


import os

import jsonlines
import numpy as np
from tqdm import tqdm


UpperCAmelCase_   :				Any						      = 2048
UpperCAmelCase_   :				int						      = 4096
UpperCAmelCase_   :				List[str]						      = 42
UpperCAmelCase_   :				Optional[Any]						      = os.environ.pop('PROCESS_TRAIN', 'false')
UpperCAmelCase_   :				Dict						      = {'null': 0, 'short': 1, 'long': 2, 'yes': 3, 'no': 4}







def  SCREAMING_SNAKE_CASE_		(    __A				:    Dict       )			->	int:

       """simple docstring"""

       def choose_first(__A				:    Optional[int]						,					__A				:    Optional[int]=False       ):
              assert isinstance(__A						,					__A       )
              if len(__A       ) == 1:
                     a_      :	Union[str, Any]							=						answer[0]
                     return {k: [answer[k]] for k in answer} if is_long_answer else answer
              for a in answer:
                     if is_long_answer:
                            a_      :	Dict							=						{k: [a[k]] for k in a}
                     if len(a['start_token']       ) > 0:
                            break
              return a

       a_      :	Union[str, Any]							=						{'id': example['id']}
       a_      :	Tuple							=						example['annotations']
       a_      :	int							=						annotation['yes_no_answer']
       if 0 in yes_no_answer or 1 in yes_no_answer:
              a_      :	int							=						['yes'] if 1 in yes_no_answer else ['no']
              a_      :	List[Any]							=						[]
              a_      :	List[str]							=						[]
              a_      :	Tuple							=						['<cls>']
       else:
              a_      :	Optional[int]							=						['short']
              a_      :	Dict							=						choose_first(annotation['short_answers']       )
              if len(out['start_token']       ) == 0:
                     # answer will be long if short is not available
                     a_      :	int							=						['long']
                     a_      :	Optional[Any]							=						choose_first(annotation['long_answer']						,					is_long_answer=__A       )
                     a_      :	str							=						[]
              answer.update(__A       )

       # disregard some samples
       if len(answer['start_token']       ) > 1 or answer["start_token"] == answer["end_token"]:
              a_      :	int							=						True
       else:
              a_      :	Optional[Any]							=						False

       a_      :	List[str]							=						['start_token', 'end_token', 'start_byte', 'end_byte', 'text']
       if not all(isinstance(answer[k]						,					__A       ) for k in cols       ):
              raise ValueError('Issue in ID'						,					example['id']       )

       return answer







def  SCREAMING_SNAKE_CASE_		(    __A				:    int						,					__A				:    Tuple=False       )			->	List[Any]:

       """simple docstring"""

       a_      :	List[Any]							=						_get_single_answer(__A       )
       # bytes are of no use
       del answer["start_byte"]
       del answer["end_byte"]

       # handle yes_no answers explicitly
       if answer["category"][0] in ["yes", "no"]:  # category is list with one element
              a_      :	List[str]							=						example['document']['tokens']
              a_      :	Optional[int]							=						[]
              for i in range(len(doc['token']       )       ):
                     if not doc["is_html"][i]:
                            context.append(doc['token'][i]       )
              return {
                  "context": " ".join(__A       ),
                  "answer": {
                      "start_token": -1_00,  # ignore index in cross-entropy
                      "end_token": -1_00,  # ignore index in cross-entropy
                      "category": answer["category"],
                      "span": answer["category"],  # extra
                  },
              }

       # later, help in removing all no answers
       if answer["start_token"] == [-1]:
              return {
                  "context": "None",
                  "answer": {
                      "start_token": -1,
                      "end_token": -1,
                      "category": "null",
                      "span": "None",  # extra
                  },
              }

       # handling normal samples

       a_      :	Optional[Any]							=						['start_token', 'end_token']
       answer.update({k: answer[k][0] if len(answer[k]       ) > 0 else answer[k] for k in cols}       )  # e.g. [10] == 10

       a_      :	Tuple							=						example['document']['tokens']
       a_      :	Union[str, Any]							=						answer['start_token']
       a_      :	Union[str, Any]							=						answer['end_token']

       a_      :	List[str]							=						[]
       for i in range(len(doc['token']       )       ):
              if not doc["is_html"][i]:
                     context.append(doc['token'][i]       )
              else:
                     if answer["start_token"] > i:
                            start_token -= 1
                     if answer["end_token"] > i:
                            end_token -= 1
       a_      :	Optional[Any]							=						' '.join(context[start_token:end_token]       )

