Created additional tests for the tensor code.

7 files changed, 406 insertions, 30 deletions

diff --git a/unsupported/test/CMakeLists.txt b/unsupported/test/CMakeLists.txt
index abc3375e5..d6072c9f3 100644
--- a/unsupported/test/CMakeLists.txt
+++ b/unsupported/test/CMakeLists.txt
@@ -102,6 +102,8 @@ if(EIGEN_TEST_CXX11)
   ei_add_test(cxx11_tensor_simple "-std=c++0x")
   ei_add_test(cxx11_tensor_symmetry "-std=c++0x")
   ei_add_test(cxx11_tensor_assign "-std=c++0x")
+  ei_add_test(cxx11_tensor_comparison "-std=c++0x")
+  ei_add_test(cxx11_tensor_contraction "-std=c++0x")
   ei_add_test(cxx11_tensor_expr "-std=c++0x")
   ei_add_test(cxx11_tensor_map "-std=c++0x")
   ei_add_test(cxx11_tensor_device  "-std=c++0x")
diff --git a/unsupported/test/cxx11_tensor_comparisons.cpp b/unsupported/test/cxx11_tensor_comparisons.cpp
new file mode 100644
index 000000000..186f56ac3
--- /dev/null
+++ b/unsupported/test/cxx11_tensor_comparisons.cpp
@@ -0,0 +1,84 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_orderings()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<bool, 3> lt(2,3,7);
+  Tensor<bool, 3> le(2,3,7);
+  Tensor<bool, 3> gt(2,3,7);
+  Tensor<bool, 3> ge(2,3,7);
+
+  mat1.setRandom();
+  mat2.setRandom();
+
+  lt = mat1 < mat2;
+  le = mat1 <= mat2;
+  gt = mat1 > mat2;
+  ge = mat1 >= mat2;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(lt(i,j,k), mat1(i,j,k) < mat2(i,j,k));
+        VERIFY_IS_EQUAL(le(i,j,k), mat1(i,j,k) <= mat2(i,j,k));
+        VERIFY_IS_EQUAL(gt(i,j,k), mat1(i,j,k) > mat2(i,j,k));
+        VERIFY_IS_EQUAL(ge(i,j,k), mat1(i,j,k) >= mat2(i,j,k));
+      }
+    }
+  }
+}
+
+
+static void test_equality()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+
+  mat1.setRandom();
+  mat2.setRandom();
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        if (random() < 0.5) {
+          mat2(i,j,k) = mat1(i,j,k);
+        }
+      }
+    }
+  }
+
+  Tensor<bool, 3> eq(2,3,7);
+  Tensor<bool, 3> ne(2,3,7);
+  eq = (mat1 == mat2);
+  ne = (mat1 != mat2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(eq(i,j,k), mat1(i,j,k) == mat2(i,j,k));
+        VERIFY_IS_EQUAL(ne(i,j,k), mat1(i,j,k) != mat2(i,j,k));
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_comparisons()
+{
+  CALL_SUBTEST(test_orderings());
+  CALL_SUBTEST(test_equality());
+}
diff --git a/unsupported/test/cxx11_tensor_contraction.cpp b/unsupported/test/cxx11_tensor_contraction.cpp
new file mode 100644
index 000000000..1c89dfdd1
--- /dev/null
+++ b/unsupported/test/cxx11_tensor_contraction.cpp
@@ -0,0 +1,163 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+typedef Tensor<float, 1>::DimensionPair DimPair;
+
+
+static void test_evals()
+{
+  Tensor<float, 2> mat1(2, 3);
+  Tensor<float, 2> mat2(2, 3);
+  Tensor<float, 2> mat3(3, 2);
+
+  mat1.setRandom();
+  mat2.setRandom();
+  mat3.setRandom();
+
+  Tensor<float, 2> mat4(3,3);
+  mat4.setZero();
+  Eigen::array<DimPair, 1> dims3({{DimPair(0, 0)}});
+  TensorEvaluator<decltype(mat1.contract(mat2, dims3))> eval(mat1.contract(mat2, dims3));
+  eval.evalTo(mat4.data());
