Fix test evaluation for Blender data

Summary: Blender data doesn't have depths or crops.

Reviewed By: shapovalov

Differential Revision: D38345583

fbshipit-source-id: a19300daf666bbfd799d0038aeefa14641c559d7

projects/implicitron_trainer/configs/repro_singleseq_nerf_blender.yaml

@@ -8,9 +8,9 @@ data_source_ImplicitronDataSource_args:
   dataset_map_provider_class_type: BlenderDatasetMapProvider
   dataset_map_provider_BlenderDatasetMapProvider_args:
     base_dir: ${oc.env:BLENDER_DATASET_ROOT}
+    n_known_frames_for_test: null
     object_name: ${oc.env:BLENDER_SINGLESEQ_CLASS}
     path_manager_factory_class_type: PathManagerFactory
-    n_known_frames_for_test: null
     path_manager_factory_PathManagerFactory_args:
       silence_logs: true
 
@@ -20,8 +20,13 @@ model_factory_ImplicitronModelFactory_args:
       n_rays_per_image_sampled_from_mask: 4096
       scene_extent: 2.0
     renderer_MultiPassEmissionAbsorptionRenderer_args:
+      density_noise_std_train: 1.0
       n_pts_per_ray_fine_training: 128
       n_pts_per_ray_fine_evaluation: 128
+      raymarcher_EmissionAbsorptionRaymarcher_args:
+        blend_output: true
+        bg_color:
+        - 1.0
     loss_weights:
       loss_rgb_mse: 1.0
       loss_prev_stage_rgb_mse: 1.0
@@ -30,9 +35,12 @@ model_factory_ImplicitronModelFactory_args:
       loss_autodecoder_norm: 0.00
 
 optimizer_factory_ImplicitronOptimizerFactory_args:
-  exponential_lr_step_size: 2000
+  exponential_lr_step_size: 3001
+  lr_policy: Exponential
 
 training_loop_ImplicitronTrainingLoop_args:
-  max_epochs: 2000
-  visualize_interval: 0
-  validation_interval: 30
+  max_epochs: 3001
+  metric_print_interval: 100
+  store_checkpoints_purge: 3
+  test_when_finished: true
+  validation_interval: 100

projects/implicitron_trainer/tests/test_experiment.py

@@ -161,7 +161,7 @@ class TestExperiment(unittest.TestCase):
 
 
 class TestNerfRepro(unittest.TestCase):
-    @unittest.skip("This test reproduces full NERF training.")
+    @unittest.skip("This runs full NeRF training on Blender data.")
     def test_nerf_blender(self):
         # Train vanilla NERF.
         # Set env vars BLENDER_DATASET_ROOT and BLENDER_SINGLESEQ_CLASS first!