import os

import jsonlines
import numpy as np
from tqdm import tqdm


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



def lowerCamelCase  (       SCREAMING_SNAKE_CASE     ):
    '''simple docstring'''







    def choose_first(SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE=False     ):
        assert isinstance(SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     )
        if len(SCREAMING_SNAKE_CASE     ) == 1:
            __UpperCamelCase					: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:
                __UpperCamelCase					:Dict        =		{k: [a[k]] for k in a}
            if len(a['''start_token''']     ) > 0:
                break
        return a

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

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

    __UpperCamelCase					:Dict        =		['''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 lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE=False     ):
    '''simple docstring'''







    __UpperCamelCase					:Union[str, 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
        __UpperCamelCase					:int        =		example['''document''']['''tokens''']
        __UpperCamelCase					:Tuple        =		[]
        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

    __UpperCamelCase					:Union[str, 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

    __UpperCamelCase					:List[str]        =		example['''document''']['''tokens''']
    __UpperCamelCase					:int        =		answer['''start_token''']
    __UpperCamelCase					:str        =		answer['''end_token''']

    __UpperCamelCase					:int        =		[]
    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
    __UpperCamelCase					:int        =		''' '''.join(context[start_token:end_token]     )

    # checking above code
    if assertion:
        __UpperCamelCase					:Dict        =		doc['''is_html'''][answer['''start_token'''] : answer['''end_token''']]
        __UpperCamelCase					:Dict        =		doc['''token'''][answer['''start_token'''] : answer['''end_token''']]
        __UpperCamelCase					:Optional[int]        =		''' '''.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 lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE=2_048  ,      SCREAMING_SNAKE_CASE=4_096  ,      SCREAMING_SNAKE_CASE=True     ):
    '''simple docstring'''







    __UpperCamelCase					:Any        =		get_context_and_ans(SCREAMING_SNAKE_CASE  ,      assertion=SCREAMING_SNAKE_CASE     )
    __UpperCamelCase					:Union[str, 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"],
            },
        }

    __UpperCamelCase					:List[Any]        =		tokenizer(example['''question''']['''text''']  ,      out['''context''']     ).input_ids
    __UpperCamelCase					: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
        __UpperCamelCase					:List[str]        =		[]
        __UpperCamelCase					:Dict        =		[]
        __UpperCamelCase					:Any        =		input_ids[:q_len]
        __UpperCamelCase					:Optional[int]        =		range(SCREAMING_SNAKE_CASE  ,      len(SCREAMING_SNAKE_CASE     )  ,      max_length - doc_stride     )
        for i in doc_start_indices:
            __UpperCamelCase					:List[str]        =		i + max_length - q_len
            __UpperCamelCase					:List[Any]        =		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,
            },
        }

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

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

    if assertion:
        __UpperCamelCase					:Optional[int]        =		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"],
            },
        }

    __UpperCamelCase					:Dict        =		input_ids[:q_len]
    __UpperCamelCase					:Optional[Any]        =		range(SCREAMING_SNAKE_CASE  ,      len(SCREAMING_SNAKE_CASE     )  ,      max_length - doc_stride     )

    __UpperCamelCase					:Union[str, Any]        =		[]
    __UpperCamelCase					:Dict        =		[]
    __UpperCamelCase					:Union[str, Any]        =		[]
    __UpperCamelCase					:Dict        =		[]  # null, yes, no, long, short
    for i in doc_start_indices:
        __UpperCamelCase					:int        =		i + max_length - q_len
        __UpperCamelCase					:Optional[int]        =		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:
            __UpperCamelCase					:List[str]        =		start_token - i + q_len
            __UpperCamelCase					:str        =		end_token - i + q_len
            answers_category.append(answer['''category'''][0]     )  # ["short"] -> "short"
        else:
            __UpperCamelCase					:int        =		-100
            __UpperCamelCase					:Optional[Any]        =		-100
            answers_category.append('''null'''     )
        __UpperCamelCase					:Optional[int]        =		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 lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE=2_048  ,      SCREAMING_SNAKE_CASE=4_096  ,      SCREAMING_SNAKE_CASE=False     ):
    '''simple docstring'''







    __UpperCamelCase					:Dict        =		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 lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     ):
    '''simple docstring'''







    with jsonlines.open(SCREAMING_SNAKE_CASE  ,      '''a'''     ) as writer:
        for example in tqdm(SCREAMING_SNAKE_CASE  ,      total=len(SCREAMING_SNAKE_CASE     )  ,      desc='''Saving samples ... '''     ):
            __UpperCamelCase					:Optional[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										= load_dataset('''natural_questions''')
    __lowercase										= BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base''')

    __lowercase										= data['''train''' if PROCESS_TRAIN == '''true''' else '''validation''']

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

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






from __future__ import annotations

from math import pi



def lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     ):
    '''simple docstring'''







    if (inductance, frequency, reactance).count(0     ) != 1:
        raise ValueError('''One and only one argument must be 0'''     )
    if inductance < 0:
        raise ValueError('''Inductance cannot be negative'''     )
    if frequency < 0:
        raise ValueError('''Frequency cannot be negative'''     )
    if reactance < 0:
        raise ValueError('''Inductive reactance cannot be negative'''     )
    if inductance == 0:
        return {"inductance": reactance / (2 * pi * frequency)}
    elif frequency == 0:
        return {"frequency": reactance / (2 * pi * inductance)}
    elif reactance == 0:
        return {"reactance": 2 * pi * frequency * inductance}
    else:
        raise ValueError('''Exactly one argument must be 0'''     )


if __name__ == "__main__":
    import doctest

    doctest.testmod()





