
# 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


_A						      =				logging.get_logger(__name__)

_A						      =				{}
_A						      =				{}
_A						      =				{}



def 		lowercase_    (     A__				,	A__				,	A__ = None				,	)							->							Any:
    """simple docstring"""

    snake_case				  =      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__})'	)
    snake_case				  =      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})'	)
        snake_case				  =      format_type



def 		lowercase_    (     A__				,	A__				,	A__ = None	)							->							List[Any]:
    """simple docstring"""

    snake_case				  =      aliases if aliases is not None else []
    for alias in set(aliases + [format_type]	):
        snake_case				  =      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:
    _A						      =				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:
    _A						      =				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:
    _A						      =				ValueError("JAX needs to be installed to be able to return JAX arrays.")
    _register_unavailable_formatter(_jax_error, "jax", aliases=[])



def 		lowercase_    (     A__	)							->							Optional[str]:
    """simple docstring"""

    if format_type in _FORMAT_TYPES_ALIASES:
        return _FORMAT_TYPES_ALIASES[format_type]
    else:
        return format_type





def 		lowercase_    (     A__				,	**A__	)							->							Formatter:
    """simple docstring"""

    snake_case				  =      get_format_type_from_alias(A__	)
    if format_type in _FORMAT_TYPES:
        return _FORMAT_TYPES[format_type](**A__	)
    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 os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin







class   lowerCamelCase	(						A_							,				unittest.TestCase						):
     UpperCAmelCase__       :							str     =	PhobertTokenizer
     UpperCAmelCase__       :							List[Any]     =	False





     def 	UpperCAmelCase(self   :					Union[str, Any]     )		->		List[str]:
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         snake_case				  =      ["T@@", "i", "I", "R@@", "r", "e@@"]
         snake_case				  =      dict(zip(_A       ,					range(len(_A     )     )     )     )
         snake_case				  =      ["#version: 0.2", "l à</w>"]
         snake_case				  =      {"unk_token": "<unk>"}

         snake_case				  =      os.path.join(self.tmpdirname       ,					VOCAB_FILES_NAMES["vocab_file"]     )
         snake_case				  =      os.path.join(self.tmpdirname       ,					VOCAB_FILES_NAMES["merges_file"]     )

         with open(self.vocab_file       ,					"w"       ,					encoding="utf-8"     ) as fp:
             for token in vocab_tokens:
                 fp.write(f'{token} {vocab_tokens[token]}\n'     )
         with open(self.merges_file       ,					"w"       ,					encoding="utf-8"     ) as fp:
             fp.write("\n".join(_A     )     )





     def 	UpperCAmelCase(self   :					Optional[int]       ,					**_A   :					Optional[int]     )		->		Union[str, Any]:
         kwargs.update(self.special_tokens_map     )
         return PhobertTokenizer.from_pretrained(self.tmpdirname       ,					**_A     )





     def 	UpperCAmelCase(self   :					Tuple       ,					_A   :					Optional[Any]     )		->		str:
         snake_case				  =      "Tôi là VinAI Research"
         snake_case				  =      "T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
         return input_text, output_text





     def 	UpperCAmelCase(self   :					Any     )		->		Union[str, Any]:
         snake_case				  =      PhobertTokenizer(self.vocab_file       ,					self.merges_file       ,					**self.special_tokens_map     )
         snake_case				  =      "Tôi là VinAI Research"
         snake_case				  =      "T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
         snake_case				  =      tokenizer.tokenize(_A     )
         print(_A     )
         self.assertListEqual(_A       ,					_A     )

         snake_case				  =      tokens + [tokenizer.unk_token]

         snake_case				  =      [4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_A     )       ,					_A     )

