Method load_model

t-few/src/models/EncoderDecoder.py:332–338

(self)

        self.load_model()

    def load_model(self):
        if self.config.load_weight != "":
            trainable_states = torch.load(self.config.load_weight, map_location=torch.device("cpu"))
            load_result = self.model.load_state_dict(trainable_states, strict=False)
            assert (
                len(load_result.unexpected_keys) == 0
            ), f"Load model failed, unexpected keys {load_result.unexpected_keys.__str__()}"

    def save_model(self, finish=False):
        if self.config.save_model and (finish or self._last_global_step_saved != self.global_step):