+  EIGEN_STATIC_ASSERT(TensorEvaluator<decltype(mat1.contract(mat2, dims3))>::NumDims==2ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval.dimensions()[0], 3);
+  VERIFY_IS_EQUAL(eval.dimensions()[1], 3);
+
+  VERIFY_IS_APPROX(mat4(0,0), mat1(0,0)*mat2(0,0) + mat1(1,0)*mat2(1,0));
+  VERIFY_IS_APPROX(mat4(0,1), mat1(0,0)*mat2(0,1) + mat1(1,0)*mat2(1,1));
+  VERIFY_IS_APPROX(mat4(0,2), mat1(0,0)*mat2(0,2) + mat1(1,0)*mat2(1,2));
+  VERIFY_IS_APPROX(mat4(1,0), mat1(0,1)*mat2(0,0) + mat1(1,1)*mat2(1,0));
+  VERIFY_IS_APPROX(mat4(1,1), mat1(0,1)*mat2(0,1) + mat1(1,1)*mat2(1,1));
+  VERIFY_IS_APPROX(mat4(1,2), mat1(0,1)*mat2(0,2) + mat1(1,1)*mat2(1,2));
+  VERIFY_IS_APPROX(mat4(2,0), mat1(0,2)*mat2(0,0) + mat1(1,2)*mat2(1,0));
+  VERIFY_IS_APPROX(mat4(2,1), mat1(0,2)*mat2(0,1) + mat1(1,2)*mat2(1,1));
+  VERIFY_IS_APPROX(mat4(2,2), mat1(0,2)*mat2(0,2) + mat1(1,2)*mat2(1,2));
+
+  Tensor<float, 2> mat5(2,2);
+  mat5.setZero();
+  Eigen::array<DimPair, 1> dims4({{DimPair(1, 1)}});
+  TensorEvaluator<decltype(mat1.contract(mat2, dims4))> eval2(mat1.contract(mat2, dims4));
+  eval2.evalTo(mat5.data());
+  EIGEN_STATIC_ASSERT(TensorEvaluator<decltype(mat1.contract(mat2, dims4))>::NumDims==2ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval2.dimensions()[0], 2);
+  VERIFY_IS_EQUAL(eval2.dimensions()[1], 2);
+
+  VERIFY_IS_APPROX(mat5(0,0), mat1(0,0)*mat2(0,0) + mat1(0,1)*mat2(0,1) + mat1(0,2)*mat2(0,2));
+  VERIFY_IS_APPROX(mat5(0,1), mat1(0,0)*mat2(1,0) + mat1(0,1)*mat2(1,1) + mat1(0,2)*mat2(1,2));
+  VERIFY_IS_APPROX(mat5(1,0), mat1(1,0)*mat2(0,0) + mat1(1,1)*mat2(0,1) + mat1(1,2)*mat2(0,2));
+  VERIFY_IS_APPROX(mat5(1,1), mat1(1,0)*mat2(1,0) + mat1(1,1)*mat2(1,1) + mat1(1,2)*mat2(1,2));
+
+  Tensor<float, 2> mat6(2,2);
+  mat6.setZero();
+  Eigen::array<DimPair, 1> dims6({{DimPair(1, 0)}});
+  TensorEvaluator<decltype(mat1.contract(mat3, dims6))> eval3(mat1.contract(mat3, dims6));
+  eval3.evalTo(mat6.data());
+  EIGEN_STATIC_ASSERT(TensorEvaluator<decltype(mat1.contract(mat3, dims6))>::NumDims==2ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval3.dimensions()[0], 2);
+  VERIFY_IS_EQUAL(eval3.dimensions()[1], 2);
+
+  VERIFY_IS_APPROX(mat6(0,0), mat1(0,0)*mat3(0,0) + mat1(0,1)*mat3(1,0) + mat1(0,2)*mat3(2,0));
+  VERIFY_IS_APPROX(mat6(0,1), mat1(0,0)*mat3(0,1) + mat1(0,1)*mat3(1,1) + mat1(0,2)*mat3(2,1));
+  VERIFY_IS_APPROX(mat6(1,0), mat1(1,0)*mat3(0,0) + mat1(1,1)*mat3(1,0) + mat1(1,2)*mat3(2,0));
+  VERIFY_IS_APPROX(mat6(1,1), mat1(1,0)*mat3(0,1) + mat1(1,1)*mat3(1,1) + mat1(1,2)*mat3(2,1));
+}
+
+
+static void test_scalar()
+{
+  Tensor<float, 1> vec1({6});
+  Tensor<float, 1> vec2({6});
+
+  vec1.setRandom();
+  vec2.setRandom();
+
+  Tensor<float, 1> scalar(1);
+  scalar.setZero();
+  Eigen::array<DimPair, 1> dims({{DimPair(0, 0)}});
+  TensorEvaluator<decltype(vec1.contract(vec2, dims))> eval(vec1.contract(vec2, dims));
+  eval.evalTo(scalar.data());
+  EIGEN_STATIC_ASSERT(TensorEvaluator<decltype(vec1.contract(vec2, dims))>::NumDims==1ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  float expected = 0.0f;
+  for (int i = 0; i < 6; ++i) {
+    expected += vec1(i) * vec2(i);
+  }
+  VERIFY_IS_APPROX(scalar(0), expected);
+}
+
+
