#TEST = './train_ant.ark' PREDICTION_ROOT ='./result/prediction/' PREDICTION = MODEL + '.csv' ######################## # load DNN open file # ######################## ACT_FUNC="leakyReLU" COST_FUNC ="CE" layers,Ws,bs = pickle.load(open(MODEL_ROOT+MODEL,'rb')) nn = DNN(layers,Ws,bs,act=ACT_FUNC,cost=COST_FUNC) # nn.rescale_params(0.9) # MODEL = "DATA_fbank_LABEL_phoneme48_HIDDEN_LAYERS_1024-1024-1024-1024_L_RATE_0.001_MOMENTUM_0.9_DROPOUT_0_EPOCH_100" TEST_DATA,VAL_DATA = readfile( TEST_ROOT+TEST,1 ) PRED_FILE = open( PREDICTION_ROOT + PREDICTION ,'wb') # Get Dictionaries Phone48 = load_list39to48() PhoneMap48to39 = load_dict_48to39() # For CSV HEADER = ["Id","Prediction"] ######################## # Predict # ########################
#TEST = './train_ant.ark' PREDICTION_ROOT = './result/prediction/' PREDICTION = MODEL + '.csv' ######################## # load DNN open file # ######################## ACT_FUNC = "leakyReLU" COST_FUNC = "CE" layers, Ws, bs = pickle.load(open(MODEL_ROOT + MODEL, 'rb')) nn = DNN(layers, Ws, bs, act=ACT_FUNC, cost=COST_FUNC) # nn.rescale_params(0.9) # MODEL = "DATA_fbank_LABEL_phoneme48_HIDDEN_LAYERS_1024-1024-1024-1024_L_RATE_0.001_MOMENTUM_0.9_DROPOUT_0_EPOCH_100" TEST_DATA, VAL_DATA = readfile(TEST_ROOT + TEST, 1) PRED_FILE = open(PREDICTION_ROOT + PREDICTION, 'wb') # Get Dictionaries Phone48 = load_list39to48() PhoneMap48to39 = load_dict_48to39() # For CSV HEADER = ["Id", "Prediction"] ######################## # Predict # ########################
