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Diffstat (limited to 'text_recognizer/networks/util.py')
| -rw-r--r-- | text_recognizer/networks/util.py | 39 |
1 files changed, 0 insertions, 39 deletions
diff --git a/text_recognizer/networks/util.py b/text_recognizer/networks/util.py index 9c6b151..05b10a8 100644 --- a/text_recognizer/networks/util.py +++ b/text_recognizer/networks/util.py @@ -22,42 +22,3 @@ def activation_function(activation: str) -> Type[nn.Module]: ] ) return activation_fns[activation.lower()] - - -# def configure_backbone(backbone: Union[OmegaConf, NamedTuple]) -> Type[nn.Module]: -# """Loads a backbone network.""" -# network_module = importlib.import_module("text_recognizer.networks") -# backbone_class = getattr(network_module, backbone.type) -# -# if "pretrained" in backbone.args: -# logger.info("Loading pretrained backbone.") -# checkpoint_file = Path(__file__).resolve().parents[2] / backbone.args.pop( -# "pretrained" -# ) -# -# # Loading state directory. -# state_dict = torch.load(checkpoint_file) -# network_args = state_dict["network_args"] -# weights = state_dict["model_state"] -# -# freeze = False -# if "freeze" in backbone.args and backbone.args["freeze"] is True: -# backbone.args.pop("freeze") -# freeze = True -# -# # Initializes the network with trained weights. -# backbone_ = backbone_(**backbone.args) -# backbone_.load_state_dict(weights) -# if freeze: -# for params in backbone_.parameters(): -# params.requires_grad = False -# else: -# backbone_ = getattr(network_module, backbone.type) -# backbone_ = backbone_(**backbone.args) -# -# if "remove_layers" in backbone_args and backbone_args["remove_layers"] is not None: -# backbone = nn.Sequential( -# *list(backbone.children())[:][: -backbone_args["remove_layers"]] -# ) -# -# return backbone |