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 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 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 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 test_tf32_enabled(self):
self.assertTrue(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)
# In tf32, each element of x is rounded to 1, so the output will be 8s.
expected = array_ops.fill((8, 8), 8)
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.
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 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 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
