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 _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)
