




import os
import unittest

from transformers import RealmTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.realm.tokenization_realm import RealmTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english


@require_tokenizers
class        UpperCAmelCase__				(							UpperCAmelCase__      ,		unittest.TestCase				):



     '''simple docstring'''
     _SCREAMING_SNAKE_CASE      :					Any     					=    RealmTokenizer
     _SCREAMING_SNAKE_CASE      :					List[str]     					=    RealmTokenizerFast
     _SCREAMING_SNAKE_CASE      :					Dict     					=    True
     _SCREAMING_SNAKE_CASE      :					List[Any]     					=    True
     _SCREAMING_SNAKE_CASE      :					List[Any]     					=    filter_non_english
     def        lowerCAmelCase__  (				self	):
            super().setUp()

            a			   =[
                """[UNK]""",
                """[CLS]""",
                """[SEP]""",
                """[PAD]""",
                """[MASK]""",
                """want""",
                """##want""",
                """##ed""",
                """wa""",
                """un""",
                """runn""",
                """##ing""",
                """,""",
                """low""",
                """lowest""",
            ]
            a			   =os.path.join(self.tmpdirname ,    VOCAB_FILES_NAMES["""vocab_file"""]	)
            with open(self.vocab_file ,    """w""" ,    encoding="""utf-8"""	) as vocab_writer:
                   vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]	)	)
     def        lowerCAmelCase__  (				self ,    _lowerCAmelCase	):
            a			   ="""UNwant\u00E9d,running"""
            a			   ="""unwanted, running"""
            return input_text, output_text
     def        lowerCAmelCase__  (				self	):
            a			   =self.tokenizer_class(self.vocab_file	)

            a			   =tokenizer.tokenize("""UNwant\u00E9d,running"""	)
            self.assertListEqual(_lowerCAmelCase ,    ["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]	)
            self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase	) ,    [9, 6, 7, 12, 10, 11]	)
     def        lowerCAmelCase__  (				self	):
            if not self.test_rust_tokenizer:
                   return

            a			   =self.get_tokenizer()
            a			   =self.get_rust_tokenizer()

            a			   ="""UNwant\u00E9d,running"""

            a			   =tokenizer.tokenize(_lowerCAmelCase	)
            a			   =rust_tokenizer.tokenize(_lowerCAmelCase	)
            self.assertListEqual(_lowerCAmelCase ,    _lowerCAmelCase	)

            a			   =tokenizer.encode(_lowerCAmelCase ,    add_special_tokens=_lowerCAmelCase	)
            a			   =rust_tokenizer.encode(_lowerCAmelCase ,    add_special_tokens=_lowerCAmelCase	)
            self.assertListEqual(_lowerCAmelCase ,    _lowerCAmelCase	)

            a			   =self.get_rust_tokenizer()
            a			   =tokenizer.encode(_lowerCAmelCase	)
            a			   =rust_tokenizer.encode(_lowerCAmelCase	)
            self.assertListEqual(_lowerCAmelCase ,    _lowerCAmelCase	)

            # With lower casing
            a			   =self.get_tokenizer(do_lower_case=_lowerCAmelCase	)
            a			   =self.get_rust_tokenizer(do_lower_case=_lowerCAmelCase	)

            a			   ="""UNwant\u00E9d,running"""

            a			   =tokenizer.tokenize(_lowerCAmelCase	)
            a			   =rust_tokenizer.tokenize(_lowerCAmelCase	)
            self.assertListEqual(_lowerCAmelCase ,    _lowerCAmelCase	)

            a			   =tokenizer.encode(_lowerCAmelCase ,    add_special_tokens=_lowerCAmelCase	)
            a			   =rust_tokenizer.encode(_lowerCAmelCase ,    add_special_tokens=_lowerCAmelCase	)
            self.assertListEqual(_lowerCAmelCase ,    _lowerCAmelCase	)

            a			   =self.get_rust_tokenizer()
            a			   =tokenizer.encode(_lowerCAmelCase	)
            a			   =rust_tokenizer.encode(_lowerCAmelCase	)
            self.assertListEqual(_lowerCAmelCase ,    _lowerCAmelCase	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer()

            self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz"""	) ,    ["""ah""", """\u535A""", """\u63A8""", """zz"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer(do_lower_case=_lowerCAmelCase	)

            self.assertListEqual(
                tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """	) ,    ["""hello""", """!""", """how""", """are""", """you""", """?"""]	)
            self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""	) ,    ["""hello"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer(do_lower_case=_lowerCAmelCase ,    strip_accents=_lowerCAmelCase	)

            self.assertListEqual(
                tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	) ,    ["""hällo""", """!""", """how""", """are""", """you""", """?"""]	)
            self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""	) ,    ["""h\u00E9llo"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer(do_lower_case=_lowerCAmelCase ,    strip_accents=_lowerCAmelCase	)

            self.assertListEqual(
                tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	) ,    ["""hallo""", """!""", """how""", """are""", """you""", """?"""]	)
            self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""	) ,    ["""hello"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer(do_lower_case=_lowerCAmelCase	)

