tensorflow/models · error · TypeError
Subconfig_type should be subclass of ParamsDict, found {!r}
Error message
Subconfig_type should be subclass of ParamsDict, found {!r} What it means
Error "Subconfig_type should be subclass of ParamsDict, found {!r}" thrown in tensorflow/models.
Source
Thrown at official/modeling/hyperparams/base_config.py:140
Args:
v: Input sequence.
Returns:
True if the sequence is valid. Valid sequence includes the sequence
type in cls.SEQUENCE_TYPES and element type is in cls.IMMUTABLE_TYPES or
is dict or ParamsDict.
"""
if not isinstance(v, cls.SEQUENCE_TYPES):
return False
return (all(isinstance(e, cls.IMMUTABLE_TYPES) for e in v) or
all(isinstance(e, dict) for e in v) or
all(isinstance(e, params_dict.ParamsDict) for e in v))
@classmethod
def _import_config(cls, v, subconfig_type):
"""Returns v with dicts converted to Configs, recursively."""
if not issubclass(subconfig_type, params_dict.ParamsDict):
raise TypeError(
'Subconfig_type should be subclass of ParamsDict, found {!r}'.format(
subconfig_type))
if isinstance(v, cls.IMMUTABLE_TYPES):
return v
elif isinstance(v, cls.SEQUENCE_TYPES):
# Only support one layer of sequence.
if not cls._isvalidsequence(v):
raise TypeError(
'Invalid sequence: only supports single level {!r} of {!r} or '
'dict or ParamsDict found: {!r}'.format(cls.SEQUENCE_TYPES,
cls.IMMUTABLE_TYPES, v))
import_fn = functools.partial(
cls._import_config, subconfig_type=subconfig_type)
return type(v)(map(import_fn, v))
elif isinstance(v, params_dict.ParamsDict):
# Deepcopy here is a temporary solution for preserving type in nested
# Config object.
return copy.deepcopy(v)View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/modeling/hyperparams/base_config.py:140 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24).
Data as JSON: /api/errors/b411f9e641cf5bd9.
Report an issue: GitHub.