old_contents: from models import mnist_mlp_benchmark
  import upload_benchmarks_bq as bq
  import argparse
  import tensorflow as tf
  #import theano
  #import cntk
  import keras
  
  parser = argparse.ArgumentParser()
  parser.add_argument('--keras_backend', default="tensorflow",
                      help='Keras backend being used to run benchmarks.')
  
  args = parser.parse_args()
  print(args.keras_backend)
  
  
  def get_keras_backend_version(backend_type):
    if str(backend_type) == "tensorflow":
      return tf.__version__
    if str(backend_type) == "theano":
      return theano.__version__
    if str(backend_type) == "cntk":
      return cntk.__version__
    return "undefined"
  
  model = mnist_mlp_benchmark.MnistMlpBenchmark()
  model.benchmarkMnistMlp()
  
  bq.upload_metrics_to_bq(model.get_testname(), model.get_totaltime(),
                       model.get_iters(), model.get_batch_size(),
                       args.keras_backend, get_keras_backend_version(args.keras_backend),
                       "1", "3.75", "GB",
                       "GCP", "n1-standard-1", model.get_sampletype(), keras.__version__)
  
new_contents: from models import mnist_mlp_benchmark
  import upload_benchmarks_bq as bq
  import argparse
  import tensorflow as tf
  import theano
  import cntk
  import keras
  
  parser = argparse.ArgumentParser()
  parser.add_argument('--keras_backend', default="tensorflow",
                      help='Keras backend being used to run benchmarks.')
  
  args = parser.parse_args()
  print(args.keras_backend)
  
  
  def get_keras_backend_version(backend_type):
    if str(backend_type) == "tensorflow":
      return tf.__version__
    if str(backend_type) == "theano":
      return theano.__version__
    if str(backend_type) == "cntk":
      return cntk.__version__
    return "undefined"
  
  model = mnist_mlp_benchmark.MnistMlpBenchmark()
  model.benchmarkMnistMlp()
  
  bq.upload_metrics_to_bq(model.get_testname(), model.get_totaltime(),
                       model.get_iters(), model.get_batch_size(),
                       args.keras_backend, get_keras_backend_version(args.keras_backend),
                       "1", "3.75", "GB",
                       "GCP", "n1-standard-1", keras.__version__,model.get_sampletype())
  
subject: remove import statement commented out