fix(tests): reduce r2plus1d_18 input size to prevent OOM

The test_video_r2plus1_18 test used a (16,3,16,112,112) input (~96M
elements) which consistently got OOM-killed. Reduced to (1,3,1,112,112)
which passes reliably while still exercising the full model.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: johnmarktaylor91

tests/test_real_world_models_slow.py

@@ -832,7 +832,7 @@ def test_taskonomy(default_input1):
 
 def test_video_r2plus1_18():
     model = torchvision.models.video.r2plus1d_18()
-    model_input = torch.randn(16, 3, 16, 112, 112)
+    model_input = torch.randn(1, 3, 1, 112, 112)
     show_model_graph(
         model,
         model_input,