Reset seed at the beginning of each epoch. (#221)

* Reset seed at the beginning of each epoch.

* Use a different seed for each epoch.

egs/aishell/ASR/conformer_ctc/train.py

@@ -121,6 +121,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -555,7 +562,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -618,6 +625,7 @@ def run(rank, world_size, args):
     valid_dl = aishell.valid_dataloaders(aishell.valid_cuts())
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/aishell/ASR/conformer_mmi/train.py

@@ -124,6 +124,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -546,7 +553,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -613,6 +620,7 @@ def run(rank, world_size, args):
     valid_dl = aishell.valid_dataloaders(aishell.valid_cuts())
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/aishell/ASR/tdnn_lstm_ctc/train.py

@@ -92,6 +92,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -507,7 +514,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -557,6 +564,7 @@ def run(rank, world_size, args):
     valid_dl = aishell.valid_dataloaders(aishell.valid_cuts())
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         if epoch > params.start_epoch:

egs/aishell/ASR/transducer_stateless/train.py

@@ -129,6 +129,13 @@ def get_parser():
         "2 means tri-gram",
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -534,7 +541,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -611,6 +618,7 @@ def run(rank, world_size, args):
     valid_dl = aishell.valid_dataloaders(aishell.valid_cuts())
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/librispeech/ASR/conformer_ctc/train.py

@@ -140,6 +140,13 @@ def get_parser():
         help="The lr_factor for Noam optimizer",
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -580,7 +587,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -684,6 +691,7 @@ def run(rank, world_size, args):
     )
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/librispeech/ASR/conformer_mmi/train.py

@@ -109,6 +109,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -673,7 +680,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -761,6 +768,7 @@ def run(rank, world_size, args):
     valid_dl = librispeech.valid_dataloaders()
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
         if (
             params.batch_idx_train >= params.use_ali_until

egs/librispeech/ASR/pruned_transducer_stateless/train.py

@@ -179,6 +179,13 @@ def get_parser():
         "with this parameter before adding to the final loss.",
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -642,7 +649,7 @@ def run(rank, world_size, args):
         params.valid_interval = 800
         params.warm_step = 30000
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -731,6 +738,7 @@ def run(rank, world_size, args):
     )
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/librispeech/ASR/streaming_conformer_ctc/train.py

@@ -138,6 +138,13 @@ def get_parser():
         help="Proportion of samples trained with short right context",
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -575,7 +582,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -645,6 +652,7 @@ def run(rank, world_size, args):
     )
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/librispeech/ASR/tdnn_lstm_ctc/train.py

@@ -95,6 +95,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -486,7 +493,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -544,6 +551,7 @@ def run(rank, world_size, args):
     valid_dl = librispeech.valid_dataloaders(valid_cuts)
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         if epoch > params.start_epoch:

egs/librispeech/ASR/transducer/train.py

@@ -130,6 +130,13 @@ def get_parser():
         help="The lr_factor for Noam optimizer",
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -544,7 +551,7 @@ def run(rank, world_size, args):
         params.valid_interval = 800
         params.warm_step = 8000
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -633,6 +640,7 @@ def run(rank, world_size, args):
     )
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/librispeech/ASR/transducer_lstm/train.py

@@ -131,6 +131,13 @@ def get_parser():
         help="The lr_factor for Noam optimizer",
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -548,7 +555,7 @@ def run(rank, world_size, args):
         params.valid_interval = 800
         params.warm_step = 8000
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -639,6 +646,7 @@ def run(rank, world_size, args):
     )
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/librispeech/ASR/transducer_stateless/train.py

@@ -149,6 +149,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -562,7 +569,7 @@ def run(rank, world_size, args):
         params.valid_interval = 800
         params.warm_step = 8000
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -651,6 +658,7 @@ def run(rank, world_size, args):
     )
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         cur_lr = optimizer._rate

egs/timit/ASR/tdnn_ligru_ctc/train.py

@@ -95,6 +95,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -486,7 +493,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -536,6 +543,7 @@ def run(rank, world_size, args):
     valid_dl = timit.valid_dataloaders()
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         if epoch > params.start_epoch:

egs/timit/ASR/tdnn_lstm_ctc/train.py

@@ -95,6 +95,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -486,7 +493,7 @@ def run(rank, world_size, args):
     params = get_params()
     params.update(vars(args))
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -536,6 +543,7 @@ def run(rank, world_size, args):
     valid_dl = timit.valid_dataloaders()
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         if epoch > params.start_epoch:

egs/yesno/ASR/tdnn/train.py

@@ -71,6 +71,13 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -468,7 +475,7 @@ def run(rank, world_size, args):
     params.update(vars(args))
     params["env_info"] = get_env_info()
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -520,6 +527,7 @@ def run(rank, world_size, args):
     valid_dl = yes_no.test_dataloaders()
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         if tb_writer is not None:

egs/yesno/ASR/transducer/train.py

@@ -114,6 +114,13 @@ def get_parser():
         help="Directory to save results",
     )
 
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="The seed for random generators intended for reproducibility",
+    )
+
     return parser
 
 
@@ -487,7 +494,7 @@ def run(rank, world_size, args):
     params.update(vars(args))
     params["env_info"] = get_env_info()
 
-    fix_random_seed(42)
+    fix_random_seed(params.seed)
     if world_size > 1:
         setup_dist(rank, world_size, params.master_port)
 
@@ -532,6 +539,7 @@ def run(rank, world_size, args):
     valid_dl = yes_no.test_dataloaders()
 
     for epoch in range(params.start_epoch, params.num_epochs):
+        fix_random_seed(params.seed + epoch)
         train_dl.sampler.set_epoch(epoch)
 
         if tb_writer is not None: