        a__			:      List[str]            =[4, 6, 8, 7, 1_0]  # ["here@@", "couple", "words", "of@@", "the"]
        a__			:      Any            =tokenizer.decode(lowerCAmelCase__							)

        self.assertTrue(output_string == "herecouple words ofthe"							)







      def      _lowercase						(					self							)     ->		Optional[Any]:



        '''simple docstring'''




        a__			:      Dict            =SpeechaTextaTokenizer.from_pretrained(self.tmpdirname							)

        with tempfile.TemporaryDirectory() as tmp_dirname:
          tokenizer.save_pretrained(lowerCAmelCase__							)
          os.remove(os.path.join(lowerCAmelCase__	,   "merges.txt"							)							)

          # load tokenizer without merges file should not throw an error
          a__			:      Any            =SpeechaTextaTokenizer.from_pretrained(lowerCAmelCase__							)

        with tempfile.TemporaryDirectory() as tmp_dirname:
          # save tokenizer and load again
          tokenizer.save_pretrained(lowerCAmelCase__							)
          a__			:      Optional[int]            =SpeechaTextaTokenizer.from_pretrained(lowerCAmelCase__							)

        self.assertIsNotNone(lowerCAmelCase__							)







      def      _lowercase						(					self							)     ->		Optional[int]:



        '''simple docstring'''




        if not self.test_slow_tokenizer:
          return

        a__			:      List[Any]            =inspect.signature(self.tokenizer_class.__init__							)
        a__			:      List[str]            =self.get_tokenizer()

        for parameter_name, parameter in signature.parameters.items():
          if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
            self.assertIn(lowerCAmelCase__	,   tokenizer.init_kwargs							)













import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases







class        __lowerCAmelCase (					UpperCamelCase__):







      def      _lowercase						(					self	,   lowerCAmelCase__	,   lowerCAmelCase__=False							)     ->		List[Any]:



        '''simple docstring'''




        a__      ,							a__      ,							a__			:      Optional[int]            =(
            filename_skip_take["filename"],
            filename_skip_take["skip"] if "skip" in filename_skip_take else None,
            filename_skip_take["take"] if "take" in filename_skip_take else None,
        )
        open(os.path.join(lowerCAmelCase__							)	,   "wb"							).close()
        a__			:      Optional[int]            =pa.Table.from_pydict({"filename": [Path(lowerCAmelCase__							).name] * 1_0_0}							)
        if take == -1:
          a__			:      int            =len(lowerCAmelCase__							) - skip
        if skip is not None and take is not None:
          a__			:      Optional[Any]            =pa_table.slice(lowerCAmelCase__	,   lowerCAmelCase__							)
        return pa_table







class        __lowerCAmelCase (					UpperCamelCase__):







      def      _lowercase						(					self							)     ->		str:



        '''simple docstring'''




        a__			:      List[str]            ="my_name"
        a__			:      List[Any]            =SplitInfo(name="train"	,   num_examples=1_0_0							)
        a__			:      List[str]            =SplitInfo(name="test"	,   num_examples=1_0_0							)
        a__			:      List[Any]            =[train_info, test_info]
        a__			:      Union[str, Any]            =SplitDict()
        split_dict.add(lowerCAmelCase__							)
        split_dict.add(lowerCAmelCase__							)
        a__			:      Dict            =DatasetInfo(splits=lowerCAmelCase__							)

        with tempfile.TemporaryDirectory() as tmp_dir:
          a__			:      Optional[Any]            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)

          a__			:      Any            ="test[:33%]"
          a__			:      int            =Dataset(**reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							)							)
          self.assertEqual(dset["filename"][0]	,   F'''{name}-test'''							)
          self.assertEqual(dset.num_rows	,   3_3							)
          self.assertEqual(dset.num_columns	,   1							)

          a__			:      Tuple            =["train", "test[:33%]"]
          a__			:      str            =[Split.TRAIN, ReadInstruction.from_spec("test[:33%]"							)]
          for instructions in [instructionsa, instructionsa]:
            a__			:      Optional[int]            =[reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							) for instr in instructions]
            a__      ,							a__			:      Optional[int]            =(Dataset(**lowerCAmelCase__							) for dataset_kwargs in datasets_kwargs)
            self.assertEqual(train_dset["filename"][0]	,   F'''{name}-train'''							)
            self.assertEqual(train_dset.num_rows	,   1_0_0							)
            self.assertEqual(train_dset.num_columns	,   1							)
            self.assertIsInstance(train_dset.split	,   lowerCAmelCase__							)
            self.assertEqual(str(train_dset.split							)	,   "train"							)
            self.assertEqual(test_dset["filename"][0]	,   F'''{name}-test'''							)
            self.assertEqual(test_dset.num_rows	,   3_3							)
            self.assertEqual(test_dset.num_columns	,   1							)
            self.assertIsInstance(test_dset.split	,   lowerCAmelCase__							)
            self.assertEqual(str(test_dset.split							)	,   "test[:33%]"							)
            del train_dset, test_dset







      def      _lowercase						(					self							)     ->		Optional[Any]:



        '''simple docstring'''




        a__			:      Any            ="my_name"
        a__			:      List[Any]            =SplitInfo(name="train"	,   num_examples=1_0_0_0	,   shard_lengths=[1_0_0] * 1_0							)
        a__			:      Optional[Any]            =[train_info]
        a__			:      Any            =SplitDict()
        split_dict.add(lowerCAmelCase__							)
        a__			:      Any            =DatasetInfo(splits=lowerCAmelCase__							)

        with tempfile.TemporaryDirectory() as tmp_dir:
          a__			:      Optional[int]            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)

          a__			:      Union[str, Any]            ="train[:33%]"
          a__			:      Union[str, Any]            =Dataset(**reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							)							)
          self.assertEqual(dset["filename"][0]	,   F'''{name}-train-00000-of-00010'''							)
          self.assertEqual(dset["filename"][-1]	,   F'''{name}-train-00003-of-00010'''							)
          self.assertEqual(dset.num_rows	,   3_3_0							)
          self.assertEqual(dset.num_columns	,   1							)







      def      _lowercase						(					self							)     ->		List[str]:



