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Cuda updates

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Summary:
Updates to:
- enable cuda kernel launches on any GPU (not just the default)
- cuda and contiguous checks for all kernels
- checks to ensure all tensors are on the same device
- error reporting in the cuda kernels
- cuda tests now run on a random device not just the default

Reviewed By: jcjohnson, gkioxari

Differential Revision: D21215280

fbshipit-source-id: 1bedc9fe6c35e9e920bdc4d78ed12865b1005519
This commit is contained in:
Nikhila Ravi
2020-04-24 09:07:54 -07:00
committed by Facebook GitHub Bot
parent c9267ab7af
commit c3d636dc8c
33 changed files with 979 additions and 240 deletions
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10
tests/test_graph_conv.py
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@@ -4,7 +4,7 @@ import unittest
import torch
import torch.nn as nn
from common_testing import TestCaseMixin
from common_testing import TestCaseMixin, get_random_cuda_device
from pytorch3d import _C
from pytorch3d.ops.graph_conv import GraphConv, gather_scatter, gather_scatter_python
from pytorch3d.structures.meshes import Meshes
@@ -14,7 +14,7 @@ from pytorch3d.utils import ico_sphere
class TestGraphConv(TestCaseMixin, unittest.TestCase):
def test_undirected(self):
dtype = torch.float32
device = torch.device("cuda:0")
device = get_random_cuda_device()
verts = torch.tensor(
[[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=dtype, device=device
)
@@ -97,7 +97,7 @@ class TestGraphConv(TestCaseMixin, unittest.TestCase):
self.assertClose(y, expected_y)
def test_backward(self):
device = torch.device("cuda:0")
device = get_random_cuda_device()
mesh = ico_sphere()
verts = mesh.verts_packed()
edges = mesh.edges_packed()
@@ -118,7 +118,7 @@ class TestGraphConv(TestCaseMixin, unittest.TestCase):
self.assertEqual(repr(conv), "GraphConv(32 -> 64, directed=True)")
def test_cpu_cuda_tensor_error(self):
device = torch.device("cuda:0")
device = get_random_cuda_device()
verts = torch.tensor(
[[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=torch.float32, device=device
)
@@ -134,7 +134,7 @@ class TestGraphConv(TestCaseMixin, unittest.TestCase):
Check that gather_scatter cuda version throws an error if cpu tensors
are given as input.
"""
device = torch.device("cuda:0")
device = get_random_cuda_device()
mesh = ico_sphere()
verts = mesh.verts_packed()
edges = mesh.edges_packed()