TensorFlow.NET/test/TensorFlowNET.UnitTest/TensorTest.cs at master · mm86133/TensorFlow.NET · GitHub

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using Microsoft.VisualStudio.TestTools.UnitTesting;

using NumSharp;

using System;

using System.Linq;

using System.Runtime.InteropServices;

using System.Threading;

using FluentAssertions;

using Tensorflow;

using static Tensorflow.Binding;

using Tensorflow.Framework;

namespace TensorFlowNET.UnitTest

{

[TestClass]

public class TensorTest : CApiTest

{

[TestMethod]

public unsafe void TensorFromFixed()

{

var array = new float[1000];

var span = new Span<float>(array, 100, 500);

fixed (float* ptr = &MemoryMarshal.GetReference(span))

{

using (var t = new Tensor((IntPtr) ptr, new long[] {span.Length}, tf.float32, 4 * span.Length))

{

Assert.IsFalse(t.IsDisposed);

Assert.AreEqual(2000, (int) t.bytesize);

}

fixed (float* ptr = &array[0])

{

using (var t = new Tensor((IntPtr) ptr, new long[] {array.Length}, tf.float32, 4 * array.Length))

{

Assert.IsFalse(t.IsDisposed);

Assert.AreEqual(4000, (int) t.bytesize);

}

[TestMethod]

public unsafe void TensorFromArray()

{

var array = new float[1000];

using (var t = new Tensor(array, new long[] {array.Length}, tf.float32))

{

Assert.IsFalse(t.IsDisposed);

Assert.AreEqual(1000 * sizeof(float), (int) t.bytesize);

}

using (var t = new Tensor(new float[] {1}, new long[] {1}, tf.float32))

{

Assert.IsFalse(t.IsDisposed);

Assert.AreEqual(1 * sizeof(float), (int) t.bytesize);

}

using (var t = new Tensor(new float[] {1}, null, tf.float32))

{

Assert.IsFalse(t.IsDisposed);

Assert.AreEqual(1 * sizeof(float), (int) t.bytesize);

t.shape.Should().BeEmpty();

}

[TestMethod]

public void AllocateTensor()

{

ulong num_bytes = 6 * sizeof(float);

long[] dims = {2, 3};

Tensor t = c_api.TF_AllocateTensor(TF_DataType.TF_FLOAT, dims, 2, num_bytes);

EXPECT_EQ(TF_DataType.TF_FLOAT, t.dtype);

EXPECT_EQ(2, t.NDims);

EXPECT_EQ((int) dims[0], t.shape[0]);

EXPECT_EQ(num_bytes, t.bytesize);

t.Dispose();

}

/// <summary>

/// Port from c_api_test.cc

/// `TEST(CAPI, MaybeMove)`

/// </summary>

[TestMethod]

public void MaybeMove()

{

NDArray nd = np.array(2, 3);

Tensor t = new Tensor(nd);

Tensor o = t.MaybeMove();

ASSERT_TRUE(o == IntPtr.Zero); // It is unsafe to move memory TF might not own.

t.Dispose();

}

/// <summary>

/// Port from c_api_test.cc

/// `TEST(CAPI, Tensor)`

/// </summary>

[TestMethod]

public void Tensor()

{

var nd = np.array(1f, 2f, 3f, 4f, 5f, 6f).reshape(2, 3);

var tensor = new Tensor(nd);

var array = tensor.ToArray<float>();

EXPECT_EQ(tensor.dtype, TF_DataType.TF_FLOAT);

EXPECT_EQ(tensor.rank, nd.ndim);

EXPECT_EQ((int) tensor.shape[0], nd.shape[0]);

EXPECT_EQ((int) tensor.shape[1], nd.shape[1]);

EXPECT_EQ(tensor.bytesize, (ulong) nd.size * sizeof(float));

Assert.IsTrue(Enumerable.SequenceEqual(nd.Data<float>(), new float[] {1, 2, 3, 4, 5, 6}));

}

/// <summary>

/// Port from tensorflow\c\c_api_test.cc

/// `TEST(CAPI, SetShape)`

/// </summary>

[TestMethod]

public void SetShape()

{

var s = new Status();

var graph = new Graph().as_default();

var feed = c_test_util.Placeholder(graph, s);

var feed_out_0 = new TF_Output(feed, 0);

// Fetch the shape, it should be completely unknown.

int num_dims = c_api.TF_GraphGetTensorNumDims(graph, feed_out_0, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

EXPECT_EQ(-1, num_dims);

// Set the shape to be unknown, expect no change.

c_api.TF_GraphSetTensorShape(graph, feed_out_0, null, -1, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

num_dims = c_api.TF_GraphGetTensorNumDims(graph, feed_out_0, s);

EXPECT_EQ(-1, num_dims);

// Set the shape to be 2 x Unknown

long[] dims = {2, -1};

c_api.TF_GraphSetTensorShape(graph, feed_out_0, dims, dims.Length, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

num_dims = c_api.TF_GraphGetTensorNumDims(graph, feed_out_0, s);

