class_docstr: Wrapper runtime module.
  
  This is a thin wrapper of the underlying TVM module.
  you can also directly call set_input, run, and get_output
  of underlying module functions
  
  Parameters
  ----------
  module : tvm.runtime.Module
      The internal tvm module that holds the actual graph functions.
  
  Attributes
  ----------
  module : tvm.runtime.Module
      The internal tvm module that holds the actual graph functions.
  
  Examples
  --------
  
  .. code-block:: python
  
      import tvm
      from tvm import relay
      from tvm.contrib import graph_executor
  
      # build the library using graph executor
      lib = relay.build(...)
      lib.export_library("compiled_lib.so")
      # load it back as a runtime
      lib: tvm.runtime.Module = tvm.runtime.load_module("compiled_lib.so")
      # Call the library factory function for default and create
      # a new runtime.Module, wrap with graph module.
      gmod = graph_executor.GraphModule(lib["default"](dev))
      # use the graph module.
      gmod.set_input("x", data)
      gmod.run()
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docstr: Get inputs index via input name.
  
  Parameters
  ----------
  name : str
     The input key name
  
  Returns
  -------
  index: int
      The input index. -1 will be returned if the given input name is not found.
docstr_tok: ["Get","inputs","index","via","input","name",".","Parameters","--","--","--","--","--","name",":","str","The","input","key","name","Returns","--","--","--","-","index",":","int","The","input","index",".","-1","will","be","returned","if","the","given","input","name","is","not","found","."]
code: def get_input_index(self, name):
      """Get inputs index via input name.
  
      Parameters
      ----------
      name : str
         The input key name
  
      Returns
      -------
      index: int
          The input index. -1 will be returned if the given input name is not found.
      """
      return self._get_input_index(name)
  
imports: import numpy
  import tvm._ffi
  from tvm.rpc import _ffi_api
  from tvm.rpc import base
  from tvm._ffi.base import string_types
  from tvm._ffi.runtime_ctypes import Device
label_desc: Use image node_id 9 for calling the GraphModule obj's underlying member method code with example usage: obj.get_input_index(name) and returns: self