





'''simple docstring'''




import argparse
import json
import logging
import os
import sys
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


__SCREAMING_SNAKE_CASE     :Union[str, Any]       =				[
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        '''text-classification''',
        '''language-modeling''',
        '''summarization''',
        '''token-classification''',
        '''question-answering''',
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
  import run_clm_flax
  import run_flax_glue
  import run_flax_ner
  import run_mlm_flax
  import run_qa
  import run_summarization_flax
  import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

__SCREAMING_SNAKE_CASE     :Union[str, Any]       =				logging.getLogger()
def 	UpperCAmelCase_							(					)		->       List[str]:


     '''simple docstring'''



     _UpperCAmelCase     							=   argparse.ArgumentParser()
     parser.add_argument("-f"       )
     _UpperCAmelCase     							=   parser.parse_args()
     return args.f
def 	UpperCAmelCase_							(					__lowercase							:      Tuple			,     __lowercase							:      int="eval"       )		->       Tuple:


     '''simple docstring'''



     _UpperCAmelCase     							=   os.path.join(__lowercase			,     f'{split}_results.json'       )
     if os.path.exists(__lowercase       ):
          with open(__lowercase			,     "r"       ) as f:
               return json.load(__lowercase       )
     raise ValueError(f'can\'t find {path}'       )


__SCREAMING_SNAKE_CASE     :List[str]       =				logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







class   A_	(  lowerCAmelCase_			):




 def      lowercase	(					self       :    List[str]    ):
      _UpperCAmelCase     							=   self.get_auto_remove_tmp_dir()
      _UpperCAmelCase     							=   f'\n            run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --eval_steps=2\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            '.split()

      with patch.object(snake_case_	,			"argv"	,			snake_case_    ):
           run_flax_glue.main()
           _UpperCAmelCase     							=   get_results(snake_case_    )
           self.assertGreaterEqual(result["eval_accuracy"]	,			0.7_5    )




 @slow
 def      lowercase	(					self       :    int    ):
      _UpperCAmelCase     							=   self.get_auto_remove_tmp_dir()
      _UpperCAmelCase     							=   f'\n            run_clm_flax.py\n            --model_name_or_path distilgpt2\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --block_size 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '.split()

      with patch.object(snake_case_	,			"argv"	,			snake_case_    ):
           run_clm_flax.main()
           _UpperCAmelCase     							=   get_results(snake_case_    )
           self.assertLess(result["eval_perplexity"]	,			1_0_0    )




 @slow
 def      lowercase	(					self       :    str    ):
      _UpperCAmelCase     							=   self.get_auto_remove_tmp_dir()
      _UpperCAmelCase     							=   f'\n            run_summarization.py\n            --model_name_or_path t5-small\n            --train_file tests/fixtures/tests_samples/xsum/sample.json\n            --validation_file tests/fixtures/tests_samples/xsum/sample.json\n            --test_file tests/fixtures/tests_samples/xsum/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=8\n            --do_train\n            --do_eval\n            --do_predict\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --predict_with_generate\n        '.split()

      with patch.object(snake_case_	,			"argv"	,			snake_case_    ):
           run_summarization_flax.main()
           _UpperCAmelCase     							=   get_results(snake_case_	,			split="test"    )
           self.assertGreaterEqual(result["test_rouge1"]	,			1_0    )
           self.assertGreaterEqual(result["test_rouge2"]	,			2    )
           self.assertGreaterEqual(result["test_rougeL"]	,			7    )
           self.assertGreaterEqual(result["test_rougeLsum"]	,			7    )




 @slow
 def      lowercase	(					self       :    List[Any]    ):
      _UpperCAmelCase     							=   self.get_auto_remove_tmp_dir()
      _UpperCAmelCase     							=   f'\n            run_mlm.py\n            --model_name_or_path distilroberta-base\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --logging_steps 2 --eval_steps 2\n            --do_train\n            --do_eval\n            --num_train_epochs=1\n        '.split()

      with patch.object(snake_case_	,			"argv"	,			snake_case_    ):
           run_mlm_flax.main()
           _UpperCAmelCase     							=   get_results(snake_case_    )
           self.assertLess(result["eval_perplexity"]	,			4_2    )




 @slow
 def      lowercase	(					self       :    Any    ):
      _UpperCAmelCase     							=   self.get_auto_remove_tmp_dir()
      _UpperCAmelCase     							=   f'\n            run_t5_mlm_flax.py\n            --model_name_or_path t5-small\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '.split()

      with patch.object(snake_case_	,			"argv"	,			snake_case_    ):
           run_ta_mlm_flax.main()
           _UpperCAmelCase     							=   get_results(snake_case_    )
           self.assertGreaterEqual(result["eval_accuracy"]	,			0.4_2    )




 @slow
 def      lowercase	(					self       :    Tuple    ):
      # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
      _UpperCAmelCase     							=   7 if get_gpu_count() > 1 else 2

