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from enum import Enum
class ExplicitEnum(str, Enum):
"""
Enum with more explicit error message for missing values.
"""
def __str__(self):
return str(self.value)
@classmethod
def _missing_(cls, value):
raise ValueError(
f"{value} is not a valid {cls.__name__}, please select one of {list(cls._value2member_map_.keys())}"
)
class PaddingStrategy(ExplicitEnum):
"""
Possible values for the `padding` argument in [`EventTokenizer.__call__`]. Useful for tab-completion in an
IDE.
"""
LONGEST = "longest"
MAX_LENGTH = "max_length"
DO_NOT_PAD = "do_not_pad"
class TensorType(ExplicitEnum):
"""
Possible values for the `return_tensors` argument in [`EventTokenizerBase.__call__`]. Useful for
tab-completion in an IDE.
"""
PYTORCH = "pt"
NUMPY = "np"
class RunnerPhase(ExplicitEnum):
"""Model runner phase enum.
"""
TRAIN = 'train'
VALIDATE = 'validate'
PREDICT = 'predict'
class LossFunction(ExplicitEnum):
"""Loss function for neural TPP model.
"""
LOGLIKE = 'loglike'
PARTIAL_TIME_LOSS = 'rmse'
PARTIAL_EVENT_LOSS = 'accuracy'
class LogConst:
"""Format for log handler.
"""
DEFAULT_FORMAT = '[%(asctime)s] [%(levelname)s] %(message)s'
DEFAULT_FORMAT_LONG = '%(asctime)s - %(filename)s[pid:%(process)d;line:%(lineno)d:%(funcName)s]' \
' - %(levelname)s: %(message)s'
class PredOutputIndex:
"""Positional index for the output tuple in ModelRunner.
"""
TimePredIndex = 0
TypePredIndex = 1
class DefaultRunnerConfig:
DEFAULT_DATASET_ID = 'conttime'
class TruncationStrategy(ExplicitEnum):
"""
Possible values for the `truncation` argument in [`EventTokenizer.__call__`]. Useful for tab-completion in
an IDE.
"""
LONGEST_FIRST = "longest_first"
DO_NOT_TRUNCATE = "do_not_truncate"
class Backend(ExplicitEnum):
"""
Possible values for the `backend` argument in configuration.
"""
Torch = 'torch'
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