            self.assertListEqual(
                tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	) ,    ["""hallo""", """!""", """how""", """are""", """you""", """?"""]	)
            self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""	) ,    ["""hello"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer(do_lower_case=_lowerCAmelCase	)

            self.assertListEqual(
                tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """	) ,    ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer(do_lower_case=_lowerCAmelCase ,    strip_accents=_lowerCAmelCase	)

            self.assertListEqual(
                tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	) ,    ["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer(do_lower_case=_lowerCAmelCase ,    strip_accents=_lowerCAmelCase	)

            self.assertListEqual(
                tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	) ,    ["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =BasicTokenizer(do_lower_case=_lowerCAmelCase ,    never_split=["""[UNK]"""]	)

            self.assertListEqual(
                tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]"""	) ,    ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""]	)
     def        lowerCAmelCase__  (				self	):
            a			   =["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

            a			   ={}
            for i, token in enumerate(_lowerCAmelCase	):
                   a			   =i
            a			   =WordpieceTokenizer(vocab=_lowerCAmelCase ,    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        lowerCAmelCase__  (				self	):
            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        lowerCAmelCase__  (				self	):
            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        lowerCAmelCase__  (				self	):
            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        lowerCAmelCase__  (				self	):
            a			   =self.get_tokenizer()

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

            if self.test_rust_tokenizer:
                   a			   =self.get_rust_tokenizer()
                   self.assertListEqual(
                       [rust_tokenizer.tokenize(_lowerCAmelCase	) for t in ["""Test""", """\xad""", """test"""]] ,    [["""[UNK]"""], [], ["""[UNK]"""]]	)
     @slow
     def        lowerCAmelCase__  (				self	):
            a			   =self.tokenizer_class.from_pretrained("""bert-base-uncased"""	)

            a			   =tokenizer.encode("""sequence builders""" ,    add_special_tokens=_lowerCAmelCase	)
            a			   =tokenizer.encode("""multi-sequence build""" ,    add_special_tokens=_lowerCAmelCase	)

            a			   =tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase	)
            a			   =tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase ,    _lowerCAmelCase	)

            assert encoded_sentence == [101] + text + [102]
            assert encoded_pair == [101] + text + [102] + text_a + [102]
     def        lowerCAmelCase__  (				self	):
            for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                   with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''	):
                          a			   =self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase ,    **_lowerCAmelCase	)

                          a			   =F'''A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'''
                          a			   =tokenizer_r.encode_plus(
                              _lowerCAmelCase ,    return_attention_mask=_lowerCAmelCase ,    return_token_type_ids=_lowerCAmelCase ,    return_offsets_mapping=_lowerCAmelCase ,    add_special_tokens=_lowerCAmelCase ,    )

                          a			   =tokenizer_r.do_lower_case if hasattr(_lowerCAmelCase ,    """do_lower_case"""	) else False
                          a			   =(
                              [
                                  ((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"""]	)






     @slow
     def        lowerCAmelCase__  (				self	):
            for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                   with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''	):
                          a			   =self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase ,    **_lowerCAmelCase	)
                          a			   =self.tokenizer_class.from_pretrained(_lowerCAmelCase ,    **_lowerCAmelCase	)
                          a			   =[["""Hello world!""", """Nice to meet you!"""], ["""The cute cat.""", """The adorable dog."""]]

                          a			   =tokenizer_r.batch_encode_candidates(_lowerCAmelCase ,    max_length=10 ,    return_tensors="""np"""	)
                          a			   =tokenizer_p.batch_encode_candidates(_lowerCAmelCase ,    max_length=10 ,    return_tensors="""np"""	)

                          a			   =(2, 2, 10)

                          self.assertEqual(encoded_sentence_r["""input_ids"""].shape ,    _lowerCAmelCase	)
                          self.assertEqual(encoded_sentence_r["""attention_mask"""].shape ,    _lowerCAmelCase	)
                          self.assertEqual(encoded_sentence_r["""token_type_ids"""].shape ,    _lowerCAmelCase	)

                          self.assertEqual(encoded_sentence_p["""input_ids"""].shape ,    _lowerCAmelCase	)
                          self.assertEqual(encoded_sentence_p["""attention_mask"""].shape ,    _lowerCAmelCase	)
                          self.assertEqual(encoded_sentence_p["""token_type_ids"""].shape ,    _lowerCAmelCase	)






import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter

from transformers import HfArgumentParser





def 							lowerCamelCase    (							UpperCAmelCase_	:      Union[str, Any]=None   ,       UpperCAmelCase_	:      Union[str, Any]=None      )->			Tuple:

       """simple docstring"""




       return field(default_factory=lambda: default   ,       metadata=UpperCAmelCase_      )


@dataclass
class        UpperCAmelCase__				:



