--- /dev/null
+import torch
+
+from torch.testing._internal.common_utils import TestCase, run_tests, gradcheck
+
+
+class TestAutogradComplex(TestCase):
+ def test_view_func_for_complex_views(self):
+ # case 1: both parent and child have view_func
+ x = torch.randn(2, 2, 2, dtype=torch.double, requires_grad=True)
+ y = x.detach().requires_grad_(True)
+
+ x0 = x.clone()
+ x1 = torch.view_as_complex(x0)
+ x2 = torch.view_as_real(x1)
+ x2.mul_(2)
+ x2.sum().backward()
+
+ y0 = y.clone()
+ y0.mul_(2)
+ y0.sum().backward()
+
+ self.assertEqual(x.grad, y.grad)
+
+ # case 2: parent has view_func but child does not
+ x = torch.randn(2, 2, 2, dtype=torch.double, requires_grad=True)
+ y = x.detach().requires_grad_(True)
+
+ def fn(a):
+ b = a.clone()
+ b1 = torch.view_as_complex(b)
+ b2 = b1.reshape(b1.numel())
+ return b2
+
+ x0 = fn(x)
+ x0.mul_(2)
+ x0.sum().backward()
+
+ y0 = fn(y)
+ y1 = y0.mul(2)
+ y1.sum().backward()
+
+ self.assertEqual(x.grad, y.grad)
+
+ # case 3: parent does not have a view_func but child does
+ x = torch.randn(10, dtype=torch.cdouble, requires_grad=True)
+ y = x.detach().requires_grad_(True)
+
+ def fn(a, dim0_size=5):
+ b = a.clone()
+ b1 = b.reshape(dim0_size, 2)
+ b2 = torch.view_as_real(b1)
+ return b2
+
+ x0 = fn(x)
+ x0.mul_(2)
+ x0.sum().backward()
+
+ y0 = fn(y)
+ y1 = y0.mul(2)
+ y1.sum().backward()
+
+ self.assertEqual(x.grad, y.grad)
+
+ def test_view_with_multi_output(self):
+ x = torch.randn(2, 2, 2, dtype=torch.double)
+
+ x1 = torch.view_as_complex(x)
+ # Taking an invalid view should always be allowed as long as it is not
+ # modified inplace
+ res = x1.unbind(0)
+
+ with self.assertRaisesRegex(RuntimeError, "output of a function that returns multiple views"):
+ res[0] += torch.rand(2, requires_grad=True)
+
+ x.requires_grad_(True)
+ x1 = torch.view_as_complex(x)
+ # Taking an invalid view should always be allowed as long as it is not
+ # modified inplace
+ res = x1.unbind(0)
+
+ with self.assertRaisesRegex(RuntimeError, "output of a function that returns multiple views"):
+ res[0] += torch.rand(2, requires_grad=True)
+
+ def as_identity(self):
+ # view_as_real and view_as_complex behavior should be like an identity
+ def func(z):
+ z_ = torch.view_as_complex(z)
+ z_select = torch.select(z_, z_.dim() - 1, 0)
+ z_select_real = torch.view_as_real(z_select)
+ return z_select_real.sum()
+
+ z = torch.randn(10, 2, 2, dtype=torch.double, requires_grad=True)
+ gradcheck(func, [z])
+ func(z).backward()
+
+ z1 = z.clone().detach().requires_grad_(True)
+ torch.select(z1, z1.dim() - 2, 0).sum().backward()
+
+ self.assertEqual(z.grad, z1.grad)
+
+
+if __name__ == '__main__':
+ run_tests()
from torch.testing._internal.common_cuda import TEST_CUDA
from torch.testing._internal.common_utils import (TestCase, run_tests, skipIfNoLapack,
suppress_warnings, slowTest,
- load_tests,
IS_WINDOWS, IS_MACOS, CudaMemoryLeakCheck,
TEST_WITH_ROCM, disable_gc,
gradcheck, gradgradcheck)
deviceCountAtLeast, skipCUDAIfCudnnVersionLessThan,
skipCUDAIf, skipMeta)
-
-# load_tests from common_utils is used to automatically filter tests for
-# sharding on sandcastle. This line silences flake warnings
-load_tests = load_tests
-
import pickle
PRECISION = 1e-4
