
import os

import jsonlines
import numpy as np
from tqdm import tqdm


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







def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   Tuple:
       def choose_first(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__=False    ):
              assert isinstance(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )
              if len(SCREAMING_SNAKE_CASE__    ) == 1:
                     lowercase							:					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:
                            lowercase							:					Optional[int]	     =				{k: [a[k]] for k in a}
                     if len(a["""start_token"""]    ) > 0:
                            break
              return a

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

       # disregard some samples
       if len(answer["""start_token"""]    ) > 1 or answer["start_token"] == answer["end_token"]:
              lowercase							:					List[Any]	     =				True
       else:
              lowercase							:					Union[str, Any]	     =				False

       lowercase							:					Optional[Any]	     =				["""start_token""", """end_token""", """start_byte""", """end_byte""", """text"""]
       if not all(isinstance(answer[k] ,     SCREAMING_SNAKE_CASE__    ) for k in cols    ):
              raise ValueError("""Issue in ID""" ,     example["""id"""]    )

       return answer







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__=False    )			->   Dict:
       lowercase							:					Optional[Any]	     =				_get_single_answer(SCREAMING_SNAKE_CASE__    )
       # 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
              lowercase							:					Dict	     =				example["""document"""]["""tokens"""]
              lowercase							:					Optional[int]	     =				[]
              for i in range(len(doc["""token"""]    )    ):
                     if not doc["is_html"][i]:
                            context.append(doc["""token"""][i]    )
              return {
                  "context": " ".join(SCREAMING_SNAKE_CASE__    ),
                  "answer": {
                      "start_token": -100,  # ignore index in cross-entropy
                      "end_token": -100,  # 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

       lowercase							:					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

       lowercase							:					Dict	     =				example["""document"""]["""tokens"""]
       lowercase							:					Dict	     =				answer["""start_token"""]
       lowercase							:					int	     =				answer["""end_token"""]

       lowercase							:					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
       lowercase							:					Tuple	     =				""" """.join(context[start_token:end_token]    )

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

       return {
           "context": " ".join(SCREAMING_SNAKE_CASE__    ),
           "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 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__=2_048 ,     SCREAMING_SNAKE_CASE__=4_096 ,     SCREAMING_SNAKE_CASE__=True    )			->   Any:
       # overlap will be of doc_stride - q_len

       lowercase							:					Union[str, Any]	     =				get_context_and_ans(SCREAMING_SNAKE_CASE__ ,     assertion=SCREAMING_SNAKE_CASE__    )
       lowercase							:					Tuple	     =				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"],
                  },
              }

       lowercase							:					Optional[Any]	     =				tokenizer(example["""question"""]["""text"""] ,     out["""context"""]    ).input_ids
       lowercase							:					List[Any]	     =				input_ids.index(tokenizer.sep_token_id    ) + 1

       # return yes/no
       if answer["category"][0] in ["yes", "no"]:  # category is list with one element
              lowercase							:					int	     =				[]
              lowercase							:					Union[str, Any]	     =				[]
              lowercase							:					str	     =				input_ids[:q_len]
              lowercase							:					Union[str, Any]	     =				range(SCREAMING_SNAKE_CASE__ ,     len(SCREAMING_SNAKE_CASE__    ) ,     max_length - doc_stride    )
              for i in doc_start_indices:
                     lowercase							:					Dict	     =				i + max_length - q_len
                     lowercase							:					Dict	     =				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": [-100] * len(SCREAMING_SNAKE_CASE__    ),
                      "end_token": [-100] * len(SCREAMING_SNAKE_CASE__    ),
                      "category": category,
                  },
              }

       lowercase							:					Optional[int]	     =				out["""context"""].split()
       lowercase							:					List[str]	     =				splitted_context[answer["""end_token"""]]
       lowercase							:					Union[str, Any]	     =				len(
           tokenizer(
               """ """.join(splitted_context[: answer["""start_token"""]]    ) ,     add_special_tokens=SCREAMING_SNAKE_CASE__ ,     ).input_ids    )
       lowercase							:					List[str]	     =				len(
           tokenizer(""" """.join(splitted_context[: answer["""end_token"""]]    ) ,     add_special_tokens=SCREAMING_SNAKE_CASE__    ).input_ids    )

