Error with Gradient boosted tree sample

76 views
Skip to first unread message

John Davis

unread,
Sep 15, 2019, 6:11:36 PM9/15/19
to TensorFlow Community Testing
Hello

I'm trying to run this example code from a medium article.  The article links the source from the tensorflow.org site and the code between the three versions appears to be the same.  However, when I run the code, it will kill my jupyter notiebook kernel during the training.

Here is the error message:

The kernel appears to have died. It will restart automatically.



Here is the blog with the sample code I'm running.





Here is the section from the blog:

"Then training a Boosted Trees model involves the same process as above:"
 



This is the line which interrupts the kernel:

# The model will stop training once the specified number of trees is built, not 
# based on the number of steps.
est.train(train_input_fn, max_steps=100)




The log for the above cell shows this:

INFO:tensorflow:Calling model_fn.
WARNING:tensorflow:From /home/davis/anaconda3/envs/py3tf2/lib/python3.7/site-packages/tensorflow_core/python/feature_column/feature_column.py:2158: NumericColumn._transform_feature (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version.
Instructions for updating:
The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead.
WARNING:tensorflow:From /home/davis/anaconda3/envs/py3tf2/lib/python3.7/site-packages/tensorflow_core/python/feature_column/feature_column.py:2158: IndicatorColumn._transform_feature (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version.
Instructions for updating:
The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead.
WARNING:tensorflow:From /home/davis/anaconda3/envs/py3tf2/lib/python3.7/site-packages/tensorflow_core/python/feature_column/feature_column_v2.py:4302: VocabularyListCategoricalColumn._get_sparse_tensors (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version.
Instructions for updating:
The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead.
WARNING:tensorflow:From /home/davis/anaconda3/envs/py3tf2/lib/python3.7/site-packages/tensorflow_core/python/feature_column/feature_column.py:2158: VocabularyListCategoricalColumn._transform_feature (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version.
Instructions for updating:
The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead.
WARNING:tensorflow:From /home/davis/anaconda3/envs/py3tf2/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/canned/boosted_trees.py:161: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.cast` instead.
INFO:tensorflow:Done calling model_fn.
INFO:tensorflow:Create CheckpointSaverHook.
WARNING:tensorflow:Issue encountered when serializing resources.
Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.
'_Resource' object has no attribute 'name'
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
WARNING:tensorflow:Issue encountered when serializing resources.
Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.
'_Resource' object has no attribute 'name'
INFO:tensorflow:Saving checkpoints for 0 into /tmp/tmpsjioltem/model.ckpt.
WARNING:tensorflow:Issue encountered when serializing resources.
Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.
'_Resource' object has no attribute 'name'
INFO:tensorflow:loss = 0.6931468, step = 0
WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.


Any idea where to discuss this problem?


Reply all
Reply to author
Forward
0 new messages