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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def softplus(x, scale=1.0, name=None):
 """Computes softplus with a scale factor to sharpen of the hinge. This is an alternate non-linearity to relu. It has a similar shape, but it has a smooth transition from the linear part to 0. Args: x: A tensor. scale: A float that sharpens the curve. name: Optional name. Returns: y = log(1 + exp(scale * x)) / scale """

  if scale == 1:
    return tf.nn.softplus(x)
  else:
    with tf.name_scope(name, 'softplus', [x]):
      scale = tf.convert_to_tensor(scale, dtype=x.dtype.base_dtype)
      return tf.nn.softplus(x * scale) / scale