code: def gelu(x, approximate=True):
      x = convert_to_tensor(x)
      # we need to explicitly implement gelu because bfloat16 will trigger
      # DTypePromotionError when using enable_numpy_behavior()
      if approximate:
          coeff = tf.constant(0.044715, x.dtype)
          return (
              tf.constant(0.5, x.dtype)
              * x
              * (
                  tf.constant(1.0, x.dtype)
                  + tf.math.tanh(
                      tf.constant(0.7978845608028654, x.dtype)
                      * (x + coeff * tf.pow(x, 3))
                  )
              )
          )
      else:
          return (
              tf.constant(0.5, x.dtype)
              * x
              * (
                  tf.constant(1.0, x.dtype)
                  + tf.math.erf(
                      x / tf.constant(1.4142135623730951, x.dtype)
                  )
              )
          )
  
imports: import warnings
  import tensorflow
  from keras.backend import standardize_data_format
  from keras.backend import standardize_dtype
  from keras.backend.common.backend_utils import compute_conv_transpose_output_shape
  from keras.backend.config import epsilon
  from keras.backend.tensorflow.core import cast
  from keras.backend.tensorflow.core import convert_to_tensor
label_desc: Use image node_id 14 for calling a global function with example usage: gelu(x, approximate) and returns: unknown, unknown