extract camera_difficulty_bin_breaks

Summary: As part of removing Task, move camera difficulty bin breaks from hard code to the top level.

Reviewed By: davnov134

Differential Revision: D37491040

fbshipit-source-id: f2d6775ebc490f6f75020d13f37f6b588cc07a0b

projects/implicitron_trainer/configs/repro_multiseq_base.yaml

@@ -27,3 +27,6 @@ solver_args:
   max_epochs: 3000
   milestones:
   - 1000
+camera_difficulty_bin_breaks:
+  - 0.666667
+  - 0.833334

projects/implicitron_trainer/experiment.py

@@ -535,7 +535,12 @@ def run_training(cfg: DictConfig, device: str = "cpu") -> None:
                 and epoch % cfg.test_interval == 0
             ):
                 _run_eval(
-                    model, all_train_cameras, dataloaders.test, task, device=device
+                    model,
+                    all_train_cameras,
+                    dataloaders.test,
+                    task,
+                    camera_difficulty_bin_breaks=cfg.camera_difficulty_bin_breaks,
+                    device=device,
                 )
 
             assert stats.epoch == epoch, "inconsistent stats!"
@@ -588,7 +593,14 @@ def _eval_and_dump(
     if dataloader is None:
         raise ValueError('DataLoaderMap have to contain the "test" entry for eval!')
 
-    results = _run_eval(model, all_train_cameras, dataloader, task, device=device)
+    results = _run_eval(
+        model,
+        all_train_cameras,
+        dataloader,
+        task,
+        camera_difficulty_bin_breaks=cfg.camera_difficulty_bin_breaks,
+        device=device,
+    )
 
     # add the evaluation epoch to the results
     for r in results:
@@ -615,7 +627,14 @@ def _get_eval_frame_data(frame_data):
     return frame_data_for_eval
 
 
-def _run_eval(model, all_train_cameras, loader, task: Task, device):
+def _run_eval(
+    model,
+    all_train_cameras,
+    loader,
+    task: Task,
+    camera_difficulty_bin_breaks: Tuple[float, float],
+    device,
+):
     """
     Run the evaluation loop on the test dataloader
     """
@@ -648,7 +667,7 @@ def _run_eval(model, all_train_cameras, loader, task: Task, device):
             )
 
     _, category_result = evaluate.summarize_nvs_eval_results(
-        per_batch_eval_results, task
+        per_batch_eval_results, task, camera_difficulty_bin_breaks
     )
 
     return category_result["results"]
@@ -684,6 +703,7 @@ class ExperimentConfig(Configurable):
     visdom_server: str = "http://127.0.0.1"
     visualize_interval: int = 1000
     clip_grad: float = 0.0
+    camera_difficulty_bin_breaks: Tuple[float, ...] = 0.97, 0.98
 
     hydra: dict = field(
         default_factory=lambda: {

projects/implicitron_trainer/tests/experiment.yaml

@@ -375,6 +375,9 @@ visdom_port: 8097
 visdom_server: http://127.0.0.1
 visualize_interval: 1000
 clip_grad: 0.0
+camera_difficulty_bin_breaks:
+- 0.97
+- 0.98
 hydra:
   run:
     dir: .