

import os

import jsonlines
import numpy as np
from tqdm import tqdm


_UpperCamelCase 			=		2048
_UpperCamelCase 			=		4096
_UpperCamelCase 			=		42
_UpperCamelCase 			=		os.environ.pop("PROCESS_TRAIN", "false")
_UpperCamelCase 			=		{"null": 0, "short": 1, "long": 2, "yes": 3, "no": 4}







def 		_lowercase (     lowercase__						):
      def choose_first(lowercase__   ,	lowercase__=False						):
            assert isinstance(lowercase__   ,	lowercase__						)
            if len(lowercase__						) == 1:
                  __lowerCAmelCase					:						Tuple					=					answer[0]
                  return {k: [answer[k]] for k in answer} if is_long_answer else answer
            for a in answer:
                  if is_long_answer:
                        __lowerCAmelCase					:						str					=					{k: [a[k]] for k in a}
                  if len(a['''start_token''']						) > 0:
                        break
            return a

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

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

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

      return answer







def 		_lowercase (     lowercase__   ,	lowercase__=False						):
      __lowerCAmelCase					:						Dict					=					_get_single_answer(lowercase__						)
      # 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
            __lowerCAmelCase					:						Optional[Any]					=					example['''document''']['''tokens''']
            __lowerCAmelCase					:						Union[str, Any]					=					[]
            for i in range(len(doc['''token''']						)						):
                  if not doc["is_html"][i]:
                        context.append(doc['''token'''][i]						)
            return {
                "context": " ".join(lowercase__						),
                "answer": {
                    "start_token": -1_0_0,  # ignore index in cross-entropy
                    "end_token": -1_0_0,  # 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

      __lowerCAmelCase					:						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

      __lowerCAmelCase					:						Optional[Any]					=					example['''document''']['''tokens''']
      __lowerCAmelCase					:						List[Any]					=					answer['''start_token''']
      __lowerCAmelCase					:						str					=					answer['''end_token''']

      __lowerCAmelCase					:						Dict					=					[]
      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
      __lowerCAmelCase					:						Optional[Any]					=					''' '''.join(context[start_token:end_token]						)

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

      return {
          "context": " ".join(lowercase__						),
          "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 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__=2_0_4_8   ,	lowercase__=4_0_9_6   ,	lowercase__=True						):
      # overlap will be of doc_stride - q_len

      __lowerCAmelCase					:						int					=					get_context_and_ans(lowercase__   ,	assertion=lowercase__						)
      __lowerCAmelCase					:						str					=					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"],
                },
            }

      __lowerCAmelCase					:						List[Any]					=					tokenizer(example['''question''']['''text''']   ,	out['''context''']						).input_ids
      __lowerCAmelCase					:						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
            __lowerCAmelCase					:						Optional[Any]					=					[]
            __lowerCAmelCase					:						Any					=					[]
            __lowerCAmelCase					:						Any					=					input_ids[:q_len]
            __lowerCAmelCase					:						str					=					range(lowercase__   ,	len(lowercase__						)   ,	max_length - doc_stride						)
            for i in doc_start_indices:
                  __lowerCAmelCase					:						Optional[Any]					=					i + max_length - q_len
                  __lowerCAmelCase					:						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": [-1_0_0] * len(lowercase__						),
                    "end_token": [-1_0_0] * len(lowercase__						),
                    "category": category,
                },
            }

      __lowerCAmelCase					:						Tuple					=					out['''context'''].split()
      __lowerCAmelCase					:						Tuple					=					splitted_context[answer['''end_token''']]
      __lowerCAmelCase					:						Optional[int]					=					len(
          tokenizer(
              ''' '''.join(splitted_context[: answer['''start_token''']]						)   ,	add_special_tokens=lowercase__   ,	).input_ids						)
      __lowerCAmelCase					:						str					=					len(
          tokenizer(''' '''.join(splitted_context[: answer['''end_token''']]						)   ,	add_special_tokens=lowercase__						).input_ids						)

