如何按名称获取张量流操作? [英] How to get a tensorflow op by name?

问题描述

您可以使用 tf.get_default_graph().get_tensor_by_name("tensor_name:0")

但是你能得到一个操作，比如Optimizer.minimize，或者一个队列上的enqueue操作?

But can you get an operation, such as Optimizer.minimize, or an enqueue operation on a queue?

在我的第一个模型中，我从 build_model 函数返回了我需要的所有张量和操作.但是张量列表变得丑陋.在后来的模型中，我将所有张量和操作都放入字典中以便于访问.这一次，我想我会在需要时按名称查找张量，但我不知道如何使用 ops 来做到这一点.

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.

或者有更好的方法来做到这一点?我发现到处都需要各种张量和操作.训练、推理代码、测试用例，因此需要一种很好的标准方式来访问图表的各个部分，而无需到处传递变量.

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.

推荐答案

您可以使用 tf.Graph.get_operation_by_name() 方法通过名称获取tf.Operation.例如，要从默认图中获取一个名为 "enqueue" 的操作:

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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