code: def _softfloor_grad_np(x, t):
      x -= 0.5
      frac_part = x - np.floor(x)
      inner_part = (frac_part - 0.5) / t
      return (
          _sigmoid(inner_part)
          * (1 - _sigmoid(inner_part))
          / (t * (1 - 2.0 * _sigmoid(-0.5 / t)))
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import softfloor
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.gradient import value_and_gradient
label_desc: Use image node_id 2 for calling a global function with example usage: _softfloor_grad_np(x, t) and returns: unknown