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Jul 22nd, 2019
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  1. predictions = {
  2. "classes": tf.argmax(input=logits, axis=1),
  3. "probabilities": tf.nn.softmax(logits, name="softmax_tensor")
  4. }
  5. if mode == tf.estimator.ModeKeys.PREDICT:
  6. return tf.estimator.EstimatorSpec(mode=mode, predictions=predictions)
  7.  
  8. predictions = {
  9. "classes": tf.argmax(input=logits, axis=1),
  10. "probabilities": tf.nn.softmax(logits, name="softmax_tensor")
  11. }
  12. if mode == tf.estimator.ModeKeys.PREDICT:
  13. return tf.estimator.EstimatorSpec(mode=mode, predictions=predictions)
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