+static void test_multidims()
+{
+  Tensor<float, 3> mat1(2, 2, 2);
+  Tensor<float, 4> mat2(2, 2, 2, 2);
+
+  mat1.setRandom();
+  mat2.setRandom();
+
+  Tensor<float, 3> mat3(2, 2, 2);
+  mat3.setZero();
+  Eigen::array<DimPair, 2> dims({{DimPair(1, 2), DimPair(2, 3)}});
+  TensorEvaluator<decltype(mat1.contract(mat2, dims))> eval(mat1.contract(mat2, dims));
+  eval.evalTo(mat3.data());
+  EIGEN_STATIC_ASSERT(TensorEvaluator<decltype(mat1.contract(mat2, dims))>::NumDims==3ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval.dimensions()[0], 2);
+  VERIFY_IS_EQUAL(eval.dimensions()[1], 2);
+  VERIFY_IS_EQUAL(eval.dimensions()[2], 2);
+
+  VERIFY_IS_APPROX(mat3(0,0,0), mat1(0,0,0)*mat2(0,0,0,0) + mat1(0,1,0)*mat2(0,0,1,0) +
+                                mat1(0,0,1)*mat2(0,0,0,1) + mat1(0,1,1)*mat2(0,0,1,1));
+  VERIFY_IS_APPROX(mat3(0,0,1), mat1(0,0,0)*mat2(0,1,0,0) + mat1(0,1,0)*mat2(0,1,1,0) +
+                                mat1(0,0,1)*mat2(0,1,0,1) + mat1(0,1,1)*mat2(0,1,1,1));
+  VERIFY_IS_APPROX(mat3(0,1,0), mat1(0,0,0)*mat2(1,0,0,0) + mat1(0,1,0)*mat2(1,0,1,0) +
+                                mat1(0,0,1)*mat2(1,0,0,1) + mat1(0,1,1)*mat2(1,0,1,1));
+  VERIFY_IS_APPROX(mat3(0,1,1), mat1(0,0,0)*mat2(1,1,0,0) + mat1(0,1,0)*mat2(1,1,1,0) +
+                                mat1(0,0,1)*mat2(1,1,0,1) + mat1(0,1,1)*mat2(1,1,1,1));
+  VERIFY_IS_APPROX(mat3(1,0,0), mat1(1,0,0)*mat2(0,0,0,0) + mat1(1,1,0)*mat2(0,0,1,0) +
+                                mat1(1,0,1)*mat2(0,0,0,1) + mat1(1,1,1)*mat2(0,0,1,1));
+  VERIFY_IS_APPROX(mat3(1,0,1), mat1(1,0,0)*mat2(0,1,0,0) + mat1(1,1,0)*mat2(0,1,1,0) +
+                                mat1(1,0,1)*mat2(0,1,0,1) + mat1(1,1,1)*mat2(0,1,1,1));
+  VERIFY_IS_APPROX(mat3(1,1,0), mat1(1,0,0)*mat2(1,0,0,0) + mat1(1,1,0)*mat2(1,0,1,0) +
+                                mat1(1,0,1)*mat2(1,0,0,1) + mat1(1,1,1)*mat2(1,0,1,1));
+  VERIFY_IS_APPROX(mat3(1,1,1), mat1(1,0,0)*mat2(1,1,0,0) + mat1(1,1,0)*mat2(1,1,1,0) +
+                                mat1(1,0,1)*mat2(1,1,0,1) + mat1(1,1,1)*mat2(1,1,1,1));
+}
+
+
+static void test_expr()
+{
+  Tensor<float, 2> mat1(2, 3);
+  Tensor<float, 2> mat2(3, 2);
+  mat1.setRandom();
+  mat2.setRandom();
+
+  Tensor<float, 2> mat3(2,2);
+
+  Eigen::array<DimPair, 1> dims({{DimPair(1, 0)}});
+  mat3 = mat1.contract(mat2, dims);
+
+  VERIFY_IS_APPROX(mat3(0,0), mat1(0,0)*mat2(0,0) + mat1(0,1)*mat2(1,0) + mat1(0,2)*mat2(2,0));
+  VERIFY_IS_APPROX(mat3(0,1), mat1(0,0)*mat2(0,1) + mat1(0,1)*mat2(1,1) + mat1(0,2)*mat2(2,1));
+  VERIFY_IS_APPROX(mat3(1,0), mat1(1,0)*mat2(0,0) + mat1(1,1)*mat2(1,0) + mat1(1,2)*mat2(2,0));
+  VERIFY_IS_APPROX(mat3(1,1), mat1(1,0)*mat2(0,1) + mat1(1,1)*mat2(1,1) + mat1(1,2)*mat2(2,1));
+}
+
+
+void test_cxx11_tensor_contraction()
+{
+  CALL_SUBTEST(test_evals());
+  CALL_SUBTEST(test_scalar());
+  CALL_SUBTEST(test_multidims());
+  CALL_SUBTEST(test_expr());
+}
diff --git a/unsupported/test/cxx11_tensor_device.cpp b/unsupported/test/cxx11_tensor_device.cpp
index 9eb1d0420..365b109c7 100644
--- a/unsupported/test/cxx11_tensor_device.cpp
+++ b/unsupported/test/cxx11_tensor_device.cpp
@@ -15,7 +15,7 @@
 
