
# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


lowercase  :					List[str]						    =							logging.get_logger(__name__)

lowercase  :					Dict[Optional[str], Type[Formatter]]						    =							{}
lowercase  :					Dict[Optional[str], str]						    =							{}
lowercase  :					Dict[Optional[str], Exception]						    =							{}







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__ = None					,	) ->    Optional[int]:
       lowercase							:     Optional[int]       	=      aliases if aliases is not None else []
       if format_type in _FORMAT_TYPES:
              logger.warning(
                  f"Overwriting format type \'{format_type}\' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})"				)
       lowercase							:     int       	=      formatter_cls
       for alias in set(aliases + [format_type]				):
              if alias in _FORMAT_TYPES_ALIASES:
                     logger.warning(
                         f"Overwriting format type alias \'{alias}\' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})"				)
              lowercase							:     Union[str, Any]       	=      format_type







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__ = None				) ->    List[str]:
       lowercase							:     Any       	=      aliases if aliases is not None else []
       for alias in set(aliases + [format_type]				):
              lowercase							:     int       	=      unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=["""python"""])
_register_formatter(ArrowFormatter, """arrow""", aliases=["""pa""", """pyarrow"""])
_register_formatter(NumpyFormatter, """numpy""", aliases=["""np"""])
_register_formatter(PandasFormatter, """pandas""", aliases=["""pd"""])
_register_formatter(CustomFormatter, """custom""")

if config.TORCH_AVAILABLE:
  from .torch_formatter import TorchFormatter

  _register_formatter(TorchFormatter, """torch""", aliases=["""pt""", """pytorch"""])
else:
  lowercase  :					str						    =							ValueError("""PyTorch needs to be installed to be able to return PyTorch tensors.""")
  _register_unavailable_formatter(_torch_error, """torch""", aliases=["""pt""", """pytorch"""])

if config.TF_AVAILABLE:
  from .tf_formatter import TFFormatter

  _register_formatter(TFFormatter, """tensorflow""", aliases=["""tf"""])
else:
  lowercase  :					List[str]						    =							ValueError("""Tensorflow needs to be installed to be able to return Tensorflow tensors.""")
  _register_unavailable_formatter(_tf_error, """tensorflow""", aliases=["""tf"""])

if config.JAX_AVAILABLE:
  from .jax_formatter import JaxFormatter

  _register_formatter(JaxFormatter, """jax""", aliases=[])
else:
  lowercase  :					List[str]						    =							ValueError("""JAX needs to be installed to be able to return JAX arrays.""")
  _register_unavailable_formatter(_jax_error, """jax""", aliases=[])







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    Optional[str]:
       if format_type in _FORMAT_TYPES_ALIASES:
              return _FORMAT_TYPES_ALIASES[format_type]
       else:
              return format_type







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	**SCREAMING_SNAKE_CASE__				) ->    Formatter:
       lowercase							:     List[str]       	=      get_format_type_from_alias(__lowerCamelCase				)
       if format_type in _FORMAT_TYPES:
              return _FORMAT_TYPES[format_type](**__lowerCamelCase				)
       if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
              raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
       else:
              raise ValueError(
                  f"Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None				)}, but got \'{format_type}\'"				)






import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 		__lowerCAmelCase	(	__magic_name__      ,       unittest.TestCase ):
							UpperCamelCase__					     =  CLIPTokenizer
							UpperCamelCase__					     =  CLIPTokenizerFast
							UpperCamelCase__					     =  True
							UpperCamelCase__					     =  {}
							UpperCamelCase__					     =  False
							def       lowerCamelCase__							(						self						:str				):







								'''simple docstring'''







								super().setUp()

								# fmt: off
								a										=							["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
								# fmt: on
								a										=							dict(zip(__magic_name__		,      range(len(__magic_name__				)				)				)				)
								a										=							["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>"""]
								a										=							{"""unk_token""": """<unk>"""}

								a										=							os.path.join(self.tmpdirname		,      VOCAB_FILES_NAMES["""vocab_file"""]				)
								a										=							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(__magic_name__				) + """\n"""				)
								with open(self.merges_file		,      """w"""		,      encoding="""utf-8"""				) as fp:
									fp.write("""\n""".join(__magic_name__				)				)
							def       lowerCamelCase__							(						self						:Optional[Any]		,      **__magic_name__						:Union[str, Any]				):







								'''simple docstring'''







								kwargs.update(self.special_tokens_map				)
								return CLIPTokenizer.from_pretrained(self.tmpdirname		,      **__magic_name__				)
							def       lowerCamelCase__							(						self						:int		,      **__magic_name__						:Optional[Any]				):