       # checking above code
       if assertion:
              a_      :	int							=						doc['is_html'][answer['start_token'] : answer['end_token']]
              a_      :	Tuple							=						doc['token'][answer['start_token'] : answer['end_token']]
              a_      :	List[str]							=						' '.join([old[i] for i in range(len(__A       )       ) if not is_html[i]]       )
              if new != old:
                     print('ID:'						,					example['id']       )
                     print('New:'						,					__A						,					end='\n'       )
                     print('Old:'						,					__A						,					end='\n\n'       )

       return {
           "context": " ".join(__A       ),
           "answer": {
               "start_token": start_token,
               "end_token": end_token - 1,  # this makes it inclusive
               "category": answer["category"],  # either long or short
               "span": new,  # extra
           },
       }







def  SCREAMING_SNAKE_CASE_		(    __A				:    Optional[Any]						,					__A				:    int						,					__A				:    List[Any]=20_48						,					__A				:    Dict=40_96						,					__A				:    Optional[int]=True       )			->	List[Any]:

       """simple docstring"""

       a_      :	List[Any]							=						get_context_and_ans(__A						,					assertion=__A       )
       a_      :	Any							=						out['answer']

       # later, removing these samples
       if answer["start_token"] == -1:
              return {
                  "example_id": example["id"],
                  "input_ids": [[-1]],
                  "labels": {
                      "start_token": [-1],
                      "end_token": [-1],
                      "category": ["null"],
                  },
              }

       a_      :	Optional[int]							=						tokenizer(example['question']['text']						,					out['context']       ).input_ids
       a_      :	List[str]							=						input_ids.index(tokenizer.sep_token_id       ) + 1

       # return yes/no
       if answer["category"][0] in ["yes", "no"]:  # category is list with one element
              a_      :	Any							=						[]
              a_      :	List[Any]							=						[]
              a_      :	int							=						input_ids[:q_len]
              a_      :	Optional[Any]							=						range(__A						,					len(__A       )						,					max_length - doc_stride       )
              for i in doc_start_indices:
                     a_      :	str							=						i + max_length - q_len
                     a_      :	Tuple							=						input_ids[i:end_index]
                     inputs.append(q_indices + slice       )
                     category.append(answer['category'][0]       )
                     if slice[-1] == tokenizer.sep_token_id:
                            break

              return {
                  "example_id": example["id"],
                  "input_ids": inputs,
                  "labels": {
                      "start_token": [-1_00] * len(__A       ),
                      "end_token": [-1_00] * len(__A       ),
                      "category": category,
                  },
              }

       a_      :	str							=						out['context'].split()
       a_      :	List[Any]							=						splitted_context[answer['end_token']]
       a_      :	int							=						len(
           tokenizer(
               ' '.join(splitted_context[: answer['start_token']]       )						,					add_special_tokens=__A						,					).input_ids       )
       a_      :	str							=						len(
           tokenizer(' '.join(splitted_context[: answer['end_token']]       )						,					add_special_tokens=__A       ).input_ids       )

       answer["start_token"] += q_len
       answer["end_token"] += q_len

       # fixing end token
       a_      :	Optional[int]							=						len(tokenizer(__A						,					add_special_tokens=__A       ).input_ids       )
       if num_sub_tokens > 1:
              answer["end_token"] += num_sub_tokens - 1

       a_      :	List[str]							=						input_ids[answer['start_token'] : answer['end_token'] + 1]  # right & left are inclusive
       a_      :	List[Any]							=						answer['start_token']
       a_      :	Tuple							=						answer['end_token']

       if assertion:
              a_      :	List[Any]							=						tokenizer.decode(__A       )
              if answer["span"] != new:
                     print('ISSUE IN TOKENIZATION'       )
                     print('OLD:'						,					answer['span']       )
                     print('NEW:'						,					__A						,					end='\n\n'       )

       if len(__A       ) <= max_length:
              return {
                  "example_id": example["id"],
                  "input_ids": [input_ids],
                  "labels": {
                      "start_token": [answer["start_token"]],
                      "end_token": [answer["end_token"]],
                      "category": answer["category"],
                  },
              }

       a_      :	Union[str, Any]							=						input_ids[:q_len]
       a_      :	Tuple							=						range(__A						,					len(__A       )						,					max_length - doc_stride       )

       a_      :	str							=						[]
       a_      :	Dict							=						[]
       a_      :	Dict							=						[]
       a_      :	Optional[int]							=						[]  # null, yes, no, long, short
       for i in doc_start_indices:
              a_      :	Tuple							=						i + max_length - q_len
              a_      :	Dict							=						input_ids[i:end_index]
              inputs.append(q_indices + slice       )
              assert len(inputs[-1]       ) <= max_length, "Issue in truncating length"

