class_docstr: Transforms the input vector to model_size with an one-layer MPL, i.e.,
  (batch_size, time_length, input_dim) -> (batch_size, time_length,
  model_size)
class_docstr_tok: ["Transforms","the","input","vector","to","model_size","with","an","one-layer","MPL",",","i.e.",",","(","batch_size",",","time_length",",","input_dim",")","-",">","(","batch_size",",","time_length",",","model_size",")"]
code: def hybrid_forward(self, F, data: Tensor, *args):
      return self.net(data)
  
imports: from typing import Dict, Optional, Tuple
  import mxnet
  from mxnet.gluon import HybridBlock
  from gluonts.mx import Tensor
label_desc: Use image node_id 2 for calling the InputLayer obj's underlying member method code with example usage: obj.hybrid_forward(F, data) and returns: self