class_docstr: Inspects a given class and collects information about its instance
  methods.
  
  Args:
      cls (Type): The class to inspect.
docstr: Collects the input data of the inspected function :obj:`func`
  according to its function signature from a data blob.
  
  Args:
      func (callabel or str): The function.
      kwargs (dict[str, Any]): The data blob which may serve as inputs.
docstr_tok: ["Collects","the","input","data","of","the","inspected","function",":","obj",":","`","func","`","according","to","its","function","signature","from","a","data","blob",".","Args",":","func","(","callabel","or","str",")",":","The","function",".","kwargs","(","dict","[","str",",","Any","]",")",":","The","data","blob","which","may","serve","as","inputs","."]
code: def collect_param_data(
      self,
      func: Union[Callable, str],
      kwargs: Dict[str, Any],
  ) -> Dict[str, Any]:
      r"""Collects the input data of the inspected function :obj:`func`
      according to its function signature from a data blob.
  
      Args:
          func (callabel or str): The function.
          kwargs (dict[str, Any]): The data blob which may serve as inputs.
      """
      out_dict: Dict[str, Any] = {}
      for param in self.get_params(func):
          if param.name not in kwargs:
              if param.default is inspect._empty:
                  raise TypeError(
                      f"Parameter '{param.name}' is required"
                  )
              out_dict[param.name] = param.default
          else:
              out_dict[param.name] = kwargs[param.name]
      return out_dict
  
imports: import inspect
  import re
  import sys
  import typing
  from typing import Any, Callable, Dict, List, NamedTuple, Optional, Type, Union
  from torch import Tensor
label_desc: Use image node_id 16 for calling the Inspector obj's underlying member method code with example usage: obj.collect_param_data(func, kwargs) and returns: out_dict