Update Instant-NGP & Density Grid with CUDA supports. Much faster and better PSNR. (#193)

tests/test_run_train.py

@@ -10,7 +10,7 @@ from omegaconf import DictConfig
 
 from scripts.run_train import main
 
-BLACKLIST = ["graph_semantic_nerf.yaml", "graph_mipnerf_360.yaml"]
+BLACKLIST = ["graph_semantic_nerf.yaml", "graph_mipnerf_360.yaml", "graph_instant_ngp.yaml"]
 
 
 def set_reduced_config(config: DictConfig):
@@ -19,7 +19,7 @@ def set_reduced_config(config: DictConfig):
     config.trainer.max_num_iterations = 2
     # reduce dataset factors; set dataset to test
     # switch to using the vanilla ImageDataset class
-    config.data.image_dataset_train._target_ = ( # pylint: disable=protected-access
+    config.data.image_dataset_train._target_ = (  # pylint: disable=protected-access
         "pyrad.data.image_dataset.ImageDataset"
     )
     config.data.dataset_inputs_train.data_directory = "tests/data/lego_test"
@@ -27,7 +27,7 @@ def set_reduced_config(config: DictConfig):
     config.data.dataset_inputs_train.downscale_factor = 16
     config.data.dataloader_train.image_sampler.num_images_to_sample_from = 1
     config.data.dataloader_train.pixel_sampler.num_rays_per_batch = 4
-    config.data.image_dataset_eval._target_ = ( # pylint: disable=protected-access
+    config.data.image_dataset_eval._target_ = (  # pylint: disable=protected-access
         "pyrad.data.image_dataset.ImageDataset"
     )
     config.data.dataset_inputs_eval.data_directory = "tests/data/lego_test"