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

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

       lowercase							:					Optional[Any]	     =				input_ids[answer["""start_token"""] : answer["""end_token"""] + 1]  # right & left are inclusive
       lowercase							:					Dict	     =				answer["""start_token"""]
       lowercase							:					str	     =				answer["""end_token"""]

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

       if len(SCREAMING_SNAKE_CASE__    ) <= 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"],
                  },
              }

       lowercase							:					Any	     =				input_ids[:q_len]
       lowercase							:					Tuple	     =				range(SCREAMING_SNAKE_CASE__ ,     len(SCREAMING_SNAKE_CASE__    ) ,     max_length - doc_stride    )

       lowercase							:					Dict	     =				[]
       lowercase							:					Optional[Any]	     =				[]
       lowercase							:					Optional[Any]	     =				[]
       lowercase							:					str	     =				[]  # null, yes, no, long, short
       for i in doc_start_indices:
              lowercase							:					int	     =				i + max_length - q_len
              lowercase							:					Optional[Any]	     =				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:
                     lowercase							:					Dict	     =				start_token - i + q_len
                     lowercase							:					Tuple	     =				end_token - i + q_len
                     answers_category.append(answer["""category"""][0]    )  # ["short"] -> "short"
              else:
                     lowercase							:					int	     =				-100
                     lowercase							:					Dict	     =				-100
                     answers_category.append("""null"""    )
              lowercase							:					Tuple	     =				inputs[-1][start_token : end_token + 1]

              answers_start_token.append(SCREAMING_SNAKE_CASE__    )
              answers_end_token.append(SCREAMING_SNAKE_CASE__    )
              if assertion:
                     if new != old and new != [tokenizer.cls_token_id]:
                            print("""ISSUE in strided for ID:""" ,     example["""id"""]    )
                            print("""New:""" ,     tokenizer.decode(SCREAMING_SNAKE_CASE__    )    )
                            print("""Old:""" ,     tokenizer.decode(SCREAMING_SNAKE_CASE__    ) ,     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 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__=2_048 ,     SCREAMING_SNAKE_CASE__=4_096 ,     SCREAMING_SNAKE_CASE__=False    )			->   Optional[int]:
       lowercase							:					List[Any]	     =				get_strided_contexts_and_ans(
           SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     doc_stride=SCREAMING_SNAKE_CASE__ ,     max_length=SCREAMING_SNAKE_CASE__ ,     assertion=SCREAMING_SNAKE_CASE__ ,     )

       return example







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   List[Any]:
       with jsonlines.open(SCREAMING_SNAKE_CASE__ ,     """a"""    ) as writer:
              for example in tqdm(SCREAMING_SNAKE_CASE__ ,     total=len(SCREAMING_SNAKE_CASE__    ) ,     desc="""Saving samples ... """    ):
                     lowercase							:					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

  lowercase  : str						   =							load_dataset("""natural_questions""")
  lowercase  : Dict						   =							BigBirdTokenizer.from_pretrained("""google/bigbird-roberta-base""")

  lowercase  : Any						   =							data["""train""" if PROCESS_TRAIN == """true""" else """validation"""]

  lowercase  : Any						   =							{
      """tokenizer""": tokenizer,
      """doc_stride""": DOC_STRIDE,
      """max_length""": MAX_LENGTH,
      """assertion""": False,
  }
  lowercase  : Dict						   =							data.map(prepare_inputs, fn_kwargs=fn_kwargs)
  lowercase  : Any						   =							data.remove_columns(["""annotations""", """document""", """id""", """question"""])
  print(data)

  np.random.seed(SEED)
  lowercase  : Optional[Any]						   =							"""nq-training.jsonl""" if PROCESS_TRAIN == """true""" else """nq-validation.jsonl"""
  save_to_disk(data, file_name=cache_file_name)


def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   Union[str, Any]:
       global f  # a global dp table for knapsack
       if f[i][j] < 0:
              if j < wt[i - 1]:
                     lowercase							:					str	     =				mf_knapsack(i - 1 ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )
              else:
                     lowercase							:					Optional[int]	     =				max(
                         mf_knapsack(i - 1 ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    ) ,     mf_knapsack(i - 1 ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     j - wt[i - 1]    ) + val[i - 1] ,     )
              lowercase							:					List[Any]	     =				val
       return f[i][j]







