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What would be a good way to ensure TensorFlow results persist across different runs? I can't find much information on e.g. seeding random weight initialization, so my results tend to differ with every run.
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The API method tf.set_random_seed() can be used to set a random seed that will be used in all TensorFlow random operations (including the usual random weight initializers and tf.RandomShuffleQueue).
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