              if start_token >= i and end_token <= end_index - 1:
                     a_      :	List[str]							=						start_token - i + q_len
                     a_      :	Optional[Any]							=						end_token - i + q_len
                     answers_category.append(answer['category'][0]       )  # ["short"] -> "short"
              else:
                     a_      :	Any							=						-1_00
                     a_      :	Any							=						-1_00
                     answers_category.append('null'       )
              a_      :	Tuple							=						inputs[-1][start_token : end_token + 1]

              answers_start_token.append(__A       )
              answers_end_token.append(__A       )
              if assertion:
                     if new != old and new != [tokenizer.cls_token_id]:
                            print('ISSUE in strided for ID:'						,					example['id']       )
                            print('New:'						,					tokenizer.decode(__A       )       )
                            print('Old:'						,					tokenizer.decode(__A       )						,					end='\n\n'       )
              if slice[-1] == tokenizer.sep_token_id:
                     break

       return {
           "example_id": example["id"],
           "input_ids": inputs,
           "labels": {
               "start_token": answers_start_token,
               "end_token": answers_end_token,
               "category": answers_category,
           },
       }







def  SCREAMING_SNAKE_CASE_		(    __A				:    Optional[int]						,					__A				:    int						,					__A				:    Optional[Any]=20_48						,					__A				:    Union[str, Any]=40_96						,					__A				:    Any=False       )			->	Optional[Any]:

       """simple docstring"""

       a_      :	List[Any]							=						get_strided_contexts_and_ans(
           __A						,					__A						,					doc_stride=__A						,					max_length=__A						,					assertion=__A						,					)

       return example







def  SCREAMING_SNAKE_CASE_		(    __A				:    Dict						,					__A				:    int       )			->	str:

       """simple docstring"""

       with jsonlines.open(__A						,					'a'       ) as writer:
              for example in tqdm(__A						,					total=len(__A       )						,					desc='Saving samples ... '       ):
                     a_      :	Union[str, Any]							=						example['labels']
                     for ids, start, end, cat in zip(
                         example['input_ids']						,					labels['start_token']						,					labels['end_token']						,					labels['category']						,					):
                            if start == -1 and end == -1:
                                   continue  # leave waste samples with no answer
                            if cat == "null" and np.random.rand() < 0.6:
                                   continue  # removing 50 % samples
                            writer.write(
                                {
                                    'input_ids': ids,
                                    'start_token': start,
                                    'end_token': end,
                                    'category': CATEGORY_MAPPING[cat],
                                }       )


if __name__ == "__main__":
   from datasets import load_dataset

   from transformers import BigBirdTokenizer

   UpperCAmelCase_   :				List[Any]						      = load_dataset('natural_questions')
   UpperCAmelCase_   :				Union[str, Any]						      = BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base')

   UpperCAmelCase_   :				str						      = data['train' if PROCESS_TRAIN == 'true' else 'validation']

   UpperCAmelCase_   :				Tuple						      = {
       'tokenizer': tokenizer,
       'doc_stride': DOC_STRIDE,
       'max_length': MAX_LENGTH,
       'assertion': False,
   }
   UpperCAmelCase_   :				List[str]						      = data.map(prepare_inputs, fn_kwargs=fn_kwargs)
   UpperCAmelCase_   :				Dict						      = data.remove_columns(['annotations', 'document', 'id', 'question'])
   print(data)

   np.random.seed(SEED)
   UpperCAmelCase_   :				Dict						      = 'nq-training.jsonl' if PROCESS_TRAIN == 'true' else 'nq-validation.jsonl'
   save_to_disk(data, file_name=cache_file_name)






import argparse
import os
import re


UpperCAmelCase_   :				List[Any]						      = 'src/transformers'

# Pattern that looks at the indentation in a line.
UpperCAmelCase_   :				Any						      = re.compile(R'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCAmelCase_   :				str						      = re.compile(R'^\s*"([^"]+)":')
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
UpperCAmelCase_   :				Dict						      = re.compile(R'^\s*_import_structure\["([^"]+)"\]')
# Pattern that matches `"key",` and puts `key` in group 0.
UpperCAmelCase_   :				int						      = re.compile(R'^\s*"([^"]+)",\s*$')
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
UpperCAmelCase_   :				List[str]						      = re.compile(R'\[([^\]]+)\]')







def  SCREAMING_SNAKE_CASE_		(    __A				:    Optional[Any]       )			->	Optional[Any]:

       """simple docstring"""

       a_      :	List[Any]							=						_re_indent.search(__A       )
       return "" if search is None else search.groups()[0]







def  SCREAMING_SNAKE_CASE_		(    __A				:    int						,					__A				:    Union[str, Any]=""						,					__A				:    Dict=None						,					__A				:    Dict=None       )			->	int:

