



import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english


@require_tokenizers
class   snake_case_ (lowercase__ , unittest.TestCase  ):




       """simple docstring"""






       _lowerCamelCase			    =				RoCBertTokenizer
       _lowerCamelCase			    =				None
       _lowerCamelCase			    =				False
       _lowerCamelCase			    =				True
       _lowerCamelCase			    =				filter_non_english



       def  A_   (     self):

             """simple docstring"""





             super().setUp()

             UpperCAmelCase_  :	int				      =		["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "你", "好", "是", "谁", "a", "b", "c", "d"]
             UpperCAmelCase_  :	int				      =		{}
             UpperCAmelCase_  :	Tuple				      =		{}
             for i, value in enumerate(lowercase):
                   UpperCAmelCase_  :	Tuple				      =		i
                   UpperCAmelCase_  :	int				      =		i
             UpperCAmelCase_  :	Any				      =		os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES["vocab_file"])
             UpperCAmelCase_  :	str				      =		os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES["word_shape_file"])
             UpperCAmelCase_  :	str				      =		os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES["word_pronunciation_file"])
             with open(self.vocab_file     ,"w"     ,encoding="utf-8") as vocab_writer:
                   vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
             with open(self.word_shape_file     ,"w"     ,encoding="utf-8") as word_shape_writer:
                   json.dump(lowercase     ,lowercase     ,ensure_ascii=lowercase)
             with open(self.word_pronunciation_file     ,"w"     ,encoding="utf-8") as word_pronunciation_writer:
                   json.dump(lowercase     ,lowercase     ,ensure_ascii=lowercase)



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Dict				      =		self.tokenizer_class(self.vocab_file     ,self.word_shape_file     ,self.word_pronunciation_file)

             UpperCAmelCase_  :	Dict				      =		tokenizer.tokenize("你好[SEP]你是谁")
             self.assertListEqual(lowercase     ,["你", "好", "[SEP]", "你", "是", "谁"])
             self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase)     ,[5, 6, 2, 5, 7, 8])
             self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(lowercase)     ,[5, 6, 2, 5, 7, 8])
             self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(lowercase)     ,[5, 6, 2, 5, 7, 8])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	int				      =		RoCBertBasicTokenizer()

             self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz")     ,["ah", "\u535A", "\u63A8", "zz"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Any				      =		RoCBertBasicTokenizer(do_lower_case=lowercase)

             self.assertListEqual(
                 tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  ")     ,["hello", "!", "how", "are", "you", "?"])
             self.assertListEqual(tokenizer.tokenize("H\u00E9llo")     ,["hello"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Union[str, Any]				      =		RoCBertBasicTokenizer(do_lower_case=lowercase     ,strip_accents=lowercase)

             self.assertListEqual(
                 tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")     ,["hällo", "!", "how", "are", "you", "?"])
             self.assertListEqual(tokenizer.tokenize("H\u00E9llo")     ,["h\u00E9llo"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[str]				      =		RoCBertBasicTokenizer(do_lower_case=lowercase     ,strip_accents=lowercase)

             self.assertListEqual(
                 tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")     ,["hallo", "!", "how", "are", "you", "?"])
             self.assertListEqual(tokenizer.tokenize("H\u00E9llo")     ,["hello"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[Any]				      =		RoCBertBasicTokenizer(do_lower_case=lowercase)

             self.assertListEqual(
                 tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")     ,["hallo", "!", "how", "are", "you", "?"])
             self.assertListEqual(tokenizer.tokenize("H\u00E9llo")     ,["hello"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Union[str, Any]				      =		RoCBertBasicTokenizer(do_lower_case=lowercase)

             self.assertListEqual(
                 tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  ")     ,["HeLLo", "!", "how", "Are", "yoU", "?"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[Any]				      =		RoCBertBasicTokenizer(do_lower_case=lowercase     ,strip_accents=lowercase)

             self.assertListEqual(
                 tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")     ,["HäLLo", "!", "how", "Are", "yoU", "?"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	int				      =		RoCBertBasicTokenizer(do_lower_case=lowercase     ,strip_accents=lowercase)

             self.assertListEqual(
                 tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")     ,["HaLLo", "!", "how", "Are", "yoU", "?"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Optional[int]				      =		RoCBertBasicTokenizer(do_lower_case=lowercase     ,never_split=["[UNK]"])

             self.assertListEqual(
                 tokenizer.tokenize(" \tHeLLo!how  \n Are yoU? [UNK]")     ,["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	str				      =		["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"]