      _UpperCAmelCase     							=   self.get_auto_remove_tmp_dir()
      _UpperCAmelCase     							=   f'\n            run_flax_ner.py\n            --model_name_or_path bert-base-uncased\n            --train_file tests/fixtures/tests_samples/conll/sample.json\n            --validation_file tests/fixtures/tests_samples/conll/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --do_train\n            --do_eval\n            --warmup_steps=2\n            --learning_rate=2e-4\n            --logging_steps 2 --eval_steps 2\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=2\n            --num_train_epochs={epochs}\n            --seed 7\n        '.split()

      with patch.object(snake_case_	,			"argv"	,			snake_case_    ):
           run_flax_ner.main()
           _UpperCAmelCase     							=   get_results(snake_case_    )
           self.assertGreaterEqual(result["eval_accuracy"]	,			0.7_5    )
           self.assertGreaterEqual(result["eval_f1"]	,			0.3    )




 @slow
 def      lowercase	(					self       :    Any    ):
      _UpperCAmelCase     							=   self.get_auto_remove_tmp_dir()
      _UpperCAmelCase     							=   f'\n            run_qa.py\n            --model_name_or_path bert-base-uncased\n            --version_2_with_negative\n            --train_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=2\n            --do_train\n            --do_eval\n            --logging_steps 2 --eval_steps 2\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n        '.split()

      with patch.object(snake_case_	,			"argv"	,			snake_case_    ):
           run_qa.main()
           _UpperCAmelCase     							=   get_results(snake_case_    )
           self.assertGreaterEqual(result["eval_f1"]	,			3_0    )
           self.assertGreaterEqual(result["eval_exact"]	,			3_0    )











'''simple docstring'''




from __future__ import annotations

from collections.abc import Callable
from typing import Any, Generic, TypeVar

__SCREAMING_SNAKE_CASE     :Optional[int]       =				TypeVar('''T''')







class   A_	(  Generic[T]			):




 def __init__(					self       :    List[Any]	,			snake_case_       :    list[T]	,			snake_case_       :    Callable[[T, T], T]    ):
      _UpperCAmelCase     							=   None

      _UpperCAmelCase     							=   len(snake_case_    )
      _UpperCAmelCase     							=   [any_type for _ in range(self.N    )] + arr
      _UpperCAmelCase     							=   fnc
      self.build()




 def      lowercase	(					self       :    List[Any]    ):
      for p in range(self.N - 1	,			0	,			-1    ):
           _UpperCAmelCase     							=   self.fn(self.st[p * 2]	,			self.st[p * 2 + 1]    )




 def      lowercase	(					self       :    Optional[Any]	,			snake_case_       :    int	,			snake_case_       :    T    ):
      p += self.N
      _UpperCAmelCase     							=   v
      while p > 1:
           _UpperCAmelCase     							=   p // 2
           _UpperCAmelCase     							=   self.fn(self.st[p * 2]	,			self.st[p * 2 + 1]    )




 def      lowercase	(					self       :    Any	,			snake_case_       :    int	,			snake_case_       :    int    ):  # noqa: E741
      _UpperCAmelCase							,  _UpperCAmelCase     							=   l + self.N, r + self.N

      _UpperCAmelCase     							=   None
      while l <= r:
           if l % 2 == 1:
                _UpperCAmelCase     							=   self.st[l] if res is None else self.fn(snake_case_	,			self.st[l]    )
           if r % 2 == 0:
                _UpperCAmelCase     							=   self.st[r] if res is None else self.fn(snake_case_	,			self.st[r]    )
           _UpperCAmelCase							,  _UpperCAmelCase     							=   (l + 1) // 2, (r - 1) // 2
      return res


if __name__ == "__main__":
  from functools import reduce

  __SCREAMING_SNAKE_CASE     :Union[str, Any]       =				[1, 10, -2, 9, -3, 8, 4, -7, 5, 6, 11, -12]

  __SCREAMING_SNAKE_CASE     :List[str]       =				{
      0: 7,
      1: 2,
      2: 6,
      3: -14,
      4: 5,
      5: 4,
      6: 7,
      7: -10,
      8: 9,
      9: 10,
      10: 12,
      11: 1,
  }

  __SCREAMING_SNAKE_CASE     :Any       =				SegmentTree(test_array, min)
  __SCREAMING_SNAKE_CASE     :Any       =				SegmentTree(test_array, max)
  __SCREAMING_SNAKE_CASE     :Any       =				SegmentTree(test_array, lambda a, b: a + b)
  def 	UpperCAmelCase_							(					)		->       None:


       '''simple docstring'''



       for i in range(len(__lowercase       )       ):
            for j in range(__lowercase			,     len(__lowercase       )       ):
                 _UpperCAmelCase     							=   reduce(__lowercase			,     test_array[i : j + 1]       )
                 _UpperCAmelCase     							=   reduce(__lowercase			,     test_array[i : j + 1]       )
                 _UpperCAmelCase     							=   reduce(lambda __lowercase			,     __lowercase       : a + b			,     test_array[i : j + 1]       )
                 assert min_range == min_segment_tree.query(__lowercase			,     __lowercase       )
                 assert max_range == max_segment_tree.query(__lowercase			,     __lowercase       )
                 assert sum_range == sum_segment_tree.query(__lowercase			,     __lowercase       )

  test_all_segments()

  for index, value in test_updates.items():
    __SCREAMING_SNAKE_CASE     :str       =				value
    min_segment_tree.update(index, value)
    max_segment_tree.update(index, value)
    sum_segment_tree.update(index, value)
    test_all_segments()




