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| author | gchanan <gregchanan@gmail.com> | 2018-04-27 15:11:45 -0400 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2018-04-27 15:11:45 -0400 |
| commit | a6bfa16c17c2e2847dbec2ccc1b2b60741ae4c65 (patch) | |
| tree | de8e0bf6da6b26a247f9db13ed60759a89ece06f /test/test_multiprocessing.py | |
| parent | bdd27ea9567675f41eb7000e29f02a841718d25e (diff) | |
| download | pytorch-a6bfa16c17c2e2847dbec2ccc1b2b60741ae4c65.tar.gz pytorch-a6bfa16c17c2e2847dbec2ccc1b2b60741ae4c65.tar.bz2 pytorch-a6bfa16c17c2e2847dbec2ccc1b2b60741ae4c65.zip | |
torch.arange: add numpy-style type inference. (#7016)
* torch.arange: add numpy-style type inference.
This is a backwards-compatibility breaking change.
* Fix flake8.
* Use at::optional.
* Remove unneeded header files.
* Use reference wrapper.
* Update arange for test.
* Address review comments.
Diffstat (limited to 'test/test_multiprocessing.py')
| -rw-r--r-- | test/test_multiprocessing.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/test/test_multiprocessing.py b/test/test_multiprocessing.py index 4eec7080f3..a7c0e1befd 100644 --- a/test/test_multiprocessing.py +++ b/test/test_multiprocessing.py @@ -92,7 +92,7 @@ def autograd_sharing(queue, ready, master_modified): ready.set() master_modified.wait() - expected_var = torch.arange(1, 26).view(5, 5) + expected_var = torch.arange(1., 26).view(5, 5) expected_var[0, 0] = 1000 is_ok = var.data.equal(expected_var) var.data[:] = torch.ones(5, 5) @@ -314,7 +314,7 @@ class TestMultiprocessing(TestCase): tensors = [] for i in range(5): device = i % 2 - tensors += [torch.arange(i * 5, (i + 1) * 5).cuda(device)] + tensors += [torch.arange(i * 5., (i + 1) * 5).cuda(device)] inq = ctx.Queue() outq = ctx.Queue() @@ -329,7 +329,7 @@ class TestMultiprocessing(TestCase): for i, tensor in enumerate(tensors): v, device, tensor_size, storage_size = results[i] - self.assertEqual(v, torch.arange(i * 5, (i + 1) * 5).sum()) + self.assertEqual(v, torch.arange(i * 5., (i + 1) * 5).sum()) self.assertEqual(device, i % 2) self.assertEqual(tensor_size, 5) self.assertEqual(storage_size, 5) @@ -412,12 +412,12 @@ class TestMultiprocessing(TestCase): def test_variable_sharing(self): for requires_grad in [True, False]: - var = Variable(torch.arange(1, 26).view(5, 5), + var = Variable(torch.arange(1., 26).view(5, 5), requires_grad=requires_grad) self._test_autograd_sharing(var) def test_parameter_sharing(self): - param = Parameter(torch.arange(1, 26).view(5, 5)) + param = Parameter(torch.arange(1., 26).view(5, 5)) self._test_autograd_sharing(param) def test_empty_shared(self): |