								'''simple docstring'''







								kwargs.update(self.special_tokens_map				)
								return CLIPTokenizerFast.from_pretrained(self.tmpdirname		,      **__magic_name__				)
							def       lowerCamelCase__							(						self						:int		,      __magic_name__						:List[str]				):







								'''simple docstring'''







								a										=							"""lower newer"""
								a										=							"""lower newer"""
								return input_text, output_text
							def       lowerCamelCase__							(						self						:int				):







								'''simple docstring'''







								a										=							CLIPTokenizer(self.vocab_file		,      self.merges_file		,      **self.special_tokens_map				)
								a										=							"""lower newer"""
								a										=							["""lo""", """w""", """er</w>""", """n""", """e""", """w""", """er</w>"""]
								a										=							tokenizer.tokenize(__magic_name__				)
								self.assertListEqual(__magic_name__		,      __magic_name__				)

								a										=							tokens + [tokenizer.unk_token]
								a										=							[10, 2, 16, 9, 3, 2, 16, 20]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__				)		,      __magic_name__				)
							@require_ftfy
							def       lowerCamelCase__							(						self						:List[Any]				):







								'''simple docstring'''







								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
										a										=							self.tokenizer_class.from_pretrained(__magic_name__		,      **__magic_name__				)
										a										=							self.rust_tokenizer_class.from_pretrained(__magic_name__		,      **__magic_name__				)

										a										=							"""A\n'll 11p223RF☆ho!!to?'d'd''d of a cat to-$''d."""
										a										=							tokenizer_s.tokenize(__magic_name__				)
										a										=							tokenizer_r.tokenize(__magic_name__				)

										self.assertListEqual(__magic_name__		,      __magic_name__				)

										# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
										# with Tilde) encoded in 2 different ways
										a										=							"""xa\u0303y""" + """ """ + """x\xe3y"""
										a										=							tokenizer_s.tokenize(__magic_name__				)
										a										=							tokenizer_r.tokenize(__magic_name__				)

										self.assertListEqual(__magic_name__		,      __magic_name__				)

										# Test that the tokenization is identical on unicode of space type
										a										=							[
										    """\u0009""",  # (horizontal tab, '\t')
										    """\u000B""",  # (vertical tab)
										    """\u000C""",  # (form feed)
										    """\u0020""",  # (space, ' ')
										    """\u200E""",  # (left-to-right mark):w
										    """\u200F""",  # (right-to-left mark)
										]
										for unicode_seq in spaces_unicodes:
											a										=							tokenizer_s.tokenize(__magic_name__				)
											a										=							tokenizer_r.tokenize(__magic_name__				)

											self.assertListEqual(__magic_name__		,      __magic_name__				)

										# Test that the tokenization is identical on unicode of line break type
										a										=							[
										    """\u000A""",  # (line feed, '\n')
										    """\r\n""",  # (carriage return and line feed, '\r\n')
										    """\u000D""",  # (carriage return, '\r')
										    """\r""",  # (carriage return, '\r')
										    """\u000D""",  # (carriage return, '\r')
										    """\u2028""",  # (line separator)
										    """\u2029""",  # (paragraph separator)
										    # "\u0085", # (next line)
										]

										# The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
										# it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
										# space (and thus into an empty list).

										for unicode_seq in line_break_unicodes:
											a										=							tokenizer_s.tokenize(__magic_name__				)
											a										=							tokenizer_r.tokenize(__magic_name__				)

											self.assertListEqual(__magic_name__		,      __magic_name__				)
							def       lowerCamelCase__							(						self						:int				):







								'''simple docstring'''







								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
										a										=							"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
										a										=							F'{text_of_1_token} {text_of_1_token}'

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      )
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (0, len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (len(__magic_name__				) + 1, len(__magic_name__				) + 1 + len(__magic_name__				))		,      )

										a										=							F' {text}'

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      )
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (1, 1 + len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (1 + len(__magic_name__				) + 1, 1 + len(__magic_name__				) + 1 + len(__magic_name__				))		,      )
							def       lowerCamelCase__							(						self						:List[str]				):







								'''simple docstring'''







								with self.assertRaises(__magic_name__				) as context:
									self.rust_tokenizer_class.from_pretrained("""robot-test/old-clip-tokenizer"""				)

								self.assertTrue(
								    context.exception.args[0].startswith(
								        """The `backend_tokenizer` provided does not match the expected format."""				)				)
							@require_ftfy
							def       lowerCamelCase__							(						self						:Tuple				):







								'''simple docstring'''







								super().test_tokenization_python_rust_equals()





							def       lowerCamelCase__							(						self						:Optional[int]				):







								'''simple docstring'''







								pass

