| @@ -277,7 +277,7 @@ namespace TensorFlowNET.UnitTest | |||||
| AssertItemsEqual(new[] {a_4.op}, e_4.op.control_inputs); | AssertItemsEqual(new[] {a_4.op}, e_4.op.control_inputs); | ||||
| } | } | ||||
| [Ignore("will fail due to unsupported op 'FloatOutput'")] | |||||
| [Ignore("Don't know how to create an operation with two outputs")] | |||||
| [TestMethod] | [TestMethod] | ||||
| public void TestRepeatedDependency() | public void TestRepeatedDependency() | ||||
| { | { | ||||
| @@ -293,16 +293,22 @@ namespace TensorFlowNET.UnitTest | |||||
| self.assertEqual(b.op.control_inputs, [a]) | self.assertEqual(b.op.control_inputs, [a]) | ||||
| self.assertEqual(c.op.control_inputs, [a]) | self.assertEqual(c.op.control_inputs, [a]) | ||||
| def testNoControlDependencyWithDataDependency(self): | |||||
| g = ops.Graph() | |||||
| a = _apply_op(g, "FloatOutput", [], [dtypes.float32]) | |||||
| with g.control_dependencies([a]): | |||||
| b = _apply_op(g, "Identity", [a], [dtypes.float32]) | |||||
| self.assertEqual(b.op.control_inputs, []) | |||||
| */ | */ | ||||
| } | } | ||||
| [TestMethod] | |||||
| public void TestNoControlDependencyWithDataDependency() | |||||
| { | |||||
| var g = tf.Graph().as_default(); | |||||
| Operation b = null; | |||||
| var a = constant_op.constant(100.0); | |||||
| with(g.control_dependencies(new[] { a }), ctrl1 => | |||||
| { | |||||
| b = array_ops.identity(a); | |||||
| }); | |||||
| Assert.AreEqual(0, b.op.control_inputs.Length); | |||||
| } | |||||
| } | } | ||||
| } | } | ||||