code: def _check_inputs(model, X, emissions, priors):
      if X is None and emissions is None:
          raise ValueError("Must pass in one of `X` or `emissions`.")
  
      emissions = _check_parameter(
          _cast_as_tensor(emissions), "emissions", ndim=3
      )
      if emissions is None:
          emissions = model._emission_matrix(X, priors=priors)
  
      return emissions
  
imports: import time
  import numpy
  import torch
  from .._utils import _cast_as_tensor
  from .._utils import _cast_as_parameter
  from .._utils import _check_parameter
  from .._utils import partition_sequences
  from ..distributions._distribution import Distribution
  from ..kmeans import KMeans
label_desc: Use image node_id 1 for calling a global function with example usage: _check_inputs(model, X, emissions, priors) and returns: emissions