



'''simple docstring'''
from typing import TYPE_CHECKING

from ..utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available


__SCREAMING_SNAKE_CASE :      Optional[Any]             ={
    """configuration_utils""": ["""GenerationConfig"""],
    """streamers""": ["""TextIteratorStreamer""", """TextStreamer"""],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE :      Union[str, Any]             =[
					    """Constraint""",
					    """ConstraintListState""",
					    """DisjunctiveConstraint""",
					    """PhrasalConstraint""",
					]
					__SCREAMING_SNAKE_CASE :      Optional[int]             =[
					    """BeamHypotheses""",
					    """BeamScorer""",
					    """BeamSearchScorer""",
					    """ConstrainedBeamSearchScorer""",
					]
					__SCREAMING_SNAKE_CASE :      Any             =[
					    """EpsilonLogitsWarper""",
					    """EtaLogitsWarper""",
					    """ForcedBOSTokenLogitsProcessor""",
					    """ForcedEOSTokenLogitsProcessor""",
					    """HammingDiversityLogitsProcessor""",
					    """InfNanRemoveLogitsProcessor""",
					    """LogitsProcessor""",
					    """LogitsProcessorList""",
					    """LogitsWarper""",
					    """MinLengthLogitsProcessor""",
					    """MinNewTokensLengthLogitsProcessor""",
					    """NoBadWordsLogitsProcessor""",
					    """NoRepeatNGramLogitsProcessor""",
					    """PrefixConstrainedLogitsProcessor""",
					    """RepetitionPenaltyLogitsProcessor""",
					    """SequenceBiasLogitsProcessor""",
					    """EncoderRepetitionPenaltyLogitsProcessor""",
					    """TemperatureLogitsWarper""",
					    """TopKLogitsWarper""",
					    """TopPLogitsWarper""",
					    """TypicalLogitsWarper""",
					    """EncoderNoRepeatNGramLogitsProcessor""",
					    """ExponentialDecayLengthPenalty""",
					    """LogitNormalization""",
					]
					__SCREAMING_SNAKE_CASE :      int             =[
					    """MaxNewTokensCriteria""",
					    """MaxLengthCriteria""",
					    """MaxTimeCriteria""",
					    """StoppingCriteria""",
					    """StoppingCriteriaList""",
					    """validate_stopping_criteria""",
					]
					__SCREAMING_SNAKE_CASE :      Dict             =[
					    """GenerationMixin""",
					    """top_k_top_p_filtering""",
					    """GreedySearchEncoderDecoderOutput""",
					    """GreedySearchDecoderOnlyOutput""",
					    """SampleEncoderDecoderOutput""",
					    """SampleDecoderOnlyOutput""",
					    """BeamSearchEncoderDecoderOutput""",
					    """BeamSearchDecoderOnlyOutput""",
					    """BeamSampleEncoderDecoderOutput""",
					    """BeamSampleDecoderOnlyOutput""",
					    """ContrastiveSearchEncoderDecoderOutput""",
					    """ContrastiveSearchDecoderOnlyOutput""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE :      Optional[Any]             =[
					    """TFForcedBOSTokenLogitsProcessor""",
					    """TFForcedEOSTokenLogitsProcessor""",
					    """TFLogitsProcessor""",
					    """TFLogitsProcessorList""",
					    """TFLogitsWarper""",
					    """TFMinLengthLogitsProcessor""",
					    """TFNoBadWordsLogitsProcessor""",
					    """TFNoRepeatNGramLogitsProcessor""",
					    """TFRepetitionPenaltyLogitsProcessor""",
					    """TFTemperatureLogitsWarper""",
					    """TFTopKLogitsWarper""",
					    """TFTopPLogitsWarper""",
					    """TFForceTokensLogitsProcessor""",
					    """TFSuppressTokensAtBeginLogitsProcessor""",
					    """TFSuppressTokensLogitsProcessor""",
					]
					__SCREAMING_SNAKE_CASE :      Any             =[
					    """TFGenerationMixin""",
					    """tf_top_k_top_p_filtering""",
					    """TFGreedySearchDecoderOnlyOutput""",
					    """TFGreedySearchEncoderDecoderOutput""",
					    """TFSampleEncoderDecoderOutput""",
					    """TFSampleDecoderOnlyOutput""",
					    """TFBeamSearchEncoderDecoderOutput""",
					    """TFBeamSearchDecoderOnlyOutput""",
					    """TFBeamSampleEncoderDecoderOutput""",
					    """TFBeamSampleDecoderOnlyOutput""",
					    """TFContrastiveSearchEncoderDecoderOutput""",
					    """TFContrastiveSearchDecoderOnlyOutput""",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE :      Union[str, Any]             =[
					    """FlaxForcedBOSTokenLogitsProcessor""",
					    """FlaxForcedEOSTokenLogitsProcessor""",
					    """FlaxLogitsProcessor""",
					    """FlaxLogitsProcessorList""",
					    """FlaxLogitsWarper""",
					    """FlaxMinLengthLogitsProcessor""",
					    """FlaxTemperatureLogitsWarper""",
					    """FlaxTopKLogitsWarper""",
					    """FlaxTopPLogitsWarper""",
					]
					__SCREAMING_SNAKE_CASE :      Dict             =[
					    """FlaxGenerationMixin""",
					    """FlaxGreedySearchOutput""",
					    """FlaxSampleOutput""",
					    """FlaxBeamSearchOutput""",
					]

