CODEWITHSUNDEEP
pythontensorflow
J. Zheng
J. Zheng

Reputation: 335

what happens when I write a function using tensorflow ops

I write a function using tensorflow ops. I know the fact when I run the function, it will add many ops to the graph. But I am confused with how to get access of these ops.

for example:

def assign_weights():
    with tf.name_scope('zheng'):
        v = tf.Variable(0, 'v', dtype=tf.float32)
        b = tf.placeholder(tf.float32, shape=())
        z = tf.assign(v, b)
    return z, b

I can use feed_dict to pass a value to b, only if I set b as a return value. Otherwise, there is no way to access b. If we want to access many ops in the function scope, we should set many return values. This is very ugly.

I want to know what happens under the hood when I run functions using tensorflow and how to get access of the ops in the function scope.

Thank you!

Upvotes: 1

Views: 95

Answers (2)

Kaihong Zhang
Kaihong Zhang

Reputation: 419

3 things happen when you use op function:

  • create and add a compute node to default graph
  • set your input as the node input tensor
  • set node output tensor as return value

for example, a = tf.add(b, c, name='add'),

  • add a node with op Add to default graph, with name 'add'
  • set b and c as node input tensor
  • set node output, with name 'add:0', to a

So you can access nodes via sess.graph, there are many functions to access nodes, say, get_operation_by_name.

Also, you can operate the graph via sess.graph_def, which is serialized graph with protobuf, you can find the protobuf definition in the tensorflow source code, tensorflow/core/framework, some .proto files there.

Upvotes: 0

lxuechen
lxuechen

Reputation: 1199

Obviously, it's true that to access an op (or tensor) we need some reference to it. IMHO, one standard workaround is to build your graph in a class and make certain tensors attributes of the class and access them through the object.

Alternatively, if you're more inclined to the functional approach, a better way than returning all relevant ops and tensors separately would be to return a dict (or namedtuple).

Additionally, there are also specialized functions that return ops by name: e.g. get_operation_by_name.

As an aside to this question, you might also want to try out eager execution, which is imperative.

Upvotes: 1

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