SplatterPhongShader Benchmarks

Summary:
Benchmarking. We only use num_faces=2 for splatter, because as far as I can see one would never need to use more. Pose optimization and mesh optimization experiments (see next two diffs) showed that Splatter with 2 faces beats Softmax with 50 and 100 faces in terms of accuracy.

Results: We're slower at 64px^2. At 128px and 256px, we're slower than Softmax+50faces, but faster than Softmax+100faces. We're also slower at 10 faces/pix, but expectation as well as results show that more then 2 faces shouldn't be necessary. See also more results in .https://fburl.com/gdoc/ttv7u7hp

Reviewed By: jcjohnson

Differential Revision: D36210575

fbshipit-source-id: c8de28c8a59ce5fe21a47263bd43d2757b15d123

tests/benchmarks/bm_blending.py

@@ -16,7 +16,7 @@ def bm_blending() -> None:
     kwargs_list = []
     num_meshes = [8]
     image_size = [64, 128, 256]
-    faces_per_pixel = [50, 100]
+    faces_per_pixel = [2, 50, 100]
     backend = ["pytorch", "custom"]
     test_cases = product(num_meshes, image_size, faces_per_pixel, devices, backend)
 
@@ -47,6 +47,28 @@ def bm_blending() -> None:
         warmup_iters=1,
     )
 
+    kwargs_list = []
+    faces_per_pixel = [2, 10]
+    backend = ["pytorch"]
+    test_cases = product(num_meshes, image_size, faces_per_pixel, devices, backend)
+    for case in test_cases:
+        n, s, k, d, b = case
+        kwargs_list.append(
+            {
+                "num_meshes": n,
+                "image_size": s,
+                "faces_per_pixel": k,
+                "device": d,
+                "backend": b,
+            }
+        )
+    benchmark(
+        TestBlending.bm_splatter_blending,
+        "SPLATTER_BLENDING_PYTORCH",
+        kwargs_list,
+        warmup_iters=1,
+    )
+
 
 if __name__ == "__main__":
     bm_blending()