EXPECT_EQ(2, num_dims);

// Get the dimension vector appropriately.

var returned_dims = new long[dims.Length];

c_api.TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

Assert.IsTrue(Enumerable.SequenceEqual(dims, returned_dims));

// Set to a new valid shape: [2, 3]

dims[1] = 3;

c_api.TF_GraphSetTensorShape(graph, feed_out_0, dims, dims.Length, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

// Fetch and see that the new value is returned.

c_api.TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

Assert.IsTrue(Enumerable.SequenceEqual(dims, returned_dims));

// Try to set 'unknown' with unknown rank on the shape and see that

// it doesn't change.

c_api.TF_GraphSetTensorShape(graph, feed_out_0, null, -1, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

c_api.TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

EXPECT_EQ(2, num_dims);

EXPECT_EQ(2, (int) returned_dims[0]);

EXPECT_EQ(3, (int) returned_dims[1]);

// Try to set 'unknown' with same rank on the shape and see that

// it doesn't change.

dims[0] = -1;

dims[1] = -1;

c_api.TF_GraphSetTensorShape(graph, feed_out_0, dims, 2, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

c_api.TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

EXPECT_EQ(2, num_dims);

EXPECT_EQ(2, (int) returned_dims[0]);

EXPECT_EQ(3, (int) returned_dims[1]);

// Try to fetch a shape with the wrong num_dims

c_api.TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, 5, s);

Assert.IsTrue(s.Code == TF_Code.TF_INVALID_ARGUMENT);

// Try to set an invalid shape (cannot change 2x3 to a 2x5).

dims[1] = 5;

c_api.TF_GraphSetTensorShape(graph, feed_out_0, dims, 2, s);

Assert.IsTrue(s.Code == TF_Code.TF_INVALID_ARGUMENT);

// Test for a scalar.

var three = c_test_util.ScalarConst(3, graph, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

var three_out_0 = new TF_Output(three, 0);

num_dims = c_api.TF_GraphGetTensorNumDims(graph, three_out_0, s);

Assert.IsTrue(s.Code == TF_Code.TF_OK);

EXPECT_EQ(0, num_dims);

c_api.TF_GraphGetTensorShape(graph, feed_out_0, null, num_dims, s);

//Assert.IsTrue(s.Code == TF_Code.TF_OK);

// graph.Dispose();

s.Dispose();

}

[TestMethod]

public void sparse_to_dense()

{

var indices = tf.reshape(tf.range(0, 5), new int[] { 5, 1 });

var labels = tf.expand_dims(tf.constant(new[] { 0, 1, 2, 3, 4 }),1);

var st = tf.concat(values: new[] { indices, labels }, axis: 1);

var onehot = tf.sparse_to_dense(st, (5, 5), 1);

using (var sess = tf.Session())

{

var result = sess.run(onehot);

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 1, 0, 0, 0, 0 }, result[0].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 1, 0, 0, 0 }, result[1].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 0, 1, 0, 0 }, result[2].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 0, 0, 1, 0 }, result[3].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 0, 0, 0, 1 }, result[4].ToArray<int>()));

};

}

[TestMethod]

public void sparse_tensor_to_dense()

{

var decoded_list = tf.SparseTensor(new[,]

{

{ 0L, 0L },

{ 1L, 2L }

new int[] { 1, 2 },

new[] { 3L, 4L });

var onehot = tf.sparse_tensor_to_dense(decoded_list);

using (var sess = tf.Session())

{

var result = sess.run(onehot);

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 1, 0, 0, 0 }, result[0].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 0, 2, 0 }, result[1].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 0, 0, 0 }, result[2].ToArray<int>()));

}

[TestMethod]

public void batch_to_space_nd()

{

var inputs = np.arange(24).reshape(4, 2, 3);

var block_shape = new[] { 2, 2 };

int[,] crops = { { 0, 0 }, { 0, 0 } };

var tensor = tf.batch_to_space_nd(inputs, block_shape, crops);

using (var sess = tf.Session())

{

var result = sess.run(tensor);

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 6, 1, 7, 2, 8 }, result[0, 0].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 12, 18, 13, 19, 14, 20 }, result[0, 1].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 3, 9, 4, 10, 5, 11 }, result[0, 2].ToArray<int>()));

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 15, 21, 16, 22, 17, 23 }, result[0, 3].ToArray<int>()));

}

[TestMethod]

public void boolean_mask()

{

var tensor = new[] { 0, 1, 2, 3 };

var mask = np.array(new[] { true, false, true, false });

var masked = tf.boolean_mask(tensor, mask);

using (var sess = tf.Session())

{

var result = sess.run(masked);

Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 2 }, result.ToArray<int>()));

}

TensorFlow.NET/test/TensorFlowNET.UnitTest/TensorTest.cs at master · mm86133/TensorFlow.NET · GitHub

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