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   Any:
       lowercase							:					Optional[int]	     =				[[0] * (w + 1) for _ in range(n + 1    )]

       for i in range(1 ,     n + 1    ):
              for w_ in range(1 ,     w + 1    ):
                     if wt[i - 1] <= w_:
                            lowercase							:					Union[str, Any]	     =				max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]] ,     dp[i - 1][w_]    )
                     else:
                            lowercase							:					Any	     =				dp[i - 1][w_]

       return dp[n][w_], dp







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   Optional[Any]:
       if not (isinstance(SCREAMING_SNAKE_CASE__ ,     (list, tuple)    ) and isinstance(SCREAMING_SNAKE_CASE__ ,     (list, tuple)    )):
              raise ValueError(
                  """Both the weights and values vectors must be either lists or tuples"""    )

       lowercase							:					Optional[Any]	     =				len(SCREAMING_SNAKE_CASE__    )
       if num_items != len(SCREAMING_SNAKE_CASE__    ):
              lowercase							:					Optional[Any]	     =				(
                  """The number of weights must be the same as the number of values.\n"""
                  f"But got {num_items} weights and {len(SCREAMING_SNAKE_CASE__    )} values"
              )
              raise ValueError(SCREAMING_SNAKE_CASE__    )
       for i in range(SCREAMING_SNAKE_CASE__    ):
              if not isinstance(wt[i] ,     SCREAMING_SNAKE_CASE__    ):
                     lowercase							:					Tuple	     =				(
                         """All weights must be integers but got weight of """
                         f"type {type(wt[i]    )} at index {i}"
                     )
                     raise TypeError(SCREAMING_SNAKE_CASE__    )

       lowercase     ,      lowercase							:					Any	     =				knapsack(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )
       lowercase							:					set	     =				set()
       _construct_solution(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )

       return optimal_val, example_optional_set







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   Optional[int]:
       # for the current item i at a maximum weight j to be part of an optimal subset,
       # the optimal value at (i, j) must be greater than the optimal value at (i-1, j).
       # where i - 1 means considering only the previous items at the given maximum weight
       if i > 0 and j > 0:
              if dp[i - 1][j] == dp[i][j]:
                     _construct_solution(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     i - 1 ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )
              else:
                     optimal_set.add(SCREAMING_SNAKE_CASE__    )
                     _construct_solution(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     i - 1 ,     j - wt[i - 1] ,     SCREAMING_SNAKE_CASE__    )


if __name__ == "__main__":
  lowercase  : Dict						   =							[3, 2, 4, 4]
  lowercase  : List[Any]						   =							[4, 3, 2, 3]
  lowercase  : Tuple						   =							4
  lowercase  : Tuple						   =							6
  lowercase  : Tuple						   =							[[0] * (w + 1)] + [[0] + [-1] * (w + 1) for _ in range(n + 1)]
  lowercase   ,  lowercase  : List[str]						   =							knapsack(w, wt, val, n)
  print(optimal_solution)
  print(mf_knapsack(n, wt, val, w))  # switched the n and w

  # testing the dynamic programming problem with example
  # the optimal subset for the above example are items 3 and 4
  lowercase   ,  lowercase  : Optional[int]						   =							knapsack_with_example_solution(w, wt, val)
  assert optimal_solution == 8
  assert optimal_subset == {3, 4}
  print("""optimal_value = """, optimal_solution)
  print("""An optimal subset corresponding to the optimal value""", optimal_subset)
