Linter, deprecated type()

Summary: Run linter after recent changes. Fix long comment in knn.h which clang-format has reflowed badly. Add crude test that code doesn't call deprecated `.type()` or `.data()`.

Reviewed By: nikhilaravi

Differential Revision: D20692935

fbshipit-source-id: 28ce0308adae79a870cb41a810b7cf8744f41ab8

tests/bm_knn.py

@@ -1,7 +1,6 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
 
 from itertools import product
-
 import torch
 from fvcore.common.benchmark import benchmark
 
@@ -30,21 +29,13 @@ def benchmark_knn_cuda_versions() -> None:
             continue
         if version == 3 and K > 4:
             continue
-        knn_kwargs.append({'N': N, 'D': D, 'P': P, 'K': K, 'v': version})
+        knn_kwargs.append({"N": N, "D": D, "P": P, "K": K, "v": version})
     for N, P, D in product(Ns, Ps, Ds):
-        nn_kwargs.append({'N': N, 'D': D, 'P': P})
+        nn_kwargs.append({"N": N, "D": D, "P": P})
     benchmark(
-        knn_cuda_with_init,
-        'KNN_CUDA_VERSIONS',
-        knn_kwargs,
-        warmup_iters=1,
-    )
-    benchmark(
-        nn_cuda_with_init,
-        'NN_CUDA',
-        nn_kwargs,
-        warmup_iters=1,
+        knn_cuda_with_init, "KNN_CUDA_VERSIONS", knn_kwargs, warmup_iters=1
     )
+    benchmark(nn_cuda_with_init, "NN_CUDA", nn_kwargs, warmup_iters=1)
 
 
 def benchmark_knn_cuda_vs_naive() -> None:
@@ -55,21 +46,16 @@ def benchmark_knn_cuda_vs_naive() -> None:
     Ks = [1, 2, 4, 8, 16]
     knn_kwargs, naive_kwargs = [], []
     for N, P, D, K in product(Ns, Ps, Ds, Ks):
-        knn_kwargs.append({'N': N, 'D': D, 'P': P, 'K': K})
+        knn_kwargs.append({"N": N, "D": D, "P": P, "K": K})
         if P <= 4096:
-            naive_kwargs.append({'N': N, 'D': D, 'P': P, 'K': K})
+            naive_kwargs.append({"N": N, "D": D, "P": P, "K": K})
     benchmark(
         knn_python_cuda_with_init,
-        'KNN_CUDA_PYTHON',
+        "KNN_CUDA_PYTHON",
         naive_kwargs,
         warmup_iters=1,
     )
-    benchmark(
-        knn_cuda_with_init,
-        'KNN_CUDA',
-        knn_kwargs,
-        warmup_iters=1,
-    )
+    benchmark(knn_cuda_with_init, "KNN_CUDA", knn_kwargs, warmup_iters=1)
 
 
 def benchmark_knn_cpu() -> None:
@@ -79,31 +65,18 @@ def benchmark_knn_cpu() -> None:
     Ks = [1, 2, 4]
     knn_kwargs, nn_kwargs = [], []
     for N, P, D, K in product(Ns, Ps, Ds, Ks):
-        knn_kwargs.append({'N': N, 'D': D, 'P': P, 'K': K})
+        knn_kwargs.append({"N": N, "D": D, "P": P, "K": K})
     for N, P, D in product(Ns, Ps, Ds):
-        nn_kwargs.append({'N': N, 'D': D, 'P': P})
+        nn_kwargs.append({"N": N, "D": D, "P": P})
     benchmark(
-        knn_python_cpu_with_init,
-        'KNN_CPU_PYTHON',
-        knn_kwargs,
-        warmup_iters=1,
-    )
-    benchmark(
-        knn_cpu_with_init,
-        'KNN_CPU_CPP',
-        knn_kwargs,
-        warmup_iters=1,
-    )
-    benchmark(
-        nn_cpu_with_init,
-        'NN_CPU_CPP',
-        nn_kwargs,
-        warmup_iters=1,
+        knn_python_cpu_with_init, "KNN_CPU_PYTHON", knn_kwargs, warmup_iters=1
     )
+    benchmark(knn_cpu_with_init, "KNN_CPU_CPP", knn_kwargs, warmup_iters=1)
+    benchmark(nn_cpu_with_init, "NN_CPU_CPP", nn_kwargs, warmup_iters=1)
 
