Adding utility methods to TensorProperties

Summary:
Context: in the code we are releasing with CO3D dataset, we use  `cuda()` on TensorProperties like Pointclouds and Cameras where we recursively move batch to a GPU. It would be good to push it to a release so we don’t need to depend on the nightly build.

Additionally, I aligned the logic of `.to("cuda")` without device index to the one of `torch.Tensor` where the current device is populated to index. It should not affect any actual use cases but some tests had to be changed.

Reviewed By: bottler

Differential Revision: D29659529

fbshipit-source-id: abe58aeaca14bacc68da3e6cf5ae07df3353e3ce

Author: shapovalov

pytorch3d/common/types.py

@@ -15,15 +15,21 @@
 def make_device(device: Device) -> torch.device:
     """
     Makes an actual torch.device object from the device specified as
-    either a string or torch.device object.
+    either a string or torch.device object. If the device is `cuda` without
+    a specific index, the index of the current device is assigned.
 
     Args:
         device: Device (as str or torch.device)
 
     Returns:
         A matching torch.device object
     """
-    return torch.device(device) if isinstance(device, str) else device
+    device = torch.device(device) if isinstance(device, str) else device
+    if device.type == "cuda" and device.index is None:  # pyre-ignore[16]
+        # If cuda but with no index, then the current cuda device is indicated.
+        # In that case, we fix to that device
+        device = torch.device(f"cuda:{torch.cuda.current_device()}")
+    return device
 
 
 def get_device(x, device: Optional[Device] = None) -> torch.device:

pytorch3d/renderer/utils.py

@@ -8,7 +8,7 @@
 import copy
 import inspect
 import warnings
-from typing import Any, Union
+from typing import Any, Optional, Union
 
 import numpy as np
 import torch
@@ -174,6 +174,12 @@ def to(self, device: Device = "cpu") -> "TensorProperties":
                 setattr(self, k, v.to(device_))
         return self
 
+    def cpu(self) -> "TensorProperties":
+        return self.to("cpu")
+
+    def cuda(self, device: Optional[int] = None) -> "TensorProperties":
+        return self.to(f"cuda:{device}" if device is not None else "cuda")
+
     def clone(self, other) -> "TensorProperties":
         """
         Update the tensor properties of other with the cloned properties of self.

tests/test_meshes.py

@@ -709,9 +709,9 @@ def test_to(self):
         self.assertEqual(cpu_device, mesh.device)
         self.assertIs(mesh, converted_mesh)
 
-        cuda_device = torch.device("cuda")
+        cuda_device = torch.device("cuda:0")
 
-        converted_mesh = mesh.to("cuda")
+        converted_mesh = mesh.to("cuda:0")
         self.assertEqual(cuda_device, converted_mesh.device)
         self.assertEqual(cpu_device, mesh.device)
         self.assertIsNot(mesh, converted_mesh)

tests/test_rendering_utils.py

@@ -39,7 +39,17 @@ def test_to(self):
         example = TensorPropertiesTestClass(x=10.0, y=(100.0, 200.0))
         device = torch.device("cuda:0")
         new_example = example.to(device=device)
-        self.assertTrue(new_example.device == device)
+        self.assertEqual(new_example.device, device)
+
+        example_cpu = example.cpu()
+        self.assertEqual(example_cpu.device, torch.device("cpu"))
+
+        example_gpu = example.cuda()
+        self.assertEqual(example_gpu.device.type, "cuda")
+        self.assertIsNotNone(example_gpu.device.index)
+
+        example_gpu1 = example.cuda(1)
+        self.assertEqual(example_gpu1.device, torch.device("cuda:1"))
 
     def test_clone(self):
         # Check clone method

tests/test_shader.py

@@ -22,7 +22,7 @@
 class TestShader(TestCaseMixin, unittest.TestCase):
     def test_to(self):
         cpu_device = torch.device("cpu")
-        cuda_device = torch.device("cuda")
+        cuda_device = torch.device("cuda:0")
 
         R, T = look_at_view_transform()
 

tests/test_transforms.py

@@ -50,9 +50,9 @@ def test_to(self):
         self.assertEqual(torch.float32, t.dtype)
         self.assertIsNot(t, cpu_t)
 
-        cuda_device = torch.device("cuda")
+        cuda_device = torch.device("cuda:0")
 
-        cuda_t = t.to("cuda")
+        cuda_t = t.to("cuda:0")
         self.assertEqual(cuda_device, cuda_t.device)
         self.assertEqual(cpu_device, t.device)
         self.assertEqual(torch.float32, cuda_t.dtype)