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Supporting control flow in TensorFlow Lite #28485

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miaout17 opened this issue May 7, 2019 · 4 comments

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@miaout17
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commented May 7, 2019

This is a tracking ticket for supporting generalized control flow in TensorFlow Lite. See also the RFC.

At this moment, if you see missing ops like "Switch", "Merge", "Enter", "Exit", "NextIteration" when converting a TensorFlow model to TensorFlow Lite, it means the graph contains control flows, and there's no way to convert it.

We're working hard to enable this feature. Updates will be posted here.

@Dayananda-V

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commented May 28, 2019

@miaout17

When we can expect control flow in TensorFlow Lite?

@nikoliazekter

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commented Jul 10, 2019

Is this really hard to implement? Because to me it looks like a very critical issue and the lack of attention seems quite weird. How else am I supposed to deploy my model to a mobile device? Are there any workarounds?

EDIT: I see that while op is registered here , can I somehow use it?

@nikoliazekter

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commented Jul 22, 2019

@miaout17 there were several commits recently like this one eedf79e but no updates were posted in this thread. Can you update us on when all these features will be available and in which tensorflow version (only 2.0 I assume)?

@jackyLens

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commented Oct 12, 2019

I met the same problem. It shows that "switch and merge" operations which in batchnormalization(bn) are not supported. However, I change the is_training from tf.bool to tf.Variable. This process are OK and the tflite model are produced sucessfully.
I do not know the reason, but it runs well in my programe.

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