code: def hybrid_forward(
      self, F, x: Tensor, bin_centers: Tensor
  ) -> Tuple[Tensor, Tensor]:
      ps = self.proj(x)
      reshaped_probs = ps.reshape(
          shape=(-2, -1, self.num_bins), reverse=1
      )
      bin_centers = F.broadcast_add(bin_centers, ps.zeros_like())
      return reshaped_probs, bin_centers
  
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, _sample_multiple, getF
  from .distribution_output import DistributionOutput
label_desc: Use image node_id 2 for calling the BinnedArgs obj's underlying member method code with example usage: obj.hybrid_forward(F, x, bin_centers) and returns: reshaped_probs,  bin_centers