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

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

      __lowerCAmelCase					:						Dict					=					input_ids[answer['''start_token'''] : answer['''end_token'''] + 1]  # right & left are inclusive
      __lowerCAmelCase					:						Optional[int]					=					answer['''start_token''']
      __lowerCAmelCase					:						str					=					answer['''end_token''']

      if assertion:
            __lowerCAmelCase					:						Optional[int]					=					tokenizer.decode(lowercase__						)
            if answer["span"] != new:
                  print('''ISSUE IN TOKENIZATION'''						)
                  print('''OLD:'''   ,	answer['''span''']						)
                  print('''NEW:'''   ,	lowercase__   ,	end='''\n\n'''						)

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

      __lowerCAmelCase					:						int					=					input_ids[:q_len]
      __lowerCAmelCase					:						Tuple					=					range(lowercase__   ,	len(lowercase__						)   ,	max_length - doc_stride						)

      __lowerCAmelCase					:						List[str]					=					[]
      __lowerCAmelCase					:						Dict					=					[]
      __lowerCAmelCase					:						int					=					[]
      __lowerCAmelCase					:						Optional[Any]					=					[]  # null, yes, no, long, short
      for i in doc_start_indices:
            __lowerCAmelCase					:						int					=					i + max_length - q_len
            __lowerCAmelCase					:						Tuple					=					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:
                  __lowerCAmelCase					:						List[Any]					=					start_token - i + q_len
                  __lowerCAmelCase					:						Union[str, Any]					=					end_token - i + q_len
                  answers_category.append(answer['''category'''][0]						)  # ["short"] -> "short"
            else:
                  __lowerCAmelCase					:						Any					=					-1_0_0
                  __lowerCAmelCase					:						Tuple					=					-1_0_0
                  answers_category.append('''null'''						)
            __lowerCAmelCase					:						int					=					inputs[-1][start_token : end_token + 1]

            answers_start_token.append(lowercase__						)
            answers_end_token.append(lowercase__						)
            if assertion:
                  if new != old and new != [tokenizer.cls_token_id]:
                        print('''ISSUE in strided for ID:'''   ,	example['''id''']						)
                        print('''New:'''   ,	tokenizer.decode(lowercase__						)						)
                        print('''Old:'''   ,	tokenizer.decode(lowercase__						)   ,	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 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__=2_0_4_8   ,	lowercase__=4_0_9_6   ,	lowercase__=False						):
      __lowerCAmelCase					:						List[Any]					=					get_strided_contexts_and_ans(
          lowercase__   ,	lowercase__   ,	doc_stride=lowercase__   ,	max_length=lowercase__   ,	assertion=lowercase__   ,	)

      return example







def 		_lowercase (     lowercase__   ,	lowercase__						):
      with jsonlines.open(lowercase__   ,	'''a'''						) as writer:
            for example in tqdm(lowercase__   ,	total=len(lowercase__						)   ,	desc='''Saving samples ... '''						):
                  __lowerCAmelCase					:						Tuple					=					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 			=		load_dataset("natural_questions")
 _UpperCamelCase 			=		BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base")

 _UpperCamelCase 			=		data["train" if PROCESS_TRAIN == "true" else "validation"]

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

 np.random.seed(SEED)
 _UpperCamelCase 			=		"nq-training.jsonl" if PROCESS_TRAIN == "true" else "nq-validation.jsonl"
 save_to_disk(data, file_name=cache_file_name)





def 		_lowercase (     lowercase__ = 2_0_0						):
      __lowerCAmelCase					:						Union[str, Any]					=					[1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
      __lowerCAmelCase					:						Dict					=					[0] * (pence + 1)
      __lowerCAmelCase					:						Optional[int]					=					1  # base case: 1 way to make 0 pence

      for coin in coins:
            for i in range(lowercase__   ,	pence + 1   ,	1						):
                  number_of_ways[i] += number_of_ways[i - coin]
      return number_of_ways[pence]


if __name__ == "__main__":
 assert solution(200) == 7_3682


