def testSimple(self):
with self.assertRaises(TypeError):
_ = gen_math_ops.Add(1., 1.)
x = constant_op.constant(1)
self.assertEqual([2], self.evaluate(gen_math_ops.Add(x=x, y=x)))
def testSimple(self):
with self.assertRaisesRegexp(TypeError, "only takes keyword args"):
_ = gen_math_ops.Add(1., 1.)
x = constant_op.constant(1)
self.assertEqual([2], self.evaluate(gen_math_ops.Add(x=x, y=x)))
def _tfr_control_flow_range_for(x):
# TODO(fengliuai): use len(x) instead
n = 10
x_sum = x[0]
for i in range(1, n):
x_sum = math_ops.Add(x_sum, x[i])
return x_sum
def _tfr_loc_test(x):
n = 10
x_sum = x[0]
for i in range(1, n):
x_sum = math_ops.Add(x_sum, x[i])
return x_sum
def _tfr_tf_ops_tensors(x, y, pred):
if pred:
return math_ops.Add(x, y)
else:
return array_ops.Concat(0, [x, y])
def testName(self):
x = constant_op.constant(1)
op = gen_math_ops.Add(x=x, y=x, name="double")
if not context.executing_eagerly():
# `Tensor.name` is not available in eager.
self.assertEqual(op.name, "double:0")
def testRequiresKwargs_providesSuggestion(self):
msg = "possible keys: \\['x', 'y', 'name'\\]"
with self.assertRaisesRegex(TypeError, msg):
gen_math_ops.Add(1., y=2.)
def testRequiresKwargs(self):
with self.assertRaisesRegex(TypeError, "only takes keyword args"):
gen_math_ops.Add(1., 1.)
def testSimple(self):
x = constant_op.constant(1)
self.assertEqual([2], self.evaluate(gen_math_ops.Add(x=x, y=x)))