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