doka-train.py

@@ -16,6 +16,7 @@ from Loss_final1 import loss
 from model_rnn import Dual_RNN_model
 from mindspore.nn.dynamic_lr import piecewise_constant_lr
 from train_wrapper import TrainingWrapper
+import time
 
 parser = argparse.ArgumentParser(
         description='Parameters for training Dual-Path-RNN')
@@ -44,9 +45,9 @@ parser.add_argument('--sample_rate', default=8000, type=int,
                     help='Sample rate')
 parser.add_argument('--segment', default=4, type=float,  # 取音频的长度，2s。#数据集语音长度要相同
                     help='Segment length (seconds)')
-parser.add_argument('--data_batch_size', default=3, type=int,  # 需要抛弃的音频长度
+parser.add_argument('--data_batch_size', default=2, type=int,  # 需要抛弃的音频长度
                     help='Batch size')
-parser.add_argument('--batch_size', type=int, default=1,
+parser.add_argument('--batch_size', type=int, default=2,
                     help='Sample rate of audio file')
 
 # Network architecture
@@ -64,7 +65,7 @@ parser.add_argument('--norm', default='gln', type=str,
                     help='gln = "Global Norm", cln = "Cumulative Norm", ln = "Layer Norm"')
 parser.add_argument('--dropout', default=0.0, type=float,
                     help='dropout')
-parser.add_argument('--num_layers', default=4, type=int,
+parser.add_argument('--num_layers', default=6, type=int,
                     help='Number of Dual-Path-Block')
 parser.add_argument('--K', default=250, type=int,
                     help='The length of chunk')
@@ -76,7 +77,7 @@ parser.add_argument('--lr', default=1e-3, type=float,
                     help='Init learning rate')
 parser.add_argument('--lr1', default=5e-4, type=float,
                     help='Init learning rate')
-parser.add_argument('--lr2', default=2.5e-4, type=float,
+parser.add_argument('--lr2', default=2e-4, type=float,
                     help='Init learning rate')
 parser.add_argument('--l2', default=1e-5, type=float,
                     help='weight decay (L2 penalty)')
@@ -84,7 +85,7 @@ parser.add_argument('--l2', default=1e-5, type=float,
 # save and load model
 parser.add_argument('--save_folder', default=r"/home/work/user-job-dir/model/",
                     help='Location to save epoch models')
-parser.add_argument('--nEpochs', type=int, default=30, help='number of epochs to train for')
+parser.add_argument('--nEpochs', type=int, default=60, help='number of epochs to train for')
 parser.add_argument('--device_num', type=int, default=2,
                     help='Sample rate of audio file')
 parser.add_argument('--device_id', type=int, default=0,
@@ -117,7 +118,8 @@ def preprocess(args):
     print("preprocess done")
 
 def main(args):
-    context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, save_graphs=True)
+    # context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
 
     if args.run_distribute:
         print("distribute")
@@ -195,7 +197,7 @@ def main(args):
     loss_cb = LossMonitor(1)
     cb = [time_cb, loss_cb]
     
-    config_ck = CheckpointConfig(save_checkpoint_steps=num_steps, keep_checkpoint_max=4)
+    config_ck = CheckpointConfig(save_checkpoint_steps=num_steps, keep_checkpoint_max=5)
     ckpt_cb = ModelCheckpoint(prefix='commit',
                               directory=save_ckpt,
                               config=config_ck)
@@ -203,7 +205,7 @@ def main(args):
 
     #开始训练
     print("============== Starting Training ==============")
-    model.train(epoch=30, train_dataset=tr_loader, callbacks=cb, dataset_sink_mode=False)
+    model.train(epoch=60, train_dataset=tr_loader, callbacks=cb, dataset_sink_mode=False)
 
     try:
         mox.file.copy_parallel(save_folder, obs_train_url)