update

lib/python/graph_test.py

@@ -1,14 +1,11 @@
-import argparse 
 import tensorflow as tf
-import data_reader_bDNN_v2 as dr
-import data_reader_DNN_v2 as dnn_dr
-import data_reader_RNN as rnn_dr
-
 
 import utils as utils
 import numpy as np
 import os, sys
 
+os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
+os.environ["CUDA_VISIBLE_DEVICES"] = ""
 
 def bdnn_prediction(batch_size, logits, threshold=0.6, w=19, u=9):
     bdnn_batch_size = batch_size + 2*w
@@ -64,7 +61,7 @@ def do_test(fname_model, test_file_dir, norm_dir, data_len, is_default, model_ty
     final_label = []
 
     if model_type == 0:  # acam
-
+        import data_reader_bDNN_v2 as dr
         print(os.path.abspath('./configure/ACAM'))
         sys.path.insert(0, os.path.abspath('./configure/ACAM'))
 
@@ -120,7 +117,7 @@ def do_test(fname_model, test_file_dir, norm_dir, data_len, is_default, model_ty
         return final_softout[0:data_len, :], final_label[0:data_len, :]
 
     if model_type == 1:  # bdnn
-
+        import data_reader_bDNN_v2 as dr
         print(os.path.abspath('./configure/bDNN'))
         sys.path.insert(0, os.path.abspath('./configure/bDNN'))
 
@@ -170,7 +167,7 @@ def do_test(fname_model, test_file_dir, norm_dir, data_len, is_default, model_ty
         return final_softout[0:data_len, :], final_label[0:data_len, :]
 
     if model_type == 2:  # dnn
-
+        import data_reader_DNN_v2 as dnn_dr
         print(os.path.abspath('./configure/DNN'))
         sys.path.insert(0, os.path.abspath('./configure/DNN'))
 
@@ -216,6 +213,7 @@ def do_test(fname_model, test_file_dir, norm_dir, data_len, is_default, model_ty
         return final_softout[0:data_len, :], final_label[0:data_len, :]
 
     if model_type == 3:  # lstm
+        import data_reader_RNN as rnn_dr
 
         print(os.path.abspath('./configure/LSTM'))
         sys.path.insert(0, os.path.abspath('./configure/LSTM'))
@@ -309,4 +307,4 @@ def do_test(fname_model, test_file_dir, norm_dir, data_len, is_default, model_ty
     #     })
     #     # I taught a neural net to recognise when a sum of numbers is bigger than 45
     #     # it should return False in this case
-    #     print(y_out) # [[ False ]] Yay, it works!
+    #     print(y_out) # [[ False ]] Yay, it works!

main.m

@@ -9,7 +9,7 @@
 audio_dir = './data/clean/clean_speech.wav';
 % audio_dir = './data/example/SNR103F3MIC021001_ch01.wav';
 
-mode = 3;           % 0 : ACAM3, 1 : bDNN, 2 : DNN, 3 : LSTM
+mode = 2;           % 0 : ACAM3, 1 : bDNN, 2 : DNN, 3 : LSTM
 threshold = 0.4;    % threshold for hard decision
 output_type = 1;    % 0 : frame based prediction, 1: sample based prediction
 is_default = 1;     % 0 : use trained model, 1: use default model