 
 def knn_cuda_with_init(N, D, P, K, v=-1):
-    device = torch.device('cuda:0')
+    device = torch.device("cuda:0")
     x = torch.randn(N, P, D, device=device)
     y = torch.randn(N, P, D, device=device)
     torch.cuda.synchronize()
@@ -116,7 +89,7 @@ def knn_cuda_with_init(N, D, P, K, v=-1):
 
 
 def knn_cpu_with_init(N, D, P, K):
-    device = torch.device('cpu')
+    device = torch.device("cpu")
     x = torch.randn(N, P, D, device=device)
     y = torch.randn(N, P, D, device=device)
 
@@ -127,7 +100,7 @@ def knn_cpu_with_init(N, D, P, K):
 
 
 def knn_python_cuda_with_init(N, D, P, K):
-    device = torch.device('cuda')
+    device = torch.device("cuda")
     x = torch.randn(N, P, D, device=device)
     y = torch.randn(N, P, D, device=device)
     torch.cuda.synchronize()
@@ -140,7 +113,7 @@ def knn_python_cuda_with_init(N, D, P, K):
 
 
 def knn_python_cpu_with_init(N, D, P, K):
-    device = torch.device('cpu')
+    device = torch.device("cpu")
     x = torch.randn(N, P, D, device=device)
     y = torch.randn(N, P, D, device=device)
 
@@ -151,7 +124,7 @@ def knn_python_cpu_with_init(N, D, P, K):
 
 
 def nn_cuda_with_init(N, D, P):
-    device = torch.device('cuda')
+    device = torch.device("cuda")
     x = torch.randn(N, P, D, device=device)
     y = torch.randn(N, P, D, device=device)
     torch.cuda.synchronize()
@@ -164,7 +137,7 @@ def nn_cuda_with_init(N, D, P):
 
 
 def nn_cpu_with_init(N, D, P):
-    device = torch.device('cpu')
+    device = torch.device("cpu")
     x = torch.randn(N, P, D, device=device)
     y = torch.randn(N, P, D, device=device)
 

tests/test_build.py

@@ -22,6 +22,27 @@ class TestBuild(unittest.TestCase):
         for k, v in counter.items():
             self.assertEqual(v, 1, f"Too many files with stem {k}.")
 
+    def test_deprecated_usage(self):
+        # Check certain expressions do not occur in the csrc code
+        test_dir = Path(__file__).resolve().parent
+        source_dir = test_dir.parent / "pytorch3d" / "csrc"
+
+        files = sorted(source_dir.glob("**/*.*"))
+        self.assertGreater(len(files), 4)
+
+        patterns = [".type()", ".data()"]
+
+        for file in files:
+            with open(file) as f:
+                text = f.read()
+                for pattern in patterns:
+                    found = pattern in text
+                    msg = (
+                        f"{pattern} found in {file.name}"
+                        + ", this has been deprecated."
+                    )
+                    self.assertFalse(found, msg)
+
     def test_copyright(self):
         test_dir = Path(__file__).resolve().parent
         root_dir = test_dir.parent

tests/test_knn.py

@@ -28,7 +28,7 @@ class TestKNN(unittest.TestCase):
 
     def test_knn_vs_python_cpu(self):
         """ Test CPU output vs PyTorch implementation """
-        device = torch.device('cpu')
+        device = torch.device("cpu")
         Ns = [1, 4]
         Ds = [2, 3]
         P1s = [1, 10, 101]
@@ -45,7 +45,7 @@ class TestKNN(unittest.TestCase):
 
     def test_knn_vs_python_cuda(self):
         """ Test CUDA output vs PyTorch implementation """
-        device = torch.device('cuda')
+        device = torch.device("cuda")
         Ns = [1, 4]
         Ds = [2, 3, 8]
         P1s = [1, 8, 64, 128, 1001]