





"""simple docstring"""





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  __A   (_SCREAMING_SNAKE_CASE=None     ,   _SCREAMING_SNAKE_CASE=None			)					->Optional[Any]:





  """simple docstring"""


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






@dataclass
class 					_lowerCAmelCase   :
       """simple docstring"""




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






def  __A   (_SCREAMING_SNAKE_CASE			)					->str:





  """simple docstring"""


  try:
    int(_SCREAMING_SNAKE_CASE			)
    return True
  except ValueError:
    return False
def  __A   (_SCREAMING_SNAKE_CASE			)					->Union[str, Any]:





  """simple docstring"""


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






class 					_lowerCAmelCase   :
       """simple docstring"""




       def __init__(    self    , __UpperCAmelCase      ):



         '''simple docstring'''

         lowerCAmelCase__			:List[str]											=							args
         lowerCAmelCase__			:int											=							defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}      )

         with open(self.args.csv_file    , newline=''      ) as csv_file:
           lowerCAmelCase__			:Optional[Any]											=							csv.DictReader(__UpperCAmelCase      )
           for row in reader:
             lowerCAmelCase__			:List[str]											=							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
               lowerCAmelCase__			:List[str]											=							int(row['result']      )
             elif can_convert_to_float(row['result']      ):
               # value is not None
               lowerCAmelCase__			:Optional[int]											=							float(row['result']      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__							,				lowerCAmelCase__			:int											=							plt.subplots()
         lowerCAmelCase__			:List[str]											=							'Time usage' if self.args.is_time else 'Memory usage'
         lowerCAmelCase__			:Tuple											=							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()      ):
           lowerCAmelCase__			:List[str]											=							sorted(set(self.result_dict[model_name]['bsz']      )      )
           lowerCAmelCase__			:List[Any]											=							sorted(set(self.result_dict[model_name]['seq_len']      )      )
           lowerCAmelCase__			:Tuple											=							self.result_dict[model_name]['result']

           ((lowerCAmelCase__)							,				(lowerCAmelCase__))			:str											=							(
               (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
           )

           lowerCAmelCase__			:int											=							(
               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:
               lowerCAmelCase__			:List[str]											=							np.asarray(
                   [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results]    , dtype=__UpperCAmelCase    , )
             else:
               lowerCAmelCase__			:List[str]											=							np.asarray(
                   [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results]    , dtype=np.floataa    , )

             ((lowerCAmelCase__)							,				(lowerCAmelCase__))			:Optional[Any]											=							(
                 ('batch_size', 'len') if self.args.plot_along_batch else ('in #tokens', 'bsz')
             )

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

           title_str += F" {label_model_name} vs."

         lowerCAmelCase__			:int											=							title_str[:-4]
         lowerCAmelCase__			:Dict											=							'Time in s' if self.args.is_time else 'Memory in MB'

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

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






def  __A   ()					->List[str]:





  """simple docstring"""


  lowerCAmelCase__			:List[Any]											=							HfArgumentParser(_SCREAMING_SNAKE_CASE			)
  lowerCAmelCase__			:Optional[int]											=							parser.parse_args_into_dataclasses()[0]
  lowerCAmelCase__			:Dict											=							Plot(args=_SCREAMING_SNAKE_CASE			)
  plot.plot()


if __name__ == "__main__":
  main()







"""simple docstring"""





import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__A											=		get_tests_dir("""fixtures/test_sentencepiece.model""")






@require_sentencepiece
@require_tokenizers
class 					_lowerCAmelCase   (     a  ,   unittest.TestCase       ):
       """simple docstring"""




       __magic_name__     :List[str]		  =					XGLMTokenizer
       __magic_name__     :Any		  =					XGLMTokenizerFast
       __magic_name__     :Dict		  =					True
       __magic_name__     :Union[str, Any]		  =					True






       def      snake_case						(    self      ):



         '''simple docstring'''

         super().setUp()

         # We have a SentencePiece fixture for testing
         lowerCAmelCase__			:int											=							XGLMTokenizer(__UpperCAmelCase    , keep_accents=__UpperCAmelCase      )
         tokenizer.save_pretrained(self.tmpdirname      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:List[Any]											=							'<pad>'
         lowerCAmelCase__			:int											=							1

         self.assertEqual(self.get_tokenizer()._convert_token_to_id(__UpperCAmelCase      )    , __UpperCAmelCase      )
         self.assertEqual(self.get_tokenizer()._convert_id_to_token(__UpperCAmelCase      )    , __UpperCAmelCase      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[int]											=							list(self.get_tokenizer().get_vocab().keys()      )

         self.assertEqual(vocab_keys[0]    , '<s>'      )
         self.assertEqual(vocab_keys[1]    , '<pad>'      )
         self.assertEqual(len(__UpperCAmelCase      )    , 1_0_0_8      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         self.assertEqual(self.get_tokenizer().vocab_size    , 1_0_0_8      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:List[Any]											=							XGLMTokenizer(__UpperCAmelCase    , keep_accents=__UpperCAmelCase      )

         lowerCAmelCase__			:Optional[Any]											=							tokenizer.tokenize('This is a test'      )
         self.assertListEqual(__UpperCAmelCase    , ['▁This', '▁is', '▁a', '▁t', 'est']      )

