Comments (8)
Could it be that tf.estimator.EvalSpec
did not support None
steps in TF 1.8?
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@cweill
i changed it to 100 (the default number for tf.estimator.EvalSpec). it stayed almost the same, except print out evaluation progressbar.
before: (steps=None):
INFO:tensorflow:Starting evaluation at 2018-11-07-09:00:11
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from C:\Users\dell\AppData\Local\Temp\tmp6brw31q8\model.ckpt-5000
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
INFO:tensorflow:Finished evaluation at 2018-11-07-09:00:14
INFO:tensorflow:Saving dict for global step 5000: accuracy = 0.8413, average_loss = 0.46480888, global_step = 5000, loss = 0.4642294TypeError Traceback (most recent call last)
in ()
6 eval_spec=tf.estimator.EvalSpec(
7 input_fn=input_fn("test", training=False, batch_size=BATCH_SIZE),
----> 8 steps=None))TypeError: 'NoneType' object is not iterable
after: (steps=100):
INFO:tensorflow:Starting evaluation at 2018-11-08-01:13:41
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from C:\Users\dell\AppData\Local\Temp\tmp1mw6x8zx\model.ckpt-5000
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
> INFO:tensorflow:Evaluation [10/100]
INFO:tensorflow:Evaluation [20/100]
...
INFO:tensorflow:Evaluation [90/100]
INFO:tensorflow:Evaluation [100/100]
INFO:tensorflow:Finished evaluation at 2018-11-08-01:13:43
INFO:tensorflow:Saving dict for global step 5000: accuracy = 0.8421875, average_loss = 0.47057664, global_step = 5000, loss = 0.47057664TypeError Traceback (most recent call last)
in ()
6 eval_spec=tf.estimator.EvalSpec(
7 input_fn=input_fn("test", training=False, batch_size=BATCH_SIZE),
----> 8 steps=100))
TypeError: 'NoneType' object is not iterable
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@yuezhilanyi: Could you please copy the full log from start to end? It's not clear what is raising this TypeError
.
In the meantime you can use Colab to run the tutorials. For examples: https://colab.research.google.com/github/tensorflow/adanet/blob/master/adanet/examples/tutorials/adanet_objective.ipynb
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Here is the full log.
full_log.txt
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Tensorflow v1.10.0 improved local run behavior in tf.estimator.train_and_evaluate which does not reload checkpoints for evaluation, see release.md.
It maybe the reason that adanet doesn't work well on tf 1.8.0.
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Can you try upgrading to TF 1.9+? We recently bumped our minimum version to 1.9.
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Sorry I can't, for it is for production sometimes also.
But I tried on my own laptop with no gpu support and TRAIN_STEPS=1000:
- when using TF 1.8, the same issues occured;
- when using TF 1.9, it succeeded
I run the whole adanet_objective.ipynb sucessfully.
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Unfortunately, I won't be able to look into TF 1.8 support for a while. If you figure out the source of the issue, feel free to submit a PR.
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Related Issues (20)
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