 
 #include "main.h"
-#include <Eigen/CXX11/Tensor>
+#include <unsupported/Eigen/CXX11/Tensor>
 
 using Eigen::Tensor;
 using Eigen::RowMajor;
@@ -39,8 +39,12 @@ struct CPUContext {
 
 // Context for evaluation on GPU
 struct GPUContext {
-  GPUContext(const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in1, Eigen::TensorMap<Eigen::Tensor<float, 3> >& in2, Eigen::TensorMap<Eigen::Tensor<float, 3> >& out) : in1_(in1), in2_(in2), out_(out) { }
-
+  GPUContext(const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in1, Eigen::TensorMap<Eigen::Tensor<float, 3> >& in2, Eigen::TensorMap<Eigen::Tensor<float, 3> >& out) : in1_(in1), in2_(in2), out_(out), gpu_device_(&stream_) {
+    cudaStreamCreate(&stream_);
+  }
+  ~GPUContext() {
+    cudaStreamDestroy(stream_);
+  }
   const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in1() const { return in1_; }
   const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in2() const { return in2_; }
   Eigen::TensorDevice<Eigen::TensorMap<Eigen::Tensor<float, 3> >, Eigen::GpuDevice> out() { return TensorDevice<Eigen::TensorMap<Eigen::Tensor<float, 3> >, Eigen::GpuDevice>(gpu_device_, out_); }
@@ -49,6 +53,7 @@ struct GPUContext {
   const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in1_;
   const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in2_;
   Eigen::TensorMap<Eigen::Tensor<float, 3> >& out_;
+  cudaStream_t stream_;
   Eigen::GpuDevice gpu_device_;
 };
 
