class_docstr: A simple wrapper to easily create "linear" graph,
  consisting of layers / symbolic functions with only one input & output.
class_docstr_tok: ["A","simple","wrapper","to","easily","create","``","linear","''","graph",",","consisting","of","layers","\/","symbolic","functions","with","only","one","input","&","output","."]
docstr: Print the underlying tensor and return self. Can be useful to get the
  name of tensors inside :class:`LinearWrap`.
  
  :return: self
docstr_tok: ["Print","the","underlying","tensor","and","return","self",".","Can","be","useful","to","get","the","name","of","tensors","inside",":","class",":","`","LinearWrap","`",".",":","return",":","self"]
code: def print_tensor(self):
      """
      Print the underlying tensor and return self. Can be useful to get the
      name of tensors inside :class:`LinearWrap`.
  
      :return: self
      """
      print(self._t)
      return self
  
file_path: tensorpack/tensorpack/models/linearwrap.py
imports: from types import ModuleType
  import six
  from .registry import get_registered_layer
label_desc: Use image node_id 7 for calling the LinearWrap obj's underlying member method code with example usage: obj.print_tensor() and returns: self