if TYPE_CHECKING:
					from .configuration_utils import GenerationConfig
					from .streamers import TextIteratorStreamer, TextStreamer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .beam_constraints import Constraint, ConstraintListState, DisjunctiveConstraint, PhrasalConstraint
										from .beam_search import BeamHypotheses, BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
										from .logits_process import (
										    EncoderNoRepeatNGramLogitsProcessor,
										    EncoderRepetitionPenaltyLogitsProcessor,
										    EpsilonLogitsWarper,
										    EtaLogitsWarper,
										    ExponentialDecayLengthPenalty,
										    ForcedBOSTokenLogitsProcessor,
										    ForcedEOSTokenLogitsProcessor,
										    HammingDiversityLogitsProcessor,
										    InfNanRemoveLogitsProcessor,
										    LogitNormalization,
										    LogitsProcessor,
										    LogitsProcessorList,
										    LogitsWarper,
										    MinLengthLogitsProcessor,
										    MinNewTokensLengthLogitsProcessor,
										    NoBadWordsLogitsProcessor,
										    NoRepeatNGramLogitsProcessor,
										    PrefixConstrainedLogitsProcessor,
										    RepetitionPenaltyLogitsProcessor,
										    SequenceBiasLogitsProcessor,
										    TemperatureLogitsWarper,
										    TopKLogitsWarper,
										    TopPLogitsWarper,
										    TypicalLogitsWarper,
										)
										from .stopping_criteria import (
										    MaxLengthCriteria,
										    MaxNewTokensCriteria,
										    MaxTimeCriteria,
										    StoppingCriteria,
										    StoppingCriteriaList,
										    validate_stopping_criteria,
										)
										from .utils import (
										    BeamSampleDecoderOnlyOutput,
										    BeamSampleEncoderDecoderOutput,
										    BeamSearchDecoderOnlyOutput,
										    BeamSearchEncoderDecoderOutput,
										    ContrastiveSearchDecoderOnlyOutput,
										    ContrastiveSearchEncoderDecoderOutput,
										    GenerationMixin,
										    GreedySearchDecoderOnlyOutput,
										    GreedySearchEncoderDecoderOutput,
										    SampleDecoderOnlyOutput,
										    SampleEncoderDecoderOutput,
										    top_k_top_p_filtering,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tf_logits_process import (
										    TFForcedBOSTokenLogitsProcessor,
										    TFForcedEOSTokenLogitsProcessor,
										    TFForceTokensLogitsProcessor,
										    TFLogitsProcessor,
										    TFLogitsProcessorList,
										    TFLogitsWarper,
										    TFMinLengthLogitsProcessor,
										    TFNoBadWordsLogitsProcessor,
										    TFNoRepeatNGramLogitsProcessor,
										    TFRepetitionPenaltyLogitsProcessor,
										    TFSuppressTokensAtBeginLogitsProcessor,
										    TFSuppressTokensLogitsProcessor,
										    TFTemperatureLogitsWarper,
										    TFTopKLogitsWarper,
										    TFTopPLogitsWarper,
										)
										from .tf_utils import (
										    TFBeamSampleDecoderOnlyOutput,
										    TFBeamSampleEncoderDecoderOutput,
										    TFBeamSearchDecoderOnlyOutput,
										    TFBeamSearchEncoderDecoderOutput,
										    TFContrastiveSearchDecoderOnlyOutput,
										    TFContrastiveSearchEncoderDecoderOutput,
										    TFGenerationMixin,
										    TFGreedySearchDecoderOnlyOutput,
										    TFGreedySearchEncoderDecoderOutput,
										    TFSampleDecoderOnlyOutput,
										    TFSampleEncoderDecoderOutput,
										    tf_top_k_top_p_filtering,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .flax_logits_process import (
										    FlaxForcedBOSTokenLogitsProcessor,
										    FlaxForcedEOSTokenLogitsProcessor,
										    FlaxLogitsProcessor,
										    FlaxLogitsProcessorList,
										    FlaxLogitsWarper,
										    FlaxMinLengthLogitsProcessor,
										    FlaxTemperatureLogitsWarper,
										    FlaxTopKLogitsWarper,
										    FlaxTopPLogitsWarper,
										)
										from .flax_utils import FlaxBeamSearchOutput, FlaxGenerationMixin, FlaxGreedySearchOutput, FlaxSampleOutput
else:
					import sys

					__SCREAMING_SNAKE_CASE :      str             =_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)










'''simple docstring'''
from __future__ import annotations



def 		_SCREAMING_SNAKE_CASE							(				lowerCamelCase__   :      list[int]				):


			'''simple docstring'''







			A:      int														=   [0] * len(lowerCamelCase__				)
			for i in range(1							,							len(lowerCamelCase__				)				):
						A:      Dict														=   duration_times[i - 1] + waiting_times[i - 1]
			return waiting_times



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


			'''simple docstring'''







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



def 		_SCREAMING_SNAKE_CASE							(				lowerCamelCase__   :      list[int]				):


			'''simple docstring'''







			return sum(lowerCamelCase__				) / len(lowerCamelCase__				)



def 		_SCREAMING_SNAKE_CASE							(				lowerCamelCase__   :      list[int]				):


			'''simple docstring'''







			return sum(lowerCamelCase__				) / len(lowerCamelCase__				)


if __name__ == "__main__":
					# process id's
					__SCREAMING_SNAKE_CASE :      Optional[Any]             =[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
					__SCREAMING_SNAKE_CASE :      Dict             =[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
					__SCREAMING_SNAKE_CASE :      Tuple             =calculate_waiting_times(duration_times)
					__SCREAMING_SNAKE_CASE :      List[Any]             =calculate_turnaround_times(duration_times, waiting_times)

					# get the average times
					__SCREAMING_SNAKE_CASE :      List[Any]             =calculate_average_waiting_time(waiting_times)
					__SCREAMING_SNAKE_CASE :      Union[str, 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}""")