       """simple docstring"""

       a_      :	Tuple							=						0
       a_      :	Dict							=						code.split('\n'       )
       if start_prompt is not None:
              while not lines[index].startswith(__A       ):
                     index += 1
              a_      :	List[Any]							=						['\n'.join(lines[:index]       )]
       else:
              a_      :	List[str]							=						[]

       # We split into blocks until we get to the `end_prompt` (or the end of the block).
       a_      :	Tuple							=						[lines[index]]
       index += 1
       while index < len(__A       ) and (end_prompt is None or not lines[index].startswith(__A       )):
              if len(lines[index]       ) > 0 and get_indent(lines[index]       ) == indent_level:
                     if len(__A       ) > 0 and get_indent(current_block[-1]       ).startswith(indent_level + ' '       ):
                            current_block.append(lines[index]       )
                            blocks.append('\n'.join(__A       )       )
                            if index < len(__A       ) - 1:
                                   a_      :	Dict							=						[lines[index + 1]]
                                   index += 1
                            else:
                                   a_      :	Dict							=						[]
                     else:
                            blocks.append('\n'.join(__A       )       )
                            a_      :	int							=						[lines[index]]
              else:
                     current_block.append(lines[index]       )
              index += 1

       # Adds current block if it's nonempty.
       if len(__A       ) > 0:
              blocks.append('\n'.join(__A       )       )

       # Add final block after end_prompt if provided.
       if end_prompt is not None and index < len(__A       ):
              blocks.append('\n'.join(lines[index:]       )       )

       return blocks







def  SCREAMING_SNAKE_CASE_		(    __A				:    Dict       )			->	Any:

       """simple docstring"""

       def _inner(__A				:    Tuple       ):
              return key(__A       ).lower().replace('_'						,					''       )

       return _inner







def  SCREAMING_SNAKE_CASE_		(    __A				:    Optional[int]						,					__A				:    List[Any]=None       )			->	List[str]:

       """simple docstring"""

       def noop(__A				:    Tuple       ):
              return x

       if key is None:
              a_      :	Optional[Any]							=						noop
       # Constants are all uppercase, they go first.
       a_      :	List[Any]							=						[obj for obj in objects if key(__A       ).isupper()]
       # Classes are not all uppercase but start with a capital, they go second.
       a_      :	Dict							=						[obj for obj in objects if key(__A       )[0].isupper() and not key(__A       ).isupper()]
       # Functions begin with a lowercase, they go last.
       a_      :	Optional[int]							=						[obj for obj in objects if not key(__A       )[0].isupper()]

       a_      :	Optional[Any]							=						ignore_underscore(__A       )
       return sorted(__A						,					key=__A       ) + sorted(__A						,					key=__A       ) + sorted(__A						,					key=__A       )







def  SCREAMING_SNAKE_CASE_		(    __A				:    Tuple       )			->	Optional[int]:

       """simple docstring"""

       def _replace(__A				:    List[Any]       ):
              a_      :	Tuple							=						match.groups()[0]
              if "," not in imports:
                     return F"""[{imports}]"""
              a_      :	int							=						[part.strip().replace('"'						,					''       ) for part in imports.split(','       )]
              # We will have a final empty element if the line finished with a comma.
              if len(keys[-1]       ) == 0:
                     a_      :	str							=						keys[:-1]
              return "[" + ", ".join([F"""\"{k}\"""" for k in sort_objects(__A       )]       ) + "]"

       a_      :	Optional[int]							=						import_statement.split('\n'       )
       if len(__A       ) > 3:
              # Here we have to sort internal imports that are on several lines (one per name):
              # key: [
              #     "object1",
              #     "object2",
              #     ...
              # ]

              # We may have to ignore one or two lines on each side.
              a_      :	int							=						2 if lines[1].strip() == '[' else 1
              a_      :	int							=						[(i, _re_strip_line.search(__A       ).groups()[0]) for i, line in enumerate(lines[idx:-idx]       )]
              a_      :	str							=						sort_objects(__A						,					key=lambda __A       : x[1]       )
              a_      :	int							=						[lines[x[0] + idx] for x in sorted_indices]
              return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]       )
       elif len(__A       ) == 3:
              # Here we have to sort internal imports that are on one separate line:
              # key: [
              #     "object1", "object2", ...
              # ]
              if _re_bracket_content.search(lines[1]       ) is not None:
                     a_      :	str							=						_re_bracket_content.sub(_replace						,					lines[1]       )
              else:
                     a_      :	List[str]							=						[part.strip().replace('"'						,					''       ) for part in lines[1].split(','       )]
                     # We will have a final empty element if the line finished with a comma.
                     if len(keys[-1]       ) == 0:
                            a_      :	Optional[int]							=						keys[:-1]
                     a_      :	Any							=						get_indent(lines[1]       ) + ', '.join([F"""\"{k}\"""" for k in sort_objects(__A       )]       )
              return "\n".join(__A       )
       else:
              # Finally we have to deal with imports fitting on one line
              a_      :	Union[str, Any]							=						_re_bracket_content.sub(_replace						,					__A       )
              return import_statement