             UpperCAmelCase_  :	str				      =		{}
             for i, token in enumerate(lowercase):
                   UpperCAmelCase_  :	Union[str, Any]				      =		i
             UpperCAmelCase_  :	Any				      =		RoCBertWordpieceTokenizer(vocab=lowercase     ,unk_token="[UNK]")

             self.assertListEqual(tokenizer.tokenize("")     ,[])

             self.assertListEqual(tokenizer.tokenize("unwanted running")     ,["un", "##want", "##ed", "runn", "##ing"])

             self.assertListEqual(tokenizer.tokenize("unwantedX running")     ,["[UNK]", "runn", "##ing"])



       def  A_   (     self):

             """simple docstring"""





             self.assertTrue(_is_whitespace(" "))
             self.assertTrue(_is_whitespace("\t"))
             self.assertTrue(_is_whitespace("\r"))
             self.assertTrue(_is_whitespace("\n"))
             self.assertTrue(_is_whitespace("\u00A0"))

             self.assertFalse(_is_whitespace("A"))
             self.assertFalse(_is_whitespace("-"))



       def  A_   (     self):

             """simple docstring"""





             self.assertTrue(_is_control("\u0005"))

             self.assertFalse(_is_control("A"))
             self.assertFalse(_is_control(" "))
             self.assertFalse(_is_control("\t"))
             self.assertFalse(_is_control("\r"))



       def  A_   (     self):

             """simple docstring"""





             self.assertTrue(_is_punctuation("-"))
             self.assertTrue(_is_punctuation("$"))
             self.assertTrue(_is_punctuation("`"))
             self.assertTrue(_is_punctuation("."))

             self.assertFalse(_is_punctuation("A"))
             self.assertFalse(_is_punctuation(" "))



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	int				      =		self.get_tokenizer()

             # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
             self.assertListEqual([tokenizer.tokenize(lowercase) for t in ["Test", "\xad", "test"]]     ,[["[UNK]"], [], ["[UNK]"]])

             if self.test_rust_tokenizer:
                   UpperCAmelCase_  :	Dict				      =		self.get_rust_tokenizer()
                   self.assertListEqual(
                       [rust_tokenizer.tokenize(lowercase) for t in ["Test", "\xad", "test"]]     ,[["[UNK]"], [], ["[UNK]"]])



       def  A_   (     self):

             """simple docstring"""





             for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                   with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
                         UpperCAmelCase_  :	int				      =		self.rust_tokenizer_class.from_pretrained(lowercase     ,**lowercase)

                         UpperCAmelCase_  :	Tuple				      =		F"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
                         UpperCAmelCase_  :	str				      =		tokenizer_r.encode_plus(
                             lowercase     ,return_attention_mask=lowercase     ,return_token_type_ids=lowercase     ,return_offsets_mapping=lowercase     ,add_special_tokens=lowercase     ,)

                         UpperCAmelCase_  :	Optional[int]				      =		tokenizer_r.do_lower_case if hasattr(lowercase     ,"do_lower_case") else False
                         UpperCAmelCase_  :	Optional[Any]				      =		(
                             [
                                 ((0, 0), tokenizer_r.cls_token),
                                 ((0, 1), "A"),
                                 ((1, 2), ","),
                                 ((3, 5), "na"),
                                 ((5, 6), "##ï"),
                                 ((6, 8), "##ve"),
                                 ((9, 15), tokenizer_r.mask_token),
                                 ((16, 21), "Allen"),
                                 ((21, 23), "##NL"),
                                 ((23, 24), "##P"),
                                 ((25, 33), "sentence"),
                                 ((33, 34), "."),
                                 ((0, 0), tokenizer_r.sep_token),
                             ]
                             if not do_lower_case
                             else [
                                 ((0, 0), tokenizer_r.cls_token),
                                 ((0, 1), "a"),
                                 ((1, 2), ","),
                                 ((3, 8), "naive"),
                                 ((9, 15), tokenizer_r.mask_token),
                                 ((16, 21), "allen"),
                                 ((21, 23), "##nl"),
                                 ((23, 24), "##p"),
                                 ((25, 33), "sentence"),
                                 ((33, 34), "."),
                                 ((0, 0), tokenizer_r.sep_token),
                             ]
                         )

                         self.assertEqual(
                             [e[1] for e in expected_results]     ,tokenizer_r.convert_ids_to_tokens(tokens["input_ids"]))
                         self.assertEqual([e[0] for e in expected_results]     ,tokens["offset_mapping"])



