using Microsoft.VisualStudio.TestTools.UnitTesting; using NumSharp; using System; using System.Collections.Generic; using Tensorflow; using static Tensorflow.Binding; namespace TensorFlowNET.UnitTest { [TestClass] public class SessionTest : CApiTest { /// /// tensorflow\c\c_api_test.cc /// `TEST(CAPI, Session)` /// [TestMethod] public void Session() { var s = new Status(); var graph = new Graph(); // Make a placeholder operation. var feed = c_test_util.Placeholder(graph, s); // Make a constant operation with the scalar "2". var two = c_test_util.ScalarConst(2, graph, s); // Add operation. var add = c_test_util.Add(feed, two, graph, s); var csession = new CSession(graph, s); ASSERT_EQ(TF_Code.TF_OK, s.Code); // Run the graph. var inputs = new Dictionary(); inputs.Add(feed, new Tensor(3)); csession.SetInputs(inputs); var outputs = new TF_Output[] { new TF_Output(add, 0) }; csession.SetOutputs(outputs); csession.Run(s); Tensor outTensor = csession.output_tensor(0); EXPECT_EQ(TF_DataType.TF_INT32, outTensor.dtype); EXPECT_EQ(0, outTensor.NDims); ASSERT_EQ((ulong)sizeof(uint), outTensor.bytesize); var output_contents = outTensor.ToArray(); EXPECT_EQ(3 + 2, output_contents[0]); // Add another operation to the graph. var neg = c_test_util.Neg(add, graph, s); ASSERT_EQ(TF_Code.TF_OK, s.Code); // Run up to the new operation. inputs = new Dictionary(); inputs.Add(feed, new Tensor(7)); csession.SetInputs(inputs); outputs = new TF_Output[] { new TF_Output(neg, 0) }; csession.SetOutputs(outputs); csession.Run(s); ASSERT_EQ(TF_Code.TF_OK, s.Code); outTensor = csession.output_tensor(0); ASSERT_TRUE(outTensor != IntPtr.Zero); EXPECT_EQ(TF_DataType.TF_INT32, outTensor.dtype); EXPECT_EQ(0, outTensor.NDims); // scalar ASSERT_EQ((ulong)sizeof(uint), outTensor.bytesize); output_contents = outTensor.ToArray(); EXPECT_EQ(-(7 + 2), output_contents[0]); // Clean up csession.CloseAndDelete(s); ASSERT_EQ(TF_Code.TF_OK, s.Code); } [TestMethod] public void EvalTensor() { var a = constant_op.constant(np.array(3.0).reshape(1, 1)); var b = constant_op.constant(np.array(2.0).reshape(1, 1)); var c = math_ops.matmul(a, b, name: "matmul"); using (var sess = tf.Session()) { var result = c.eval(sess); Assert.AreEqual(6, result.Data()[0]); } } } }