code: 
  
  
  """simple docstring"""
  
  
  
  
  # Copyright 2022 The HuggingFace Team. All rights reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  import os
  from typing import List
  
  
  
  def 						__a      (  a,		a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         if name != "training_function" and name != "main":
                raise ValueError(F'Incorrect function name passed: {name}, choose either \'main\' or \'training_function\''					)
         _a   , _a          =				[], False
         for line in lines:
                if not found_start and F'def {name}' in line:
                       _a          =				True
                       good_lines.append(a					)
                       continue
                if found_start:
                       if name == "training_function" and "def main" in line:
                              return good_lines
                       if name == "main" and "if __name__" in line:
                              return good_lines
                       good_lines.append(a					)
  
  
  
  def 						__a      (  a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         return [line for line in lines if not line.lstrip().startswith("#"					) and line != "\n"]
  
  
  
  def 						__a      (  a,		a,		a,		a = None					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         with open(a,		"r"					) as f:
                _a          =				f.readlines()
         with open(os.path.abspath(os.path.join("examples",		"nlp_example.py"					)					),		"r"					) as f:
                _a          =				f.readlines()
         with open(a,		"r"					) as f:
                _a          =				f.readlines()
         if secondary_filename is not None:
                with open(a,		"r"					) as f:
                       _a          =				f.readlines()
  
      # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
         if parser_only:
                _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
                _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
                _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
                if secondary_filename is not None:
                       _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
         else:
                _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
                _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
                _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
                if secondary_filename is not None:
                       _a          =				clean_lines(
                           get_function_contents_by_name(a,		"training_function"					)					)
  
         _a          =				"train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n"
  
         # Specific code in our script that differs from the full version, aka what is new
         _a          =				[]
         _a          =				[]  # We keep track of the idxs just in case it's a repeated statement
         _a          =				iter(a					)
         for i in range(len(a					) - 1					):
                if i not in passed_idxs:
                       _a          =				next(a					)
                       if (line not in full_file_func) and (line.lstrip() != _dl_line):
                              if "TESTING_MOCKED_DATALOADERS" not in line:
                                     new_feature_code.append(a					)
                                     passed_idxs.append(a					)
                              else:
                                     # Skip over the `config['num_epochs'] = 2` statement
                                     _a          =				next(a					)
  
      # Extract out just the new parts from the full_file_training_func
         _a          =				[]
         _a          =				[]  # We keep track of the idxs just in case it's a repeated statement
         for i, line in enumerate(a					):
                if i not in passed_idxs:
                       if (line not in full_file_func) and (line.lstrip() != _dl_line):
                              if "TESTING_MOCKED_DATALOADERS" not in line:
                                     new_full_example_parts.append(a					)
                                     passed_idxs.append(a					)
  
      # Finally, get the overall diff
         _a          =				[line for line in new_feature_code if line not in new_full_example_parts]
         if secondary_filename is not None:
                _a          =				[line for line in full_file_contents if line not in secondary_file_func]
                _a          =				[line for line in diff_from_example if line not in diff_from_two]
  
         return diff_from_example
  
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  from __future__ import annotations
  
  __SCREAMING_SNAKE_CASE					=						[2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]
  
  
  
  
  
  class __snake_case		:
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
  
     def __init__(		self							:Optional[Any]				,  UpperCamelCase__							:int       ):
            _a          =				-1
            _a          =				-1
            _a          =				[-1] * length
            _a          =				None
            _a          =				None
  
  
  
  
     def __repr__(		self							:Optional[Any]       ):
            return f'Node(min_value={self.minn} max_value={self.maxx})'
  
  
  
  
  
  
  def 						__a      (  a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         _a          =				Node(len(a					)					)
         _a   , _a          =				min(a					), max(a					)
         # Leaf node case where the node contains only one unique value
         if root.minn == root.maxx:
                return root
         _a          =				(root.minn + root.maxx) // 2
  
         _a          =				[]
         _a          =				[]
  
         for index, num in enumerate(a					):
                if num <= pivot:
                       left_arr.append(a					)
                else:
                       right_arr.append(a					)
                _a          =				len(a					)
         _a          =				build_tree(a					)
         _a          =				build_tree(a					)
         return root
  
  
  
  def 						__a      (  a,		a,		a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         if index < 0 or node is None:
                return 0
         # Leaf node cases
         if node.minn == node.maxx:
                return index + 1 if node.minn == num else 0
         _a          =				(node.minn + node.maxx) // 2
         if num <= pivot:
                # go the left subtree and map index to the left subtree
                return rank_till_index(node.left,		a,		node.map_left[index] - 1					)
         else:
                # go to the right subtree and map index to the right subtree
                return rank_till_index(node.right,		a,		index - node.map_left[index]					)
  
  
  
  def 						__a      (  a,		a,		a,		a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         if start > end:
                return 0
         _a          =				rank_till_index(a,		a,		a					)
         _a          =				rank_till_index(a,		a,		start - 1					)
         return rank_till_end - rank_before_start
  
  
  
  def 						__a      (  a,		a,		a,		a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         if index > (end - start) or start > end or node is None:
                return -1
         # Leaf node case
         if node.minn == node.maxx:
                return node.minn
         # Number of elements in the left subtree in interval [start, end]
         _a          =				node.map_left[end] - (
             node.map_left[start - 1] if start else 0
         )
         if num_elements_in_left_tree > index:
                return quantile(
                    node.left,		a,		(node.map_left[start - 1] if start else 0),		node.map_left[end] - 1,		)
         else:
                return quantile(
                    node.right,		index - num_elements_in_left_tree,		start - (node.map_left[start - 1] if start else 0),		end - node.map_left[end],		)
  
  
  
  def 						__a      (  a,		a,		a,		a,		a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         if (
             start > end
             or node is None
             or start_num > end_num
             or node.minn > end_num
             or node.maxx < start_num
         ):
                return 0
         if start_num <= node.minn and node.maxx <= end_num:
                return end - start + 1
         _a          =				range_counting(
             node.left,		(node.map_left[start - 1] if start else 0),		node.map_left[end] - 1,		a,		a,		)
         _a          =				range_counting(
             node.right,		start - (node.map_left[start - 1] if start else 0),		end - node.map_left[end],		a,		a,		)
         return left + right
  
  
  if __name__ == "__main__":
     import doctest
  
     doctest.testmod()
  