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Union[str, Any]				      =		["的", "人", "有"]
             UpperCAmelCase_  :	str				      =		"".join(lowercase)
             for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                   with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
                         UpperCAmelCase_  :	Tuple				      =		True
                         UpperCAmelCase_  :	Optional[Any]				      =		self.tokenizer_class.from_pretrained(lowercase     ,**lowercase)
                         UpperCAmelCase_  :	Union[str, Any]				      =		self.rust_tokenizer_class.from_pretrained(lowercase     ,**lowercase)

                         UpperCAmelCase_  :	Optional[int]				      =		tokenizer_p.encode(lowercase     ,add_special_tokens=lowercase)
                         UpperCAmelCase_  :	Optional[Any]				      =		tokenizer_r.encode(lowercase     ,add_special_tokens=lowercase)

                         UpperCAmelCase_  :	Union[str, Any]				      =		tokenizer_r.convert_ids_to_tokens(lowercase)
                         UpperCAmelCase_  :	List[Any]				      =		tokenizer_p.convert_ids_to_tokens(lowercase)

                         # it is expected that each Chinese character is not preceded by "##"
                         self.assertListEqual(lowercase     ,lowercase)
                         self.assertListEqual(lowercase     ,lowercase)

                         UpperCAmelCase_  :	int				      =		False
                         UpperCAmelCase_  :	Any				      =		self.rust_tokenizer_class.from_pretrained(lowercase     ,**lowercase)
                         UpperCAmelCase_  :	Optional[int]				      =		self.tokenizer_class.from_pretrained(lowercase     ,**lowercase)

                         UpperCAmelCase_  :	Union[str, Any]				      =		tokenizer_r.encode(lowercase     ,add_special_tokens=lowercase)
                         UpperCAmelCase_  :	Union[str, Any]				      =		tokenizer_p.encode(lowercase     ,add_special_tokens=lowercase)

                         UpperCAmelCase_  :	List[Any]				      =		tokenizer_r.convert_ids_to_tokens(lowercase)
                         UpperCAmelCase_  :	List[Any]				      =		tokenizer_p.convert_ids_to_tokens(lowercase)

                         # it is expected that only the first Chinese character is not preceded by "##".
                         UpperCAmelCase_  :	Dict				      =		[
                             F"""##{token}""" if idx != 0 else token for idx, token in enumerate(lowercase)
                         ]
                         self.assertListEqual(lowercase     ,lowercase)
                         self.assertListEqual(lowercase     ,lowercase)



       @slow
       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Union[str, Any]				      =		self.tokenizer_class(self.vocab_file     ,self.word_shape_file     ,self.word_pronunciation_file)

             UpperCAmelCase_  :	List[Any]				      =		tokenizer.encode("你好"     ,add_special_tokens=lowercase)
             UpperCAmelCase_  :	int				      =		tokenizer.encode("你是谁"     ,add_special_tokens=lowercase)

             UpperCAmelCase_  :	Any				      =		tokenizer.build_inputs_with_special_tokens(lowercase)
             UpperCAmelCase_  :	Optional[Any]				      =		tokenizer.build_inputs_with_special_tokens(lowercase     ,lowercase)

             assert encoded_sentence == [1] + text + [2]
             assert encoded_pair == [1] + text + [2] + text_a + [2]



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[Any]				      =		self.get_tokenizers(do_lower_case=lowercase)
             for tokenizer in tokenizers:
                   with self.subTest(F"""{tokenizer.__class__.__name__}"""):
                         UpperCAmelCase_  :	Union[str, Any]				      =		"你好，你是谁"
                         UpperCAmelCase_  :	Dict				      =		tokenizer.tokenize(lowercase)
                         UpperCAmelCase_  :	Tuple				      =		tokenizer.convert_tokens_to_ids(lowercase)
                         UpperCAmelCase_  :	int				      =		tokenizer.convert_tokens_to_shape_ids(lowercase)
                         UpperCAmelCase_  :	Dict				      =		tokenizer.convert_tokens_to_pronunciation_ids(lowercase)
                         UpperCAmelCase_  :	Any				      =		tokenizer.prepare_for_model(
                             lowercase     ,lowercase     ,lowercase     ,add_special_tokens=lowercase)

                         UpperCAmelCase_  :	Optional[int]				      =		tokenizer.encode_plus(lowercase     ,add_special_tokens=lowercase)

