def _get_processor(var):
"""The processor of var."""
if context.executing_eagerly():
if isinstance(var, ops.Tensor):
return optimizer._TensorProcessor(var)
else:
return optimizer._DenseResourceVariableProcessor(var)
if isinstance(var, resource_variable_ops.ResourceVariable) and not var._in_graph_mode:
# True if and only if `var` was initialized eagerly.
return optimizer._DenseResourceVariableProcessor(var)
if var.op.type == "VarHandleOp":
return optimizer._DenseResourceVariableProcessor(var)
if isinstance(var, variables.Variable):
return _RefVariableProcessor(var)
if isinstance(var, ops.Tensor):
return optimizer._TensorProcessor(var)
raise NotImplementedError("Trying to optimize unsupported type ", var)
def _get_processor(v):
"""The processor of v."""
if context.executing_eagerly():
if isinstance(v, ops.Tensor):
return optimizer._TensorProcessor(v)
else:
return optimizer._DenseResourceVariableProcessor(v)
if isinstance(v, de.TrainableWrapper):
return _DenseDynamicEmbeddingTrainableProcessor(v)
if (rvo.is_resource_variable(v) and not v._in_graph_mode): # pylint: disable=protected-access
# True if and only if `v` was initialized eagerly.
return optimizer._DenseResourceVariableProcessor(v)
if v.op.type == "VarHandleOp":
return optimizer._DenseResourceVariableProcessor(v)
if isinstance(v, variables.Variable):
return optimizer._RefVariableProcessor(v)
if isinstance(v, ops.Tensor):
return optimizer._TensorProcessor(v)
raise NotImplementedError("Trying to optimize unsupported type ", v)