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(__UpperCAmelCase      )    , [value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]    , )

         lowerCAmelCase__			:int											=							tokenizer.tokenize('I was born in 92000, and this is falsé.'      )
         self.assertListEqual(
             __UpperCAmelCase    , [
                 SPIECE_UNDERLINE + 'I',
                 SPIECE_UNDERLINE + 'was',
                 SPIECE_UNDERLINE + 'b',
                 'or',
                 'n',
                 SPIECE_UNDERLINE + 'in',
                 SPIECE_UNDERLINE + '',
                 '9',
                 '2',
                 '0',
                 '0',
                 '0',
                 ',',
                 SPIECE_UNDERLINE + 'and',
                 SPIECE_UNDERLINE + 'this',
                 SPIECE_UNDERLINE + 'is',
                 SPIECE_UNDERLINE + 'f',
                 'al',
                 's',
                 'é',
                 '.',
             ]    , )
         lowerCAmelCase__			:Tuple											=							tokenizer.convert_tokens_to_ids(__UpperCAmelCase      )
         self.assertListEqual(
             __UpperCAmelCase    , [
                 value + tokenizer.fairseq_offset
                 for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
             ]    , )

         lowerCAmelCase__			:Optional[int]											=							tokenizer.convert_ids_to_tokens(__UpperCAmelCase      )
         self.assertListEqual(
             __UpperCAmelCase    , [
                 SPIECE_UNDERLINE + 'I',
                 SPIECE_UNDERLINE + 'was',
                 SPIECE_UNDERLINE + 'b',
                 'or',
                 'n',
                 SPIECE_UNDERLINE + 'in',
                 SPIECE_UNDERLINE + '',
                 '<unk>',
                 '2',
                 '0',
                 '0',
                 '0',
                 ',',
                 SPIECE_UNDERLINE + 'and',
                 SPIECE_UNDERLINE + 'this',
                 SPIECE_UNDERLINE + 'is',
                 SPIECE_UNDERLINE + 'f',
                 'al',
                 's',
                 '<unk>',
                 '.',
             ]    , )






       @cached_property
       def      snake_case						(    self      ):



         '''simple docstring'''

         return XGLMTokenizer.from_pretrained('facebook/xglm-564M'      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         with tempfile.NamedTemporaryFile() as f:
           shutil.copyfile(__UpperCAmelCase    , f.name      )
           lowerCAmelCase__			:Dict											=							XGLMTokenizer(f.name    , keep_accents=__UpperCAmelCase      )
           lowerCAmelCase__			:List[Any]											=							pickle.dumps(__UpperCAmelCase      )
         pickle.loads(__UpperCAmelCase      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         if not self.test_rust_tokenizer:
           return

         lowerCAmelCase__			:Optional[Any]											=							self.get_tokenizer()
         lowerCAmelCase__			:List[str]											=							self.get_rust_tokenizer()

         lowerCAmelCase__			:Optional[Any]											=							'I was born in 92000, and this is falsé.'

         lowerCAmelCase__			:Dict											=							tokenizer.tokenize(__UpperCAmelCase      )
         lowerCAmelCase__			:Union[str, Any]											=							rust_tokenizer.tokenize(__UpperCAmelCase      )
         self.assertListEqual(__UpperCAmelCase    , __UpperCAmelCase      )

         lowerCAmelCase__			:Optional[Any]											=							tokenizer.encode(__UpperCAmelCase    , add_special_tokens=__UpperCAmelCase      )
         lowerCAmelCase__			:List[Any]											=							rust_tokenizer.encode(__UpperCAmelCase    , add_special_tokens=__UpperCAmelCase      )
         self.assertListEqual(__UpperCAmelCase    , __UpperCAmelCase      )

         lowerCAmelCase__			:int											=							self.get_rust_tokenizer()
         lowerCAmelCase__			:Dict											=							tokenizer.encode(__UpperCAmelCase      )
         lowerCAmelCase__			:Tuple											=							rust_tokenizer.encode(__UpperCAmelCase      )
         self.assertListEqual(__UpperCAmelCase    , __UpperCAmelCase      )






