class_docstr: Represents the type of a TensorFlow function.
  
  FunctionType is the canonical way to represent the input/output contract of
  all kinds of functions within the tf.function domain, including:
    - Polymorphic Function
    - Concrete Function
    - Atomic Function
  
  It provides consistent, centralized and layered logic for:
    - Canonicalization of Python input arguments
    - Type-based dispatch to monomorphic functions
    - Packing/unpacking structured python values to Tensors
    - Generation of structured placeholder values for tracing
  
  Additionaly, it also provides:
    - Lossless serialization
    - Native integration with Python function signature representation
    - Seamless migration from older representation formats
docstr: Generate FunctionType from a python Callable.
docstr_tok: ["Generate","FunctionType","from","a","python","Callable","."]
code: def from_callable(
      cls, obj: Callable[..., Any], *, follow_wrapped: bool = True
  ) -> "FunctionType":
      """Generate FunctionType from a python Callable."""
      signature = super().from_callable(
          obj, follow_wrapped=follow_wrapped
      )
      # TODO(fmuham): Support TraceType-based annotations.
      parameters = [
          Parameter(p.name, p.kind, p.default is not p.empty, None)
          for p in signature.parameters.values()
      ]
  
      return FunctionType(parameters)
  
imports: import collections
  import inspect
  from typing import Any, Callable, Dict, List, Mapping, Optional, Sequence, Tuple
  from absl import logging
  from tensorflow.core.function import trace_type
  from tensorflow.core.function.polymorphism import function_type_pb2
  from tensorflow.core.function.trace_type import serialization
  from tensorflow.python.types import core
  from tensorflow.python.types import trace
label_desc: Use image node_id 5 for calling the FunctionType obj's underlying member method code with example usage: obj.from_callable(cls, obj) and returns: FunctionType