|
|
@@ -464,6 +464,12 @@ class AbsTask(ABC):
|
|
|
default=sys.maxsize,
|
|
|
help="The maximum number update step to train",
|
|
|
)
|
|
|
+ parser.add_argument(
|
|
|
+ "--batch_interval",
|
|
|
+ type=int,
|
|
|
+ default=10000,
|
|
|
+ help="The batch interval for saving model.",
|
|
|
+ )
|
|
|
group.add_argument(
|
|
|
"--patience",
|
|
|
type=int_or_none,
|
|
|
@@ -1576,13 +1582,18 @@ class AbsTask(ABC):
|
|
|
) -> AbsIterFactory:
|
|
|
assert check_argument_types()
|
|
|
|
|
|
+ if args.frontend_conf is not None and "fs" in args.frontend_conf:
|
|
|
+ dest_sample_rate = args.frontend_conf["fs"]
|
|
|
+ else:
|
|
|
+ dest_sample_rate = 16000
|
|
|
+
|
|
|
dataset = ESPnetDataset(
|
|
|
iter_options.data_path_and_name_and_type,
|
|
|
float_dtype=args.train_dtype,
|
|
|
preprocess=iter_options.preprocess_fn,
|
|
|
max_cache_size=iter_options.max_cache_size,
|
|
|
max_cache_fd=iter_options.max_cache_fd,
|
|
|
- dest_sample_rate=args.frontend_conf["fs"],
|
|
|
+ dest_sample_rate=dest_sample_rate,
|
|
|
)
|
|
|
cls.check_task_requirements(
|
|
|
dataset, args.allow_variable_data_keys, train=iter_options.train
|