       @slow
       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:str											=							'Hello World!'
         lowerCAmelCase__			:Tuple											=							[2, 3_1_2_2_7, 4_4_4_7, 3_5]

         self.assertListEqual(__UpperCAmelCase    , self.big_tokenizer.encode(__UpperCAmelCase      )      )






       @slow
       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Tuple											=							(
             'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
             ' add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth'
         )
         # fmt: off
         lowerCAmelCase__			:List[str]											=							[2, 1_0_1_8, 6_7, 1_1, 1_9_8_8, 2_6_1_7, 5_6_3_1, 2_7_8, 1_1, 3_4_0_7, 4_8, 7_1_6_3_0, 2_8_0_8_5, 4, 3_2_3_4, 1_5_7, 1_3, 6, 5, 6, 4, 3_5_2_6, 7_6_8, 1_5, 6_5_9, 5_7, 2_9_8, 3_9_8_3, 8_6_4, 1_2_9, 2_1, 6, 5, 1_3_6_7_5, 3_7_7, 6_5_2, 7_5_8_0, 1_0_3_4_1, 1_5_5, 2_8_1_7, 4_2_2, 1_6_6_6, 7, 1_6_7_4, 5_3, 1_1_3, 2_0_2_2_7_7, 1_7_8_9_2, 3_3, 6_0, 8_7, 4, 3_2_3_4, 1_5_7, 6_1, 2_6_6_7, 5_2_3_7_6, 1_9, 8_8, 2_3, 7_3_5]
         # fmt: on

         self.assertListEqual(__UpperCAmelCase    , self.big_tokenizer.encode(__UpperCAmelCase      )      )






       @slow
       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Union[str, Any]											=							{
             'input_ids': [[2, 1_0_8_8_2_5, 1_1_6_3, 1_5, 8_8_0_1_0, 4_7_3, 1_5_8_9_8, 1_5_7, 1_3_6_7_2, 1_8_5_7, 3_1_2, 8, 2_3_8_0_2_1, 1_1_6_3, 5_3, 1_3_6_7_2, 1_8_5_7, 3_1_2, 8, 5_3_2_8_3, 1_8_2_3_9_6, 8, 1_8_5_6_6, 1_6, 3_6_7_3_3, 4_1_0_1, 8, 2_3_0, 2_4_4_0_1_7, 1_2_2_5_5_3, 7, 1_5, 1_3_2_5_9_7, 4, 2_9_3, 1_2_5_1_1, 7_6_1_0, 4, 3_4_1_4, 1_3_2_5_9_7, 9, 4, 3_2_3_6_1, 3_6_2, 4, 7_3_4, 2_8_5_1_2, 3_2_5_6_9, 1_8, 4, 3_2_3_6_1, 2_6_0_9_6, 1_4_9_8_2, 7_3, 1_8_7_1_5, 2_1_4_3_3, 2_3_5_2_6_1, 1_5, 4_9_2, 1_2_4_2_7, 1_6, 5_3, 1_8_7_1_5, 2_1_4_3_3, 6_5_4_5_4, 1_5, 2_3_6_5_9, 5_6_3, 1_6, 2_7_8, 5_9_7, 2_8_4_3, 5_9_5, 7_9_3_1, 1_8_2_3_9_6, 6_4_1_8_6, 2_2, 8_8_6, 5_9_5, 1_3_2_9_8_1, 5_3, 2_5_5_4_0, 3_4_4_9, 4_3_9_8_2, 3_9_9_0_1, 5_9_5_1, 8_7_8, 3_3_0, 4, 2_7_6_9_4, 8_0_2_6_9, 3_1_2, 5_3, 6_5_1_7, 1_1_7_8_0, 6_1_1, 2_0_4_0_8, 5], [2, 6, 1_3_2_5_9_7, 6_7, 4_2_8_9_7, 3_3, 5_9_2, 8, 1_6_3_7_2_9, 2_5_5_4_0, 3_6_1, 1_3_6_9_9_7, 1_0_9_5_1_4, 1_7_3_2_3_0, 7, 5_0_1, 6_0, 1_0_2_9_1_3, 1_9_6, 5_6_3_1, 2_3_5, 6_3_2_4_3, 4_7_3, 6, 2_3_1_7_5_7, 7_4, 5_2_7_7, 7_9_0_5, 5_3, 3_0_9_5, 3_7_3_1_7, 2_2, 4_5_4, 1_8_3_8_7_4, 5], [2, 2_6_8, 3_1_2_9_8, 4_6_5_3_0, 6, 1_3_2_9_3_5, 4_3_8_3_1, 7, 5_9_7, 3_2, 2_4, 3_6_8_8, 9_8_6_5, 5]],
             'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
         }  # noqa: E501
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=__UpperCAmelCase    , model_name='facebook/xglm-564M'    , padding=__UpperCAmelCase    , )
