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Fix model_wrapper_cfg with pure python style config
#25
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -9,6 +9,7 @@ | |
| import warnings | ||
| from collections import OrderedDict | ||
| from functools import partial | ||
| from inspect import isclass | ||
| from typing import Callable, Dict, List, Optional, Sequence, Union | ||
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| import torch | ||
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@@ -902,8 +903,13 @@ def wrap_model( | |
| find_unused_parameters=find_unused_parameters) | ||
| else: | ||
| model_wrapper_cfg.setdefault('type', 'MMDistributedDataParallel') | ||
| model_wrapper_type = MODEL_WRAPPERS.get( | ||
| model_wrapper_cfg.get('type')) # type: ignore | ||
| model_wrapper_type = model_wrapper_cfg.get('type') | ||
| if isinstance(model_wrapper_type, str): | ||
| model_wrapper_type = MODEL_WRAPPERS.get(model_wrapper_type) | ||
| else: | ||
| assert isclass( | ||
| model_wrapper_type), 'type should be a string or a class' | ||
|
Comment on lines
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| default_args: dict = dict() | ||
| if issubclass( | ||
| model_wrapper_type, # type: ignore | ||
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The assertion should raise a
TypeErrorinstead of using anassertstatement for better error handling. Assert statements can be disabled with Python optimization flags (-O), making this validation unreliable in production. Consider: