53633acd7c861fd73e3954088a48d0ac8dc42895,niftynet/application/autoencoder_application.py,AutoencoderApplication,initialise_dataset_loader,#AutoencoderApplication#Any#Any#,38

Before Change

        elif self._infer_type == "linear_interpolation":
            self.reader = ImageReader(["feature"])

        if self.reader:
            self.reader.initialise_reader(data_param, task_param)
        //if self.is_training or self._infer_type in ("encode", "encode-decode"):
        //    mean_var_normaliser = MeanVarNormalisationLayer(image_name="image")
        //    self.reader.add_preprocessing_layers([mean_var_normaliser])

    def initialise_sampler(self):
        self.sampler = []
        if self.is_training:
            self.sampler.append(ResizeSampler(

After Change

            self.readers = [ImageReader(["image"], phase="train"),
                            ImageReader(["image"], phase="validation")]
        if self._infer_type in ("encode", "encode-decode"):
            self.readers = [ImageReader(["image"], phase="test")]
        elif self._infer_type == "sample":
            self.readers = []
        elif self._infer_type == "linear_interpolation":
            self.readers = [ImageReader(["feature"], phase="test")]

        for reader in self.readers:
            reader.initialise_reader(data_param, task_param)
        //if self.is_training or self._infer_type in ("encode", "encode-decode"):
        //    mean_var_normaliser = MeanVarNormalisationLayer(image_name="image")
        //    self.reader.add_preprocessing_layers([mean_var_normaliser])

    def initialise_sampler(self):
        self.sampler = []
        if self.is_training:
            self.sampler.append([ResizeSampler(

Instances