class_docstr: A container for managing functions.
class_docstr_tok: ["A","container","for","managing","functions","."]
docstr: Looks up a function based on the context and type.
docstr_tok: ["Looks","up","a","function","based","on","the","context","and","type","."]
code: def lookup(
      self,
      function_type: function_type_lib.FunctionType,
      context: Optional[FunctionContext] = None,
  ) -> Optional[Any]:
      """Looks up a function based on the context and type."""
      context = context or FunctionContext()
      if context in self._dispatch_dict:
          dispatch_type = self._dispatch_dict[context].dispatch(
              function_type
          )
          if dispatch_type:
              return self._primary[(context, dispatch_type)]
  
      return None
  
file_path: tensorflow/tensorflow/core/function/polymorphism/function_cache.py
imports: import collections
  from typing import Any, NamedTuple, Optional
  from tensorflow.core.function.polymorphism import function_type
  from tensorflow.core.function.polymorphism import type_dispatch
label_desc: Use image node_id 2 for calling the FunctionCache obj's underlying member method code with example usage: obj.lookup(function_type, context) and returns: None, self