6f405851fcb3be013441810be9a7edbbc04fd2a3,niftynet/layer/loss_segmentation.py,LossFunction,layer_op,#LossFunction#Any#Any#Any#,46

Before Change

                    if weight_map is not None:
                        weight_b = tf.reshape(weight_map[b_ind], ref_shape)
                        if weight_b.get_shape().as_list()[-1] == 1:
                            weight_b = tf.squeeze(weight_b, axis=-1)
                    else:
                        weight_b = None

                    // preparing loss function parameters

After Change

                    pred_b = tf.reshape(pred_b, [-1, self._num_classes])
                    if self._softmax:
                        pred_b = tf.nn.softmax(
                            tf.cast(pred_b, dtype=tf.float32))
                    ground_truth_b = ground_truth[b_ind]
                    weight_b = None if weight_map is None else weight_map[b_ind]

                    loss_params = {

Instances