def  SCREAMING_SNAKE_CASE_		(    __A				:    Optional[int]						,					__A				:    Any=True       )			->	Union[str, Any]:

       """simple docstring"""

       with open(__A						,					encoding='utf-8'       ) as f:
              a_      :	Union[str, Any]							=						f.read()

       if "_import_structure" not in code:
              return

       # Blocks of indent level 0
       a_      :	Optional[Any]							=						split_code_in_indented_blocks(
           __A						,					start_prompt='_import_structure = {'						,					end_prompt='if TYPE_CHECKING:'       )

       # We ignore block 0 (everything untils start_prompt) and the last block (everything after end_prompt).
       for block_idx in range(1						,					len(__A       ) - 1       ):
              # Check if the block contains some `_import_structure`s thingy to sort.
              a_      :	Any							=						main_blocks[block_idx]
              a_      :	Any							=						block.split('\n'       )

              # Get to the start of the imports.
              a_      :	Any							=						0
              while line_idx < len(__A       ) and "_import_structure" not in block_lines[line_idx]:
                     # Skip dummy import blocks
                     if "import dummy" in block_lines[line_idx]:
                            a_      :	Tuple							=						len(__A       )
                     else:
                            line_idx += 1
              if line_idx >= len(__A       ):
                     continue

              # Ignore beginning and last line: they don't contain anything.
              a_      :	List[str]							=						'\n'.join(block_lines[line_idx:-1]       )
              a_      :	List[Any]							=						get_indent(block_lines[1]       )
              # Slit the internal block into blocks of indent level 1.
              a_      :	Optional[int]							=						split_code_in_indented_blocks(__A						,					indent_level=__A       )
              # We have two categories of import key: list or _import_structure[key].append/extend
              a_      :	Tuple							=						_re_direct_key if '_import_structure = {' in block_lines[0] else _re_indirect_key
              # Grab the keys, but there is a trap: some lines are empty or just comments.
              a_      :	Union[str, Any]							=						[(pattern.search(__A       ).groups()[0] if pattern.search(__A       ) is not None else None) for b in internal_blocks]
              # We only sort the lines with a key.
              a_      :	str							=						[(i, key) for i, key in enumerate(__A       ) if key is not None]
              a_      :	Optional[int]							=						[x[0] for x in sorted(__A						,					key=lambda __A       : x[1]       )]

              # We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
              a_      :	int							=						0
              a_      :	int							=						[]
              for i in range(len(__A       )       ):
                     if keys[i] is None:
                            reorderded_blocks.append(internal_blocks[i]       )
                     else:
                            a_      :	List[str]							=						sort_objects_in_import(internal_blocks[sorted_indices[count]]       )
                            reorderded_blocks.append(__A       )
                            count += 1

        # And we put our main block back together with its first and last line.
              a_      :	Any							=						'\n'.join(block_lines[:line_idx] + reorderded_blocks + [block_lines[-1]]       )

       if code != "\n".join(__A       ):
              if check_only:
                     return True
              else:
                     print(F"""Overwriting {file}."""       )
                     with open(__A						,					'w'						,					encoding='utf-8'       ) as f:
                            f.write('\n'.join(__A       )       )







def  SCREAMING_SNAKE_CASE_		(    __A				:    List[Any]=True       )			->	List[Any]:

       """simple docstring"""

       a_      :	Dict							=						[]
       for root, _, files in os.walk(__A       ):
              if "__init__.py" in files:
                     a_      :	Dict							=						sort_imports(os.path.join(__A						,					'__init__.py'       )						,					check_only=__A       )
                     if result:
                            a_      :	Tuple							=						[os.path.join(__A						,					'__init__.py'       )]
       if len(__A       ) > 0:
              raise ValueError(F"""Would overwrite {len(__A       )} files, run `make style`."""       )


if __name__ == "__main__":
   UpperCAmelCase_   :				int						      = argparse.ArgumentParser()
   parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
   UpperCAmelCase_   :				Tuple						      = parser.parse_args()

   sort_imports_in_all_inits(check_only=args.check_only)