     '''simple docstring'''
     _SCREAMING_SNAKE_CASE      :					str     					=    field(
         metadata={"help": "The csv file to plot."}      ,		)
     _SCREAMING_SNAKE_CASE      :					bool     					=    field(
         default=UpperCAmelCase__      ,		metadata={"help": "Whether to plot along batch size or sequence length. Defaults to sequence length."}      ,		)
     _SCREAMING_SNAKE_CASE      :					bool     					=    field(
         default=UpperCAmelCase__      ,		metadata={"help": "Whether the csv file has time results or memory results. Defaults to memory results."}      ,		)
     _SCREAMING_SNAKE_CASE      :					bool     					=    field(
         default=UpperCAmelCase__      ,		metadata={"help": "Disable logarithmic scale when plotting"}      ,		)
     _SCREAMING_SNAKE_CASE      :					bool     					=    field(
         default=UpperCAmelCase__      ,		metadata={
             "help": "Whether the csv file has training results or inference results. Defaults to inference results."
         }      ,		)
     _SCREAMING_SNAKE_CASE      :					Optional[str]     					=    field(
         default=UpperCAmelCase__      ,		metadata={"help": "Filename under which the plot will be saved. If unused no plot is saved."}      ,		)
     _SCREAMING_SNAKE_CASE      :					Optional[List[str]]     					=    list_field(
         default=UpperCAmelCase__      ,		metadata={"help": "List of model names that are used instead of the ones in the csv file."}				)





def 							lowerCamelCase    (							UpperCAmelCase_	:      Dict      )->			int:

       """simple docstring"""




       try:
              int(UpperCAmelCase_      )
              return True
       except ValueError:
              return False





def 							lowerCamelCase    (							UpperCAmelCase_	:      List[str]      )->			str:

       """simple docstring"""




       try:
              float(UpperCAmelCase_      )
              return True
       except ValueError:
              return False


class        UpperCAmelCase__				:



     '''simple docstring'''
     def __init__(				self ,    _lowerCAmelCase	):
            a			   =args
            a			   =defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}	)

            with open(self.args.csv_file ,    newline=""""""	) as csv_file:
                   a			   =csv.DictReader(_lowerCAmelCase	)
                   for row in reader:
                          a			   =row["""model"""]
                          self.result_dict[model_name]["bsz"].append(int(row["""batch_size"""]	)	)
                          self.result_dict[model_name]["seq_len"].append(int(row["""sequence_length"""]	)	)
                          if can_convert_to_int(row["""result"""]	):
                                 # value is not None
                                 a			   =int(row["""result"""]	)
                          elif can_convert_to_float(row["""result"""]	):
                                 # value is not None
                                 a			   =float(row["""result"""]	)






     def        lowerCAmelCase__  (				self	):
            a   ,      a			   =plt.subplots()
            a			   ="""Time usage""" if self.args.is_time else """Memory usage"""
            a			   =title_str + """ for training""" if self.args.is_train else title_str + """ for inference"""

            if not self.args.no_log_scale:
                   # set logarithm scales
                   ax.set_xscale("""log"""	)
                   ax.set_yscale("""log"""	)

            for axis in [ax.xaxis, ax.yaxis]:
                   axis.set_major_formatter(ScalarFormatter()	)

            for model_name_idx, model_name in enumerate(self.result_dict.keys()	):
                   a			   =sorted(set(self.result_dict[model_name]["""bsz"""]	)	)
                   a			   =sorted(set(self.result_dict[model_name]["""seq_len"""]	)	)
                   a			   =self.result_dict[model_name]["""result"""]

                   ((a)   ,      (a))			   =(
                       (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
                   )

                   a			   =(
                       model_name if self.args.short_model_names is None else self.args.short_model_names[model_name_idx]
                   )

                   for inner_loop_value in inner_loop_array:
                          if self.args.plot_along_batch:
                                 a			   =np.asarray(
                                     [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results] ,    dtype=_lowerCAmelCase ,    )
                          else:
                                 a			   =np.asarray(
                                     [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results] ,    dtype=np.floataa ,    )

                          ((a)   ,      (a))			   =(
                              ("""batch_size""", """len""") if self.args.plot_along_batch else ("""in #tokens""", """bsz""")
                          )

                          a			   =np.asarray(_lowerCAmelCase ,    _lowerCAmelCase	)[: len(_lowerCAmelCase	)]
                          plt.scatter(
                              _lowerCAmelCase ,    _lowerCAmelCase ,    label=F'''{label_model_name} - {inner_loop_label}: {inner_loop_value}'''	)
                          plt.plot(_lowerCAmelCase ,    _lowerCAmelCase ,    """--"""	)

                   title_str += F''' {label_model_name} vs.'''

            a			   =title_str[:-4]
            a			   ="""Time in s""" if self.args.is_time else """Memory in MB"""

            # plot
            plt.title(_lowerCAmelCase	)
            plt.xlabel(_lowerCAmelCase	)
            plt.ylabel(_lowerCAmelCase	)
            plt.legend()

            if self.args.figure_png_file is not None:
                   plt.savefig(self.args.figure_png_file	)
            else:
                   plt.show()





def 							lowerCamelCase    (							)->			Optional[Any]:

       """simple docstring"""




       a			   =HfArgumentParser(UpperCAmelCase_      )
       a			   =parser.parse_args_into_dataclasses()[0]
       a			   =Plot(args=UpperCAmelCase_      )
       plot.plot()


if __name__ == "__main__":
    main()
