def init_restore_or_wait_for_variables():
"""Initialize or restore variables or wait for variables to be initialized."""
session = K._get_session() # pylint: disable=protected-access
worker_context = dc_context.get_current_worker_context()
if not worker_context or worker_context.should_init:
# TODO(yuefengz): if checkpoints exit, restore from checkpoint.
K._initialize_variables(session) # pylint: disable=protected-access
else:
_wait_for_variable_initialization(session)
def init_restore_or_wait_for_variables():
"""Initialize or restore variables or wait for variables to be initialized."""
session = K._get_session() # pylint: disable=protected-access
if not multi_worker_util.has_worker_context(
) or multi_worker_util.should_load_checkpoint():
# TODO(yuefengz): if checkpoints exist, restore from checkpoint.
K._initialize_variables(session) # pylint: disable=protected-access
else:
_wait_for_variable_initialization(session)
def init_restore_or_wait_for_variables():
"""Initialize or restore variables or wait for variables to be initialized."""
session = K._get_session() # pylint: disable=protected-access
worker_context = dc_context.get_current_worker_context()
if not worker_context or worker_context.experimental_should_init:
# TODO(yuefengz): if checkpoints exist, restore from checkpoint.
K._initialize_variables(session) # pylint: disable=protected-access
else:
_wait_for_variable_initialization(session)
def _build(self, shape):
"""Initialize TP, FP, TN, and FN tensors, given the shape of the data."""
if self.multi_label:
if shape.ndims != 2:
raise ValueError(
'`y_true` must have rank=2 when `multi_label` is '
'True. Found rank %s.' % shape.ndims)
variable_shape = tensor_shape.TensorShape(
[tensor_shape.Dimension(self.num_thresholds), shape[1]])
else:
variable_shape = tensor_shape.TensorShape(
[tensor_shape.Dimension(self.num_thresholds)])
# Create metric variables
self.true_positives = self.add_weight(
'true_positives',
shape=variable_shape,
initializer=init_ops.zeros_initializer)
self.true_negatives = self.add_weight(
'true_negatives',
shape=variable_shape,
initializer=init_ops.zeros_initializer)
self.false_positives = self.add_weight(
'false_positives',
shape=variable_shape,
initializer=init_ops.zeros_initializer)
self.false_negatives = self.add_weight(
'false_negatives',
shape=variable_shape,
initializer=init_ops.zeros_initializer)
if self.multi_label:
with ops.init_scope():
# This should only be necessary for handling v1 behavior. In v2, AUC
# should be initialized outside of any tf.functions, and therefore in
# eager mode.
if not context.executing_eagerly():
K._initialize_variables(K._get_session()) # pylint: disable=protected-access
self._built = True
def init_restore_or_wait_for_variables():
"""Initialize or restore variables or wait for variables to be initialized."""
backend._initialize_variables(backend._get_session()) # pylint: disable=protected-access
def variable(value, dtype=_FLOATX, name=None):
v = tf.Variable(np.asarray(value, dtype=dtype), name=name)
_get_session().run(v.initializer)
return v
