def main(opts):
RECEIVED_PARAMS = nni.get_next_parameter()
LOG.debug(RECEIVED_PARAMS)
if 'onlyIncoming' == opts.mode:
PARAMS = cnn.generate_default_onlyIncoming_params(opts.dataType)
elif 'both' == opts.mode:
PARAMS = cnn.generate_default_whole_params(opts.dataType)
PARAMS.update(RECEIVED_PARAMS)
try:
X_train_raw, y_train, X_test_raw, y_test, labelMap = prepareData.loadTrainAndTestData(
opts.input, PARAMS['data_dim'], opts.dataType, mode=opts.mode)
NUM_CLASS = len(set(y_test))
X_train = X_train_raw.reshape(X_train_raw.shape[0],
X_train_raw.shape[1], 1)
X_test = X_test_raw.reshape(X_test_raw.shape[0], X_test_raw.shape[1],
1)
y_train = np_utils.to_categorical(y_train, NUM_CLASS)
y_test = np_utils.to_categorical(y_test, NUM_CLASS)
cnn_model = CNN(opts, PARAMS)
modelPath = cnn_model.train(PARAMS, X_train, y_train, NUM_CLASS)
cnn_model.test(X_test, y_test, NUM_CLASS, modelPath)
except Exception as e:
LOG.exception(e)
raise
def chooseModel(opts):
print('selecting model to test...')
if 'cnn' == opts.model:
if 'onlyIncoming' == opts.mode:
params = cnn.generate_default_onlyIncoming_params(opts.dataType)
else:
params = cnn.generate_default_whole_params(opts.dataType)
modelObj = cnn.CNN(opts, params)
elif 'cudnnLstm' == opts.model:
if 'onlyIncoming' == opts.mode:
params = cudnnLstm.generate_default_onlyIncoming_params(opts.dataType)
else:
params = cudnnLstm.generate_default_whole_params(opts.dataType)
modelObj = cudnnLstm.LSTM(opts, params)
elif 'sae' == opts.model:
if 'onlyIncoming' == opts.mode:
params = sae.generate_default_onlyIncoming_params(opts.dataType)
else:
params = sae.generate_default_whole_params(opts.dataType)
modelObj = sae.SAE(opts, params)
return params, modelObj
def chooseModel(opts, ifTest=True, NUM_CLASS=100, modelPath=''):
if 'cnn' == opts.model:
if 'onlyIncoming' == opts.mode:
params = cnn.generate_default_onlyIncoming_params(opts.dataType)
else:
params = cnn.generate_default_whole_params(opts.dataType)
modelObj = cnn.CNN(opts, params)
elif 'cudnnLstm' == opts.model:
if 'onlyIncoming' == opts.mode:
params = cudnnLstm.generate_default_onlyIncoming_params(opts.dataType)
else:
params = cudnnLstm.generate_default_whole_params(opts.dataType)
modelObj = cudnnLstm.LSTM(opts, params)
elif 'sae' == opts.model:
if 'onlyIncoming' == opts.mode:
params = sae.generate_default_onlyIncoming_params(opts.dataType)
else:
params = sae.generate_default_whole_params(opts.dataType)
modelObj = sae.SAE(opts, params)
if ifTest:
modelObj = modelObj.create_model(NUM_CLASS)
modelObj.load_weights(modelPath)
return modelObj, params