6dad4c27ab4ffa96e0b699b8d5925fbe2a1f9d38,onnx_tf/handlers/backend/upsample.py,Upsample,version_7,#Any#Any#,34

Before Change

  @classmethod
  def version_7(cls, node, **kwargs):
    x = kwargs["tensor_dict"][node.inputs[0]]
    x_shape = x.get_shape().as_list()
    attrs = copy.deepcopy(node.attrs)
    scales = attrs["scales"]
    new_height = np.floor(x_shape[2] * scales[2])
    new_weight = np.floor(x_shape[3] * scales[3])

    mode = attrs.get("mode", "nearest")
    if mode.lower() == "bilinear" or mode.lower() == "linear":
      mode = tf.image.ResizeMethod.BILINEAR

After Change

        [scales])

    with tf.control_dependencies([assert_n_c_scale_is_one]):
      h_w_scale = scales[2:]
      h_w_shape = x_shape[2:]
      new_h_w_shape = tf.cast(h_w_scale * tf.cast(h_w_shape, type(h_w_scale[0])),
                              tf.int32)

      mode = attrs.get("mode", "nearest")
      if mode.lower() == "bilinear" or mode.lower() == "linear":
        mode = tf.image.ResizeMethod.BILINEAR

Instances