class_docstr: Stack StochasticBlock sequentially.
      
class_docstr_tok: ["Stack","StochasticBlock","sequentially","."]
code: def forward(self, x, *args):
      # pylint: disable=arguments-differ
      for block in self._children.values():
          x = block()(x, *args)
          args = []
          if isinstance(x, (tuple, list)):
              args = x[1:]
              x = x[0]
      if args:
          x = tuple([x] + list(args))
      for block in self._layers:
          if hasattr(block, "_losses"):
              self.add_loss(block._losses)
      return x
  
file_path: mxnet/python/mxnet/gluon/probability/block/stochastic_block.py
imports: from functools import wraps
  from ...block import HybridBlock
  from ...utils import _indent
label_desc: Use image node_id 3 for calling the StochasticSequential obj's underlying member method code with example usage: obj.forward(x) and returns: x