You can get a tensor by name with tf.get_default_graph().get_tensor_by_name("tensor_name:0")
But can you get an operation, such as Optimizer.minimize
, or an enqueue
operation on a queue?
In my first model I returned all tensors and ops I would need from a build_model
function. But the list of tensors got ugly. In later models I tossed all tensors and ops in a dictionary for easier access. This time around I thought I'd just look up tensors by name as I needed them, but I don't know how to do that with ops.
Or is there a better way to do this? I find various tensors and ops are needed all over the place. Training, inference code, test cases, hence the desire for a nice standard way of accessing the various parts of the graph without passing variables all over the place.
You can use the tf.Graph.get_operation_by_name()
method to get a tf.Operation
by name. For example, to get an operation called "enqueue"
from the default graph:
op = tf.get_default_graph().get_operation_by_name("enqueue")
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