ADD

# Add test_net.test_net1:
#     Implement net1 test
#     Load trained net1 model, compute loss and accuracy

test_net/test_net1.py

@@ -0,0 +1,89 @@
+import argparse
+import os
+import torch
+import time
+import datetime
+
+import hparams
+
+from model.Net1 import Net1, get_net1_loss, get_net1_acc
+from dataloader.Net1DataLoader import get_net1_data_loader
+
+
+def test(arg):
+    device = torch.device(arg.device)
+
+    # Build model
+    net1 = Net1(in_dims=hparams.net1_in_dims,
+                hidden_units=hparams.net1_hidden_units,
+                dropout_rate=hparams.net1_dropout_rate,
+                num_conv1d_banks=hparams.net1_num_conv1d_banks,
+                num_highway_blocks=hparams.net1_num_highway_blocks)
+
+    # Move net1 model into the computing device
+    net1.to(device)
+
+    # Set data loader
+    data_loader = get_net1_data_loader(data_path=hparams.net1_test_dataset,
+                                       batch_size=hparams.net1_batch_size,
+                                       num_workers=hparams.net1_num_workers)
+
+    # Resume net1 model
+    resume_model_path = os.path.join(hparams.net1_train_checkpoint_path, arg.resume_model)
+    resume_log = "Resume net1 model from : " + resume_model_path
+    print(resume_log)
+
+    checkpoint = torch.load(resume_model_path)
+    print("Load model successfully!")
+
+    net1.load_state_dict(checkpoint["net"])
+
+    # Start testing
+    print("Start testing ... ")
+    start_time = time.time()
+
+    data_iter = iter(data_loader)
+
+    # Get input data
+    mfccs, phones = next(data_iter)
+
+    # Moving input data into the computing device
+    mfccs = mfccs.to(device)
+    phones = phones.long().to(device)
+
+    # Test net1 model
+    net1 = net1.eval()
+    ppgs, preds, logits = net1(mfccs)
+
+    # Compute the loss
+    loss = get_net1_loss(logits, phones, mfccs)
+
+    # Compute the accuracy
+    acc = get_net1_acc(preds, phones, mfccs)
+
+    # Print loss and acc
+    et = time.time() - start_time
+    et = str(datetime.timedelta(seconds=et))[:-7]
+    log = "Elapsed [{}], Loss : [{:.6f}], Accuracy : [{:.6f}]".format(et, loss, acc)
+    print(log)
+
+
+def get_arguments():
+    parser = argparse.ArgumentParser()
+
+    # Set test net1 config
+    parser.add_argument('-device', default=hparams.net1_train_device, type=str,
+                        help='Net1 training device.')
+    parser.add_argument('resume_model', type=str,
+                        help='Net1 resume model checkpoint.')
+
+    arguments = parser.parse_args()
+    return arguments
+
+
+if __name__ == '__main__':
+    args = get_arguments()
+
+    print("Test Net1 parameters : \n " + str(args))
+
+    test(args)