def initialize_parameters(default_model='uno_default_model.txt'):
# Build benchmark object
unoBmk = benchmark.BenchmarkUno(benchmark.file_path, default_model, 'keras',
prog='uno_baseline', desc='Build neural network based models to predict tumor response to single and paired drugs.')
# Initialize parameters
gParameters = finalize_parameters(unoBmk)
# benchmark.logger.info('Params: {}'.format(gParameters))
return gParameters
def initialize_parameters():
# Build benchmark object
#mymodel_common = candle.Benchmark(file_path,os.getenv("DEFAULT_PARAMS_FILE"),'keras',prog='myprog',desc='My model')
unoBmk = benchmark.BenchmarkUno(
benchmark.file_path,
os.getenv("DEFAULT_PARAMS_FILE"),
'keras',
prog='uno_baseline',
desc=
'Build neural network based models to predict tumor response to single and paired drugs.'
)
# Initialize parameters
hyperparams = candle.initialize_parameters(unoBmk)
#benchmark.logger.info('Params: {}'.format(hyperparams))
return hyperparams