Name changes

examples/text_to_image.py

@@ -8,7 +8,7 @@
 import matplotlib.pyplot as plt
 from high_order_implicit_representation.networks import GenNet
 from pytorch_lightning.callbacks import LearningRateMonitor
-from high_order_implicit_representation.rendering import Text2ImageGenerator
+from high_order_implicit_representation.rendering import Text2ImageSampler
 from high_order_implicit_representation.single_image_dataset import (
     image_to_dataset,
     Text2ImageDataModule
@@ -34,15 +34,15 @@ def run_implicit_images(cfg: DictConfig):
         data_module = Text2ImageDataModule(
             filenames=full_path, batch_size=cfg.batch_size, rotations=cfg.rotations
         )
-        image_generator = Text2ImageGenerator(
+        image_generator = Text2ImageSampler(
             filename=full_path[0], rotations=cfg.rotations, batch_size=cfg.batch_size
         )
         lr_monitor = LearningRateMonitor(logging_interval="epoch")
         trainer = Trainer(
             max_epochs=cfg.max_epochs,
             devices=cfg.gpus,
             accelerator=cfg.accelerator,
-            callbacks=[lr_monitor, image_generator],
+            callbacks=[lr_monitor],
         )
         model = GenNet(cfg)
         trainer.fit(model, datamodule=data_module)

high_order_implicit_representation/rendering.py

@@ -242,7 +242,7 @@ def on_train_epoch_end(
                 f"image", image, global_step=trainer.global_step
             )
 
-class Text2ImageGenerator(Callback):
+class Text2ImageSampler(Callback):
     def __init__(self, filename, rotations, batch_size):
         self._dataset = Text2ImageRenderDataset(filename, rotations=rotations)
         self._dataloader = DataLoader(self._dataset, batch_size=batch_size, shuffle=False)

tests/test_single_image_dataset.py

@@ -59,4 +59,4 @@ def test_text_to_image_sampler_dataloader():
         print("element", element[1][0].shape)
         assert element[0].shape[0] ==2
         assert len(element) == 3
-        break
+        break