        '''simple docstring'''




        a__			:      Dict            =SplitInfo(name="train"	,   num_examples=1_0_0							)
        a__			:      str            =SplitInfo(name="test"	,   num_examples=1_0_0							)
        a__			:      int            =SplitDict()
        split_dict.add(lowerCAmelCase__							)
        split_dict.add(lowerCAmelCase__							)
        a__			:      int            =DatasetInfo(splits=lowerCAmelCase__							)

        with tempfile.TemporaryDirectory() as tmp_dir:
          a__			:      Tuple            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)

          a__			:      Tuple            =[
              {"filename": os.path.join(lowerCAmelCase__	,   "train"							)},
              {"filename": os.path.join(lowerCAmelCase__	,   "test"							), "skip": 1_0, "take": 1_0},
          ]
          a__			:      Optional[Any]            =Dataset(**reader.read_files(lowerCAmelCase__	,   original_instructions="train+test[10:20]"							)							)
          self.assertEqual(dset.num_rows	,   1_1_0							)
          self.assertEqual(dset.num_columns	,   1							)
          del dset
@pytest.mark.parametrize("in_memory" , [False, True]		)
def   _A (	SCREAMING_SNAKE_CASE  :     Optional[Any] , SCREAMING_SNAKE_CASE  :     Optional[Any] , SCREAMING_SNAKE_CASE  :     Optional[Any]		):





  """simple docstring"""



  a__			:      int            =arrow_file
  with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
    a__			:      str            =ArrowReader.read_table(SCREAMING_SNAKE_CASE , in_memory=SCREAMING_SNAKE_CASE		)
  assert table.shape == dataset.data.shape
  assert set(table.column_names		) == set(dataset.data.column_names		)
  assert dict(table.to_pydict()		) == dict(dataset.data.to_pydict()		)  # to_pydict returns OrderedDict
@pytest.mark.parametrize("in_memory" , [False, True]		)
def   _A (	SCREAMING_SNAKE_CASE  :     Tuple , SCREAMING_SNAKE_CASE  :     List[Any] , SCREAMING_SNAKE_CASE  :     str		):





  """simple docstring"""



  a__			:      Optional[int]            =arrow_file
  a__			:      Tuple            =ArrowReader("" , SCREAMING_SNAKE_CASE		)
  with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
    a__			:      Union[str, Any]            =reader.read_files([{"filename": filename}] , in_memory=SCREAMING_SNAKE_CASE		)
  assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
  a__			:      Dict            =dataset_kwargs["arrow_table"]
  assert table.shape == dataset.data.shape
  assert set(table.column_names		) == set(dataset.data.column_names		)
  assert dict(table.to_pydict()		) == dict(dataset.data.to_pydict()		)  # to_pydict returns OrderedDict
def   _A (	):





  """simple docstring"""



  assert ReadInstruction("train" , to=10 , unit="abs"		).to_spec() == "train[:10]"
  assert ReadInstruction("train" , from_=-80 , to=10 , unit="%"		).to_spec() == "train[-80%:10%]"

  a__			:      List[Any]            ="train+test"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_test

  a__			:      Union[str, Any]            ="train[2:10]"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_abs

  a__			:      List[Any]            ="train[15%:-20%]"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_pct

  a__			:      Dict            ="train[:10%](closest)"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == "train[:10%]"

  a__			:      Tuple            ="train[:10%](pct1_dropremainder)"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_pct_rounding

  a__			:      List[Any]            ="train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_test_pct_rounding
def   _A (	):





  """simple docstring"""



  a__			:      Optional[Any]            ="dummy"
  a__			:      Dict            =[SplitInfo(name="train" , num_examples=100		)]
  a__			:      Optional[Any]            ="train[:33%]"
  a__			:      int            ="arrow"
  a__			:      Any            ="prefix"

  a__			:      Tuple            =make_file_instructions(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  assert file_instructions.num_examples == 33
  assert file_instructions.file_instructions == [
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train.arrow'''		), "skip": 0, "take": 33}
  ]

  a__			:      List[str]            =[SplitInfo(name="train" , num_examples=100 , shard_lengths=[10] * 10		)]
  a__			:      Union[str, Any]            =make_file_instructions(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  assert file_instructions.num_examples == 33
  assert file_instructions.file_instructions == [
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00000-of-00010.arrow'''		), "skip": 0, "take": -1},
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00001-of-00010.arrow'''		), "skip": 0, "take": -1},
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00002-of-00010.arrow'''		), "skip": 0, "take": -1},
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00003-of-00010.arrow'''		), "skip": 0, "take": 3},
  ]





@pytest.mark.parametrize("name, expected_exception" , [(None, TypeError), ("", ValueError)]		)
def   _A (	SCREAMING_SNAKE_CASE  :     Tuple , SCREAMING_SNAKE_CASE  :     Tuple		):





  """simple docstring"""



  a__			:      Dict            =[SplitInfo(name="train" , num_examples=100		)]
  a__			:      Any            ="train"
  a__			:      Optional[Any]            ="arrow"
  a__			:      List[Any]            ="prefix_path"
  with pytest.raises(SCREAMING_SNAKE_CASE		):
    a__			:      Optional[Any]            =make_file_instructions(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)






