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("Min")
@tf_func(tf.reduce_min)
class Min(BackendHandler):

  @classmethod
  def get_attrs_processor_param(cls):
    return {"default": {"axis": 0}}

  @classmethod
  def _common(cls, node, **kwargs):
    values = [kwargs["tensor_dict"][inp] for inp in node.inputs]
    return [
        cls.make_tensor_from_onnx_node(
            node, inputs=[tf.stack(values)], **kwargs)
    ]

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

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

  @classmethod
  def version_8(cls, node, **kwargs):
    return cls._common(node, **kwargs)
