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]);
}
}
}
}