import tensorflow as tf

from onnx_tf.handlers.backend_handler import BackendHandler
from onnx_tf.handlers.handler import onnx_op
from onnx_tf.handlers.handler import tf_func


@onnx_op("Selu")
@tf_func(tf.nn.selu)
class Selu(BackendHandler):

  @classmethod
  def _common(cls, node, **kwargs):
    tensor_dict = kwargs["tensor_dict"]
    if "alpha" not in node.attrs and "gamma" not in node.attrs:
      return [cls.make_tensor_from_onnx_node(node, **kwargs)]

    x = tensor_dict[node.inputs[0]]
    alpha = node.attrs.get("alpha", 1.67326319217681884765625)
    gamma = node.attrs.get("gamma", 1.05070102214813232421875)

    return [
        tf.clip_by_value(x, 0, tf.reduce_max(x)) * gamma +
        (tf.exp(tf.clip_by_value(x, tf.reduce_min(x), 0)) - 1) * alpha * gamma
    ]

  @classmethod
  def version_1(cls, node, **kwargs):
    return cls._common(node, **kwargs)

  @classmethod
  def version_6(cls, node, **kwargs):
    return cls._common(node, **kwargs)