from builtins import range
import sys, os
sys.path.insert(1, os.path.join("..",".."))
import h2o
from tests import pyunit_utils
from h2o.estimators.deeplearning import H2ODeepLearningEstimator

def deeplearning_basic():



  iris_hex = h2o.import_file(path=pyunit_utils.locate("smalldata/iris/iris.csv"))
  hh = H2ODeepLearningEstimator(loss="CrossEntropy")
  hh.train(x=list(range(3)), y=4, training_frame=iris_hex)
  hh.show()

if __name__ == "__main__":
  pyunit_utils.standalone_test(deeplearning_basic)
else:
  deeplearning_basic()

from builtins import range
import sys, os
sys.path.insert(1, "../../../")
import h2o
from tests import pyunit_utils
from h2o.estimators.deeplearning import H2ODeepLearningEstimator

def deeplearning_basic():



  iris_hex = h2o.import_file(path=pyunit_utils.locate("smalldata/iris/iris.csv"))
  hh = H2ODeepLearningEstimator(loss="CrossEntropy")
  hh.train(x=list(range(3)), y=4, training_frame=iris_hex)
  hh.show()

if __name__ == "__main__":
  pyunit_utils.standalone_test(deeplearning_basic)
else:
  deeplearning_basic()

Make sure pyuni_iris_basic_deeplearning can also run locally
Make sure pyuni_iris_basic_deeplearning can also run locally

  from builtins import range
  import sys, os
- sys.path.insert(1, os.path.join("..",".."))
+ sys.path.insert(1, "../../../")
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.deeplearning import H2ODeepLearningEstimator
  
  def deeplearning_basic():
  
  
  
    iris_hex = h2o.import_file(path=pyunit_utils.locate("smalldata/iris/iris.csv"))
    hh = H2ODeepLearningEstimator(loss="CrossEntropy")
    hh.train(x=list(range(3)), y=4, training_frame=iris_hex)
    hh.show()
  
  if __name__ == "__main__":
    pyunit_utils.standalone_test(deeplearning_basic)
  else:
    deeplearning_basic()
  
Make sure pyuni_iris_basic_deeplearning can also run locally
## Code Before:
from builtins import range
import sys, os
sys.path.insert(1, os.path.join("..",".."))
import h2o
from tests import pyunit_utils
from h2o.estimators.deeplearning import H2ODeepLearningEstimator

def deeplearning_basic():



  iris_hex = h2o.import_file(path=pyunit_utils.locate("smalldata/iris/iris.csv"))
  hh = H2ODeepLearningEstimator(loss="CrossEntropy")
  hh.train(x=list(range(3)), y=4, training_frame=iris_hex)
  hh.show()

if __name__ == "__main__":
  pyunit_utils.standalone_test(deeplearning_basic)
else:
  deeplearning_basic()

## Instruction:
Make sure pyuni_iris_basic_deeplearning can also run locally
## Code After:
from builtins import range
import sys, os
sys.path.insert(1, "../../../")
import h2o
from tests import pyunit_utils
from h2o.estimators.deeplearning import H2ODeepLearningEstimator

def deeplearning_basic():



  iris_hex = h2o.import_file(path=pyunit_utils.locate("smalldata/iris/iris.csv"))
  hh = H2ODeepLearningEstimator(loss="CrossEntropy")
  hh.train(x=list(range(3)), y=4, training_frame=iris_hex)
  hh.show()

if __name__ == "__main__":
  pyunit_utils.standalone_test(deeplearning_basic)
else:
  deeplearning_basic()
