Example #1
0
import test_cluster_sanity
test_cluster_sanity.test(a_node, pp, algos)

# Clean up old objects from the DKV, in case the cluster has been doing other things:
if h2o_test_utils.isVerbose(): print('Cleaning up old stuff. . .')
h2o_test_utils.cleanup(a_node)

import test_and_import_frames
datasets = test_and_import_frames.load_and_test(a_node, pp)

import test_models
test_models.build_and_test(a_node, pp, datasets, algos,
                           algo_additional_default_params)

# Metadata used to get corrupted, so test again
test_metadata.test(a_node, pp)

import test_predict_and_model_metrics
test_predict_and_model_metrics.test(a_node, pp)

import test_final_sanity
test_final_sanity.test(a_node, pp)

# TODO: use built_models
if clean_up_after:
    h2o_test_utils.cleanup(models=[
        dl_airlines_model_name, 'deeplearning_prostate_binomial',
        'kmeans_prostate'
    ],
                           frames=['prostate_binomial', 'airlines_binomial'])
Example #2
0
import test_cluster_sanity
test_cluster_sanity.test(a_node, pp, algos)

# Clean up old objects from the DKV, in case the cluster has been doing other things:
if h2o_test_utils.isVerbose(): print('Cleaning up old stuff. . .')
h2o_test_utils.cleanup(a_node)

import test_and_import_frames
datasets = test_and_import_frames.load_and_test(a_node, pp)

import test_models
test_models.build_and_test(a_node, pp, datasets, algos, algo_additional_default_params)

# Metadata used to get corrupted, so test again
test_metadata.test(a_node, pp)  

import test_predict_and_model_metrics
test_predict_and_model_metrics.test(a_node, pp)

import test_final_sanity
test_final_sanity.test(a_node, pp)



# TODO: use built_models
if clean_up_after:
    h2o_test_utils.cleanup(models=[dl_airlines_model_name, 'deeplearning_prostate_binomial', 'kmeans_prostate'], frames=['prostate_binomial', 'airlines_binomial'])