code: def stop_gradient(*args, **kwargs):
      """Identity on the forward pass but 0 (no gradient) on the backward pass."""
      return backend()["stop_gradient"](*args, **kwargs)
  
imports: import contextlib
  import enum
  import gin
  from trax.fastmath.jax import JAX_BACKEND
  from trax.fastmath.numpy import NUMPY_BACKEND
  from trax.fastmath.tf import TF_BACKEND
label_desc: Use image node_id 25 for calling a global function with example usage: stop_gradient() and returns: backend