

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__	:   Union[str, Any]								=     {
    "configuration_dpr": ["DPR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPRConfig"],
    "tokenization_dpr": [
        "DPRContextEncoderTokenizer",
        "DPRQuestionEncoderTokenizer",
        "DPRReaderOutput",
        "DPRReaderTokenizer",
    ],
}


try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__	:   List[str]								=     [
           "DPRContextEncoderTokenizerFast",
           "DPRQuestionEncoderTokenizerFast",
           "DPRReaderTokenizerFast",
       ]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__	:   Any								=     [
           "DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DPRContextEncoder",
           "DPRPretrainedContextEncoder",
           "DPRPreTrainedModel",
           "DPRPretrainedQuestionEncoder",
           "DPRPretrainedReader",
           "DPRQuestionEncoder",
           "DPRReader",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__	:   int								=     [
           "TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFDPRContextEncoder",
           "TFDPRPretrainedContextEncoder",
           "TFDPRPretrainedQuestionEncoder",
           "TFDPRPretrainedReader",
           "TFDPRQuestionEncoder",
           "TFDPRReader",
       ]


if TYPE_CHECKING:
       from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
       from .tokenization_dpr import (
           DPRContextEncoderTokenizer,
           DPRQuestionEncoderTokenizer,
           DPRReaderOutput,
           DPRReaderTokenizer,
       )

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_dpr_fast import (
                  DPRContextEncoderTokenizerFast,
                  DPRQuestionEncoderTokenizerFast,
                  DPRReaderTokenizerFast,
              )

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_dpr import (
                  DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DPRContextEncoder,
                  DPRPretrainedContextEncoder,
                  DPRPreTrainedModel,
                  DPRPretrainedQuestionEncoder,
                  DPRPretrainedReader,
                  DPRQuestionEncoder,
                  DPRReader,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_dpr import (
                  TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFDPRContextEncoder,
                  TFDPRPretrainedContextEncoder,
                  TFDPRPretrainedQuestionEncoder,
                  TFDPRPretrainedReader,
                  TFDPRQuestionEncoder,
                  TFDPRReader,
              )

else:
       import sys

       UpperCamelCase__	:   str								=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





from __future__ import annotations


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		list[int]							):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_						=    [0] * len(_SCREAMING_SNAKE_CASE							)
    for i in range(1			, len(_SCREAMING_SNAKE_CASE							)							):
        SCREAMING_SNAKE_CASE_						=    duration_times[i - 1] + waiting_times[i - 1]
    return waiting_times


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		list[int]			, _SCREAMING_SNAKE_CASE       :		list[int]							):





    """simple docstring"""


    return [
        duration_time + waiting_times[i]
        for i, duration_time in enumerate(_SCREAMING_SNAKE_CASE							)
    ]


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		list[int]							):





    """simple docstring"""


    return sum(_SCREAMING_SNAKE_CASE							) / len(_SCREAMING_SNAKE_CASE							)


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		list[int]							):





    """simple docstring"""


    return sum(_SCREAMING_SNAKE_CASE							) / len(_SCREAMING_SNAKE_CASE							)


if __name__ == "__main__":
       # process id's
       UpperCamelCase__	:   List[str]								=     [1, 2, 3]

       # ensure that we actually have processes
       if len(processes) == 0:
              print("Zero amount of processes")
              raise SystemExit(0)

       # duration time of all processes
       UpperCamelCase__	:   Any								=     [19, 8, 9]

       # ensure we can match each id to a duration time
       if len(duration_times) != len(processes):
              print("Unable to match all id's with their duration time")
              raise SystemExit(0)

       # get the waiting times and the turnaround times
       UpperCamelCase__	:   List[str]								=     calculate_waiting_times(duration_times)
       UpperCamelCase__	:   Union[str, Any]								=     calculate_turnaround_times(duration_times, waiting_times)

       # get the average times
       UpperCamelCase__	:   str								=     calculate_average_waiting_time(waiting_times)
       UpperCamelCase__	:   List[Any]								=     calculate_average_turnaround_time(turnaround_times)

       # print all the results
       print("Process ID\tDuration Time\tWaiting Time\tTurnaround Time")
       for i, process in enumerate(processes):
              print(
                  F'{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t'
                  F'{turnaround_times[i]}'
              )
       print(F'Average waiting time = {average_waiting_time}')
       print(F'Average turn around time = {average_turnaround_time}')


