






'''simple docstring'''
from collections import namedtuple

a_					=	namedtuple('from_to', 'from_ to')

a_					=	{
    'cubicmeter': from_to(1, 1),
    'litre': from_to(0.001, 1_0_0_0),
    'kilolitre': from_to(1, 1),
    'gallon': from_to(0.00454, 264.172),
    'cubicyard': from_to(0.76455, 1.30795),
    'cubicfoot': from_to(0.028, 35.3147),
    'cup': from_to(0.000236588, 4226.75),
}





def 	_a(					UpperCamelCase__			:  float,		UpperCamelCase__			:  str,		UpperCamelCase__			:  str							):




      '''simple docstring'''






      if from_type not in METRIC_CONVERSION:
            raise ValueError(
                f"Invalid 'from_type' value: {from_type!r}  Supported values are:\n"
                + ''', '''.join(UpperCamelCase__							)							)
      if to_type not in METRIC_CONVERSION:
            raise ValueError(
                f"Invalid 'to_type' value: {to_type!r}.  Supported values are:\n"
                + ''', '''.join(UpperCamelCase__							)							)
      return value * METRIC_CONVERSION[from_type].from_ * METRIC_CONVERSION[to_type].to


if __name__ == "__main__":
  import doctest

  doctest.testmod()







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

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_					=	{
    'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					=	[
      'MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'MegatronBertForCausalLM',
      'MegatronBertForMaskedLM',
      'MegatronBertForMultipleChoice',
      'MegatronBertForNextSentencePrediction',
      'MegatronBertForPreTraining',
      'MegatronBertForQuestionAnswering',
      'MegatronBertForSequenceClassification',
      'MegatronBertForTokenClassification',
      'MegatronBertModel',
      'MegatronBertPreTrainedModel',
  ]

if TYPE_CHECKING:
  from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_megatron_bert import (
        MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        MegatronBertForCausalLM,
        MegatronBertForMaskedLM,
        MegatronBertForMultipleChoice,
        MegatronBertForNextSentencePrediction,
        MegatronBertForPreTraining,
        MegatronBertForQuestionAnswering,
        MegatronBertForSequenceClassification,
        MegatronBertForTokenClassification,
        MegatronBertModel,
        MegatronBertPreTrainedModel,
    )

else:
  import sys

  a_					=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)