Function create_slot

tensorflow/python/training/slot_creator.py:189–220

Create a slot initialized to the given value. The type of the slot is determined by the given value. Args: primary: The primary `Variable` or `Tensor`. val: A `Tensor` specifying the initial value of the slot. name: Name to use for the slot variable. colocate_with_primary: Bool

(primary, val, name, colocate_with_primary=True, slot_config=None)

def create_slot(primary, val, name, colocate_with_primary=True, slot_config=None):
  """Create a slot initialized to the given value.

  The type of the slot is determined by the given value.

  Args:
    primary: The primary `Variable` or `Tensor`.
    val: A `Tensor` specifying the initial value of the slot.
    name: Name to use for the slot variable.
    colocate_with_primary: Boolean.  If True the slot is located
      on the same device as `primary`.

  Returns:
    A `Variable` object.
  """
  # Scope the slot name in the namespace of the primary variable.
  # Set "primary.op.name + '/' + name" as default name, so the scope name of
  # optimizer can be shared when reuse is True. Meanwhile when reuse is False
  # and the same name has been previously used, the scope name will add '_N'
  # as suffix for unique identifications.
  validate_shape = val.get_shape().is_fully_defined()
  if context.executing_eagerly():
    prefix = primary._shared_name  # pylint: disable=protected-access
  else:
    prefix = primary.op.name
  with variable_scope.variable_scope(None, prefix + "/" + name):
    if colocate_with_primary:
      distribution_strategy = distribution_strategy_context.get_strategy()
      with distribution_strategy.extended.colocate_vars_with(primary):
        return _create_slot_var(primary, val, "", validate_shape, None, None, slot_config)
    else:
      return _create_slot_var(primary, val, "", validate_shape, None, None, slot_config)


def create_slot_with_initializer(primary, initializer, shape, dtype, name,