babysor/MockingBird · error · ValueError
Invalid options: mode={}, arch={}
Error message
Invalid options: mode={}, arch={} What it means
Identical logic to the ppg2mel copy: get_subsample in models/ppg_extractor/nets_utils.py rejects unsupported (mode, arch) pairs, e.g. anything besides asr/{vggblstmp,vggblstmp2,vggbgru,vgggru,bgru,blstmp,blstm} and mdense/bgru.
Source
Thrown at models/ppg_extractor/nets_utils.py:439
elif mode == 'asr' and arch == 'rnn_mulenc':
subsample_list = []
for idx in range(train_args.num_encs):
subsample = np.ones(train_args.elayers[idx] + 1, dtype=np.int)
if train_args.etype[idx].endswith("p") and not train_args.etype[idx].startswith("vgg"):
ss = train_args.subsample[idx].split("_")
for j in range(min(train_args.elayers[idx] + 1, len(ss))):
subsample[j] = int(ss[j])
else:
logging.warning(
'Encoder %d: Subsampling is not performed for vgg*. '
'It is performed in max pooling layers at CNN.', idx + 1)
logging.info('subsample: ' + ' '.join([str(x) for x in subsample]))
subsample_list.append(subsample)
return subsample_list
else:
raise ValueError('Invalid options: mode={}, arch={}'.format(mode, arch))
def rename_state_dict(old_prefix: str, new_prefix: str, state_dict: Dict[str, torch.Tensor]):
"""Replace keys of old prefix with new prefix in state dict."""
# need this list not to break the dict iterator
old_keys = [k for k in state_dict if k.startswith(old_prefix)]
if len(old_keys) > 0:
logging.warning(f'Rename: {old_prefix} -> {new_prefix}')
for k in old_keys:
v = state_dict.pop(k)
new_k = k.replace(old_prefix, new_prefix)
state_dict[new_k] = v
def get_activation(act):
"""Return activation function."""
# Lazy load to avoid unused import
from .encoder.swish import Swish
View on GitHub (pinned to 28dc5e14f1)
Solutions
- Match (mode, arch) to a supported combination, e.g. ('asr','vggblstmp')
- Patch get_subsample to add a branch for your arch if genuinely needed
Example fix
# before
get_subsample('asr', 'transformer', 24)
# after
get_subsample('asr', 'vggblstmp', 24) Defensive patterns
Strategy: validation
Validate before calling
VALID = {('asr', a) for a in ['vggblstmp','vggblstmp2','vggbgru','vgggru','bgru','blstmp','blstm']} | {('mdense','bgru')}
assert (mode, arch) in VALID Prevention
- Validate config before training launch
- Add regression tests covering every supported (mode, arch)
When it happens
Trigger: Calling get_subsample with mode='asr' and an arch like 'conformer'/'transformer', or mode='mdense' with arch != 'bgru'.
Common situations: Adapting ESPnet2/conformer configs into this codebase; arch typo; wrong mode string.
Understand the failure class
Background: "Invalid value" and "allowed values are" config errors: what your library rejected and how to fix it — this error's family across 41 libraries.
Related errors
- Invalid options: mode={}, arch={}
- Number of encoders needs to be more than one. {}
- Both increase only and decrease only are set
- unknown pos_enc_layer:
- unknown input_layer:
AI-assisted analysis of babysor/MockingBird@28dc5e14f1 (2026-08-27).
Data as JSON: /api/errors/36e8bfe198364249.
Report an issue: GitHub.