What should I do when H2O AutoML returns “H2OFrame is empty”?

Question

While training a job on a SageMaker instance using H2o AutoML a message "This H2OFrame is empty" has come up after running the code, what should I do to fix the problem?

/opt/ml/input/config/hyperparameters.json
All Parameters:
{'nfolds': '5', 'training': "{'classification': 'true', 'target': 'y'}", 'max_runtime_secs': '3600'}
/opt/ml/input/config/resourceconfig.json
All Resources:
{'current_host': 'algo-1', 'hosts': ['algo-1'], 'network_interface_name': 'eth0'}
Waiting until DNS resolves: 1
10.0.182.83
Starting up H2O-3
Creating Connection to H2O-3
Attempt 0: H2O-3 not running yet...
Connecting to H2O server at http://127.0.0.1:54321... successful.
-------------------------- ----------------------------------------

-------------------------- ----------------------------------------
Beginning Model Training
Parse progress: |█████████████████████████████████████████████████████████| 100%
Classification - If you want to do a regression instead, set "classification":"false" in "training" params, inhyperparamters.json
Converting specified columns to categorical values:
[]
AutoML progress: |████████████████████████████████████████████████████████| 100%
This H2OFrame is empty.
Exception during training: Argument `model` should be a ModelBase, got NoneType None
Traceback (most recent call last):
File "/opt/program/train", line 138, in _train_model
h2o.save_model(aml.leader, path=model_path)
File "/root/.local/lib/python3.7/site-packages/h2o/h2o.py", line 969, in save_model
assert_is_type(model, ModelBase)
File "/root/.local/lib/python3.7/site-packages/h2o/utils/typechecks.py", line 457, in assert_is_type
skip_frames=skip_frames)
h2o.exceptions.H2OTypeError: Argument `model` should be a ModelBase, got NoneType None
H2O session _sid_8aba closed.

I'm wondering if it's a problem because of the max_runtime_secs, my data has around 500 rows and 250000 columns.

can you post the code you used to run AutoML if you are seeing H2OFrame is empty it's probably because no models were built. If there are no issues within your code (for example make sure you have converted your target to categorical) then I'd recommend using max_models so that you ensure at least a few models are built. — Lauren
@Lauren I realized the issue was due to the max_runtime. When I trained the model with more time I didn't have the problem. — Marcel Mendes Reis

Lauren Lauren · Accepted Answer · 2019-09-19T15:16:28

thanks @Marcel Mendes Reis for following up on your solution in the comments. I will repost here for others to easily find:

I realized the issue was due to the max_runtime. When I trained the model with more time I didn't have the problem.

What should I do when H2O AutoML returns “H2OFrame is empty”?

2 Answers