def decorated(self, *args, **kwargs):
allowed = config.tensor_float_32_execution_enabled()
try:
config.enable_tensor_float_32_execution(False)
f(self, *args, **kwargs)
finally:
config.enable_tensor_float_32_execution(allowed)
def setUp(self):
self.tf32_keep_ = config.tensor_float_32_execution_enabled()
config.enable_tensor_float_32_execution(False)
# Increase from 1e-6 to 1e-4
self._atol[dtypes.float32] = 1e-4
self._atol[dtypes.complex64] = 1e-4
self._rtol[dtypes.float32] = 1e-4
self._rtol[dtypes.complex64] = 1e-4
def test_tensor_float_32_global_variable(self):
self.assertTrue(config.tensor_float_32_execution_enabled())
self.assertTrue(test_ops.is_tensor_float32_enabled())
config.enable_tensor_float_32_execution(False)
self.assertFalse(config.tensor_float_32_execution_enabled())
self.assertFalse(test_ops.is_tensor_float32_enabled())
config.enable_tensor_float_32_execution(True)
self.assertTrue(config.tensor_float_32_execution_enabled())
self.assertTrue(test_ops.is_tensor_float32_enabled())
def setUp(self):
self.tf32_keep_ = config.tensor_float_32_execution_enabled()
config.enable_tensor_float_32_execution(False)
# Increase from 1e-6 to 1e-4
self._atol[dtypes.float32] = 1e-4
self._atol[dtypes.complex64] = 1e-4
self._rtol[dtypes.float32] = 1e-4
self._rtol[dtypes.complex64] = 1e-4
super(NonSquareLinearOperatorBlockDiagTest, self).setUp()
def setUp(self):
self.tf32_keep_ = config.tensor_float_32_execution_enabled()
config.enable_tensor_float_32_execution(False)
# Decrease tolerance since we are testing with condition numbers as high as
# 1e4.
self._atol[dtypes.float32] = 1e-5
self._rtol[dtypes.float32] = 1e-5
self._atol[dtypes.float64] = 1e-10
self._rtol[dtypes.float64] = 1e-10
self._rtol[dtypes.complex64] = 1e-4
def test_tensor_float_32_disabled(self):
self.assertTrue(config.tensor_float_32_execution_enabled())
config.enable_tensor_float_32_execution(False)
self.assertFalse(config.tensor_float_32_execution_enabled())
x = array_ops.fill((8, 8), 1 + 2**-20)
y = array_ops.ones((8, 8))
out = math_ops.matmul(x, y)
expected = array_ops.fill((8, 8), 8 * (1 + 2**-20))
self.assertAllEqual(out, expected)
def setUp(self):
self.tf32_keep_ = config.tensor_float_32_execution_enabled()
config.enable_tensor_float_32_execution(False)
# Decrease tolerance since we are testing with condition numbers as high as
# 1e4. This class does not use Cholesky, and thus needs even looser
# tolerance.
self._atol[dtypes.float32] = 1e-4
self._rtol[dtypes.float32] = 1e-4
self._atol[dtypes.float64] = 1e-9
self._rtol[dtypes.float64] = 1e-9
self._rtol[dtypes.complex64] = 2e-4
def setUp(self):
self.tf32_keep_ = config.tensor_float_32_execution_enabled()
config.enable_tensor_float_32_execution(False)
def tearDown(self):
config.enable_tensor_float_32_execution(self.tf32_keep_)
def tearDown(self):
super(TensorFloat32Test, self).tearDown()
config.enable_tensor_float_32_execution(True)
math_ops.matmul(operator1.to_dense(), operator2.to_dense()),
self.evaluate(operator_matmul.to_dense()))
operator_matmul = operator2.matmul(operator1)
self.assertTrue(
isinstance(operator_matmul,
linalg_lib.LinearOperatorLowerTriangular))
self.assertAllClose(
math_ops.matmul(operator2.to_dense(), operator1.to_dense()),
self.evaluate(operator_matmul.to_dense()))
def test_tape_safe(self):
tril = variables_module.Variable([[1., 0.], [0., 1.]])
operator = linalg_lib.LinearOperatorLowerTriangular(
tril, is_non_singular=True)
self.check_tape_safe(operator)
def test_convert_variables_to_tensors(self):
tril = variables_module.Variable([[1., 0.], [0., 1.]])
operator = linalg_lib.LinearOperatorLowerTriangular(
tril, is_non_singular=True)
with self.cached_session() as sess:
sess.run([tril.initializer])
self.check_convert_variables_to_tensors(operator)
if __name__ == "__main__":
config.enable_tensor_float_32_execution(False)
linear_operator_test_util.add_tests(LinearOperatorLowerTriangularTest)
test.main()
def setUp(self):
self.tf32_keep_ = config.tensor_float_32_execution_enabled()
config.enable_tensor_float_32_execution(False)
self._atol[dtypes.complex64] = 1e-5
self._rtol[dtypes.complex64] = 1e-5
