code: def __init__(
      self,
      distr_outputs: List[DistributionOutput],
      prefix: Optional[str] = None,
  ) -> None:
      super().__init__()
      self.num_components = len(distr_outputs)
      self.component_projections: List[gluon.HybridBlock] = []
      with self.name_scope():
          self.proj_mixture_probs = gluon.nn.HybridSequential()
          self.proj_mixture_probs.add(
              gluon.nn.Dense(
                  self.num_components,
                  prefix=f"{prefix}_pi_",
                  flatten=False,
              )
          )
          self.proj_mixture_probs.add(gluon.nn.HybridLambda("softmax"))
  
          for k, do in enumerate(distr_outputs):
              self.component_projections.append(
                  do.get_args_proj(prefix=str(k))
              )
              self.register_child(self.component_projections[-1])
  
imports: from typing import List, Optional, Tuple
  import mxnet
  import numpy
  from mxnet import gluon
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from .distribution import MAX_SUPPORT_VAL, Distribution, _expand_param, _index_tensor, getF
  from .distribution_output import DistributionOutput
label_desc: Use image node_id 1 to create a new MixtureArgs object from inherited base classes: gluon with example: obj = MixtureArgs(distr_outputs, prefix)