test_case.assertEqual(self_variable.size(), self_variable.grad.size())
-class TestAutogradComplex(TestCase):
- def test_view_func_for_complex_views(self):
- # case 1: both parent and child have view_func
- x = torch.randn(2, 2, 2, dtype=torch.double, requires_grad=True)
- y = x.detach().requires_grad_(True)
-
- x0 = x.clone()
- x1 = torch.view_as_complex(x0)
- x2 = torch.view_as_real(x1)
- x2.mul_(2)
- x2.sum().backward()
-
- y0 = y.clone()
- y0.mul_(2)
- y0.sum().backward()
-
- self.assertEqual(x.grad, y.grad)
-
- # case 2: parent has view_func but child does not
- x = torch.randn(2, 2, 2, dtype=torch.double, requires_grad=True)
- y = x.detach().requires_grad_(True)
-
- def fn(a):
- b = a.clone()
- b1 = torch.view_as_complex(b)
- b2 = b1.reshape(b1.numel())
- return b2
-
- x0 = fn(x)
- x0.mul_(2)
- x0.sum().backward()
-
- y0 = fn(y)
- y1 = y0.mul(2)
- y1.sum().backward()
-
- self.assertEqual(x.grad, y.grad)
-
- # case 3: parent does not have a view_func but child does
- x = torch.randn(10, dtype=torch.cdouble, requires_grad=True)
- y = x.detach().requires_grad_(True)
-
- def fn(a, dim0_size=5):
- b = a.clone()
- b1 = b.reshape(dim0_size, 2)
- b2 = torch.view_as_real(b1)
- return b2
-
- x0 = fn(x)
- x0.mul_(2)
- x0.sum().backward()
-
- y0 = fn(y)
- y1 = y0.mul(2)
- y1.sum().backward()
-
- self.assertEqual(x.grad, y.grad)
-
- def test_view_with_multi_output(self):
- x = torch.randn(2, 2, 2, dtype=torch.double)
-
- x1 = torch.view_as_complex(x)
- # Taking an invalid view should always be allowed as long as it is not
- # modified inplace
- res = x1.unbind(0)
-
- with self.assertRaisesRegex(RuntimeError, "output of a function that returns multiple views"):
- res[0] += torch.rand(2, requires_grad=True)
-
- x.requires_grad_(True)
- x1 = torch.view_as_complex(x)
- # Taking an invalid view should always be allowed as long as it is not
- # modified inplace
- res = x1.unbind(0)
-
- with self.assertRaisesRegex(RuntimeError, "output of a function that returns multiple views"):
- res[0] += torch.rand(2, requires_grad=True)
-
- def as_identity(self):
- # view_as_real and view_as_complex behavior should be like an identity
- def func(z):
- z_ = torch.view_as_complex(z)
- z_select = torch.select(z_, z_.dim() - 1, 0)
- z_select_real = torch.view_as_real(z_select)
- return z_select_real.sum()
-
- z = torch.randn(10, 2, 2, dtype=torch.double, requires_grad=True)
- gradcheck(func, [z])
- func(z).backward()
-
- z1 = z.clone().detach().requires_grad_(True)
- torch.select(z1, z1.dim() - 2, 0).sum().backward()
-
- self.assertEqual(z.grad, z1.grad)
-
class TestAutogradFunctional(TestCase):
def _assert_same_struct(self, res, base):
# base and res should be Tensors or tuple of Tensors with the same size
torch.autograd.gradcheck(fn, [inp_r, inp_c], check_forward_ad=True)
torch.autograd.gradcheck(fn, [inp_c, inp_r], check_forward_ad=True)
+# Import test cases from below autograd/ here. These are found
+# implicitly by the loader, so Flake8 thinks they are unused, hence
+# the suppressions.
+
+from autograd.test_complex import TestAutogradComplex # noqa: F401
# e.g., TestAutogradDeviceTypeCPU and TestAutogradDeviceTypeCUDA
instantiate_device_type_tests(
projects / platform / upstream / pytorch.git / commitdiff