code: def predict_mode():
      """Returns a scope context to be used in 'with' statement
      in which forward pass behavior is set to inference mode,
      without changing the recording states.
  
      Example::
  
          with autograd.record():
              y = model(x)
              with autograd.predict_mode():
                  y = sampling(y)
              backward([y])
      """
      return _RecordingStateScope(None, False)
  
imports: from array import array
  from threading import Lock
  import traceback
  import ctypes
  from ctypes import c_int, c_void_p, CFUNCTYPE, POINTER, cast
  from .base import _LIB, check_call, string_types, mx_uint
  from .base import NDArrayHandle, c_array, c_handle_array, c_array_buf, MXCallbackList, SymbolHandle
  from .ndarray import NDArray, _ndarray_cls
  from .ndarray import _GRAD_REQ_MAP
  from .symbol import Symbol
  from .util import is_np_array
label_desc: Use image node_id 8 for calling a global function with example usage: predict_mode() and returns: _RecordingStateScope