How to control when to compute evaluation vs training using the Estimator API of tensorflow?
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可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效,请关闭广告屏蔽插件后再试): 问题: As stated in this question : The tensorflow documentation does not provide any example of how to perform a periodic evaluation of the model on an evaluation set The accepted answer suggested the use of Experiment (which is deprecated according to this README ). All I found on online points towards using the train_and_evaluate method. However, I still do not see how to switch between the two processes (train and evaluate). I have tried the following: estimator = tf.estimator.Estimator( model_fn=model_fn, params=hparams, model_dir=model_dir,