                         self.assertEqual(lowercase     ,lowercase)





from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


__lowerCamelCase         =			logging.get_logger(__name__)

__lowerCamelCase         =			{
    '''google/umt5-small''': '''https://huggingface.co/google/umt5-small/resolve/main/config.json''',
    # See all umt5 models at https://huggingface.co/models?filter=umt5
}


class   snake_case_ (lowercase__  ):




       """simple docstring"""






       _lowerCamelCase			    =				"""umt5"""
       _lowerCamelCase			    =				["""past_key_values"""]



       def __init__(     self     ,lowercase=250112     ,lowercase=512     ,lowercase=64     ,lowercase=1024     ,lowercase=8     ,lowercase=None     ,lowercase=6     ,lowercase=32     ,lowercase=128     ,lowercase=0.1     ,lowercase=1E-6     ,lowercase=1.0     ,lowercase="gated-gelu"     ,lowercase=True     ,lowercase=True     ,lowercase="T5Tokenizer"     ,lowercase=True     ,lowercase=0     ,lowercase=1     ,lowercase=0     ,**lowercase     ,):

             """simple docstring"""





             super().__init__(
                 is_encoder_decoder=lowercase     ,tokenizer_class=lowercase     ,tie_word_embeddings=lowercase     ,pad_token_id=lowercase     ,eos_token_id=lowercase     ,decoder_start_token_id=lowercase     ,**lowercase     ,)
             UpperCAmelCase_  :	Optional[int]				      =		vocab_size
             UpperCAmelCase_  :	Any				      =		d_model
             UpperCAmelCase_  :	Any				      =		d_kv
             UpperCAmelCase_  :	int				      =		d_ff
             UpperCAmelCase_  :	Tuple				      =		num_layers
             UpperCAmelCase_  :	int				      =		(
                 num_decoder_layers if num_decoder_layers is not None else self.num_layers
             )  # default = symmetry
             UpperCAmelCase_  :	Optional[int]				      =		num_heads
             UpperCAmelCase_  :	str				      =		relative_attention_num_buckets
             UpperCAmelCase_  :	Any				      =		relative_attention_max_distance
             UpperCAmelCase_  :	Optional[Any]				      =		dropout_rate
             UpperCAmelCase_  :	Union[str, Any]				      =		layer_norm_epsilon
             UpperCAmelCase_  :	Optional[Any]				      =		initializer_factor
             UpperCAmelCase_  :	int				      =		feed_forward_proj
             UpperCAmelCase_  :	str				      =		use_cache

             UpperCAmelCase_  :	List[str]				      =		self.feed_forward_proj.split("-")
             UpperCAmelCase_  :	Any				      =		act_info[-1]
             UpperCAmelCase_  :	Optional[int]				      =		act_info[0] == "gated"

             if len(lowercase) > 1 and act_info[0] != "gated" or len(lowercase) > 2:
                   raise ValueError(
                       F"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
                       "Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. "
                       "'gated-gelu' or 'relu'")

             if feed_forward_proj == "gated-gelu":
                   UpperCAmelCase_  :	Tuple				      =		"gelu_new"



       @property
       def  A_   (     self):

             """simple docstring"""





             return self.d_model



       @property
       def  A_   (     self):

             """simple docstring"""





             return self.num_heads



       @property
       def  A_   (     self):

             """simple docstring"""





             return self.num_layers


class   snake_case_ (lowercase__  ):




       """simple docstring"""






       @property
       # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	int				      =		{
                 "input_ids": {0: "batch", 1: "encoder_sequence"},
                 "attention_mask": {0: "batch", 1: "encoder_sequence"},
             }
             if self.use_past:
                   UpperCAmelCase_  :	Union[str, Any]				      =		"past_encoder_sequence + sequence"
                   UpperCAmelCase_  :	Optional[int]				      =		{0: "batch"}
                   UpperCAmelCase_  :	Union[str, Any]				      =		{0: "batch", 1: "past_decoder_sequence + sequence"}
             else:
                   UpperCAmelCase_  :	Optional[int]				      =		{0: "batch", 1: "decoder_sequence"}
                   UpperCAmelCase_  :	Dict				      =		{0: "batch", 1: "decoder_sequence"}

             if self.use_past:
                   self.fill_with_past_key_values_(lowercase     ,direction="inputs")

             return common_inputs



       @property
       # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
       def  A_   (     self):

             """simple docstring"""





             return 13



       @property
       def  A_   (     self):

             """simple docstring"""





             return 5E-4
