def _hinge_loss(logits, target): check_shape_op = control_flow_ops.Assert( math_ops.less_equal(array_ops.rank(target), 2), ["target's shape should be either [batch_size, 1] or [batch_size]"]) with ops.control_dependencies([check_shape_op]): target = array_ops.reshape(target, shape=[array_ops.shape(target)[0], 1]) return losses.hinge_loss(logits, target)
def loss_fn(logits, labels): check_shape_op = control_flow_ops.Assert( math_ops.less_equal(array_ops.rank(labels), 2), ["labels shape should be either [batch_size, 1] or [batch_size]"]) with ops.control_dependencies([check_shape_op]): labels = array_ops.reshape( labels, shape=[array_ops.shape(labels)[0], 1]) return losses.hinge_loss(logits, labels)
def _loss_fn(logits, labels): with ops.name_scope(None, "hinge_loss", (logits, labels)) as name: check_shape_op = control_flow_ops.Assert( math_ops.less_equal(array_ops.rank(labels), 2), ("labels shape should be either [batch_size, 1] or [batch_size]",)) with ops.control_dependencies((check_shape_op,)): labels = array_ops.reshape( labels, shape=(array_ops.shape(labels)[0], 1)) return losses.hinge_loss(logits, labels, scope=name)
def _loss_fn(logits, labels): with ops.name_scope(None, "hinge_loss", (logits, labels)) as name: check_shape_op = control_flow_ops.Assert( math_ops.less_equal(array_ops.rank(labels), 2), ("labels shape should be either [batch_size, 1] or [batch_size]", )) with ops.control_dependencies((check_shape_op, )): labels = array_ops.reshape( labels, shape=(array_ops.shape(labels)[0], 1)) return losses.hinge_loss(logits, labels, scope=name)
def _loss_fn(logits, labels): with ops.name_scope(None, "hinge_loss", (logits, labels)) as name: with ops.control_dependencies((_assert_labels_rank(labels),)): labels = array_ops.reshape(labels, shape=(-1, 1)) return losses.hinge_loss(logits, labels, scope=name)