using Microsoft.VisualStudio.TestTools.UnitTesting; using Tensorflow.NumPy; using System; using System.Collections.Generic; using System.Text; using Tensorflow; using static Tensorflow.Binding; namespace TensorFlowNET.UnitTest.Basics { [TestClass] public class SessionTest : GraphModeTestBase { [TestMethod] public void EvalTensor() { lock (this) { 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"); var sess = tf.Session(); var result = c.eval(sess); Assert.AreEqual(result[0], 6.0); } } [TestMethod] public void Eval_SmallString_Scalar() { var a = constant_op.constant("123 heythere 123 ", TF_DataType.TF_STRING); var c = tf.strings.substr(a, 4, 8); var sess = tf.Session(); var result = c.eval(sess).StringData(); Assert.AreEqual(result[0], "heythere"); } [TestMethod] public void Eval_LargeString_Scalar() { lock (this) { const int size = 30_000; var a = constant_op.constant(new string('a', size), TF_DataType.TF_STRING); var c = tf.strings.substr(a, 0, size - 5000); var sess = tf.Session(); var result = UTF8Encoding.UTF8.GetString(c.eval(sess).ToByteArray()); Console.WriteLine(result); } } [TestMethod] public void Autocast_Case0() { var sess = tf.Session().as_default(); ITensorOrOperation operation = tf.global_variables_initializer(); // the cast to ITensorOrOperation is essential for the test of this method signature var ret = sess.run(operation); } [TestMethod] public void Autocast_Case1() { var sess = tf.Session().as_default(); var input = tf.placeholder(tf.int32, shape: new Shape(6)); var op = tf.reshape(input, new int[] { 2, 3 }); sess.run(tf.global_variables_initializer()); var ret = sess.run(op, feed_dict: (input, np.array(1, 2, 3, 4, 5, 6))); Assert.AreEqual(ret.shape, (2, 3)); assertAllEqual(ret.ToArray(), new[] { 1, 2, 3, 4, 5, 6 }); print(ret.dtype); print(ret); } [TestMethod] public void Autocast_Case2() { var sess = tf.Session().as_default(); var input = tf.placeholder(tf.float32, shape: new Shape(6)); var op = tf.reshape(input, new int[] { 2, 3 }); sess.run(tf.global_variables_initializer()); var ret = sess.run(op, feed_dict: (input, np.array(1, 2, 3, 4, 5, 6).astype(np.float32) + 0.1f)); } [TestMethod, Ignore] public void Autocast_Case3() { var sess = tf.Session().as_default(); var input = tf.placeholder(tf.float32, shape: new Shape(6)); var op = tf.reshape(input, new int[] { 2, 3 }); sess.run(tf.global_variables_initializer()); var ret = sess.run(op, feed_dict: (input, np.array(1, 2, 3, 4, 5, 6).astype(np.float32) + 0.1f)); Assert.AreEqual(ret.shape, (2, 3)); Assert.AreEqual(ret, new[] { 1, 2, 3, 4, 5, 6 }); print(ret.dtype); print(ret); } [TestMethod, Ignore] public void Autocast_Case4() { var sess = tf.Session().as_default(); var input = tf.placeholder(tf.byte8, shape: new Shape(6)); var op = tf.reshape(input, new int[] { 2, 3 }); sess.run(tf.global_variables_initializer()); var ret = sess.run(op, feed_dict: (input, np.array(1, 2, 3, 4, 5, 6).astype(np.float32) + 0.1f)); Assert.AreEqual(ret.shape, (2, 3)); Assert.AreEqual(ret, new[] { 1, 2, 3, 4, 5, 6 }); print(ret.dtype); print(ret); } } }