Working on fixing decoder transformer

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