@@ -57,7 +62,7 @@ struct GPUContext {
 template <typename Context>
 static void test_contextual_eval(Context* context)
 {
-  context->out() = context->in1() + context->in2() * 3.14f;
+  context->out() = context->in1() + context->in2() * 3.14f + context->in1().constant(2.718f);
 }
 
 static void test_cpu() {
@@ -73,7 +78,7 @@ static void test_cpu() {
   for (int i = 0; i < 2; ++i) {
     for (int j = 0; j < 3; ++j) {
       for (int k = 0; k < 7; ++k) {
-        VERIFY_IS_APPROX(out(Eigen::array<int, 3>(i,j,k)), in1(Eigen::array<int, 3>(i,j,k)) + in2(Eigen::array<int, 3>(i,j,k)) * 3.14f);
+        VERIFY_IS_APPROX(out(Eigen::array<int, 3>(i,j,k)), in1(Eigen::array<int, 3>(i,j,k)) + in2(Eigen::array<int, 3>(i,j,k)) * 3.14f + 2.718f);
       }
     }
   }
@@ -111,7 +116,7 @@ static void test_gpu() {
   for (int i = 0; i < 2; ++i) {
     for (int j = 0; j < 3; ++j) {
       for (int k = 0; k < 7; ++k) {
-        VERIFY_IS_APPROX(out(Eigen::array<int, 3>(i,j,k)), in1(Eigen::array<int, 3>(i,j,k)) + in2(Eigen::array<int, 3>(i,j,k)) * 3.14f);
+        VERIFY_IS_APPROX(out(Eigen::array<int, 3>(i,j,k)), in1(Eigen::array<int, 3>(i,j,k)) + in2(Eigen::array<int, 3>(i,j,k)) * 3.14f + 2.718f);
       }
     }
   }
diff --git a/unsupported/test/cxx11_tensor_expr.cpp b/unsupported/test/cxx11_tensor_expr.cpp
index e0124da8c..e85fcbfa9 100644
--- a/unsupported/test/cxx11_tensor_expr.cpp
+++ b/unsupported/test/cxx11_tensor_expr.cpp
@@ -28,10 +28,10 @@ static void test_1d()
 
   float data3[6];
   TensorMap<Tensor<float, 1>> vec3(data3, 6);
-  vec3 = vec1.cwiseSqrt();
+  vec3 = vec1.sqrt();
   float data4[6];
   TensorMap<Tensor<float, 1, RowMajor>> vec4(data4, 6);
-  vec4 = vec2.cwiseSqrt();
+  vec4 = vec2.square();
 
   VERIFY_IS_APPROX(vec3(0), sqrtf(4.0));
   VERIFY_IS_APPROX(vec3(1), sqrtf(8.0));
@@ -40,12 +40,12 @@ static void test_1d()
   VERIFY_IS_APPROX(vec3(4), sqrtf(23.0));
   VERIFY_IS_APPROX(vec3(5), sqrtf(42.0));
 
-  VERIFY_IS_APPROX(vec4(0), sqrtf(0.0));
-  VERIFY_IS_APPROX(vec4(1), sqrtf(1.0));
-  VERIFY_IS_APPROX(vec4(2), sqrtf(2.0));
-  VERIFY_IS_APPROX(vec4(3), sqrtf(3.0));
-  VERIFY_IS_APPROX(vec4(4), sqrtf(4.0));
-  VERIFY_IS_APPROX(vec4(5), sqrtf(5.0));
+  VERIFY_IS_APPROX(vec4(0), 0.0f);
+  VERIFY_IS_APPROX(vec4(1), 1.0f);
+  VERIFY_IS_APPROX(vec4(2), 2.0f * 2.0f);
+  VERIFY_IS_APPROX(vec4(3), 3.0f * 3.0f);
+  VERIFY_IS_APPROX(vec4(4), 4.0f * 4.0f);
+  VERIFY_IS_APPROX(vec4(5), 5.0f * 5.0f);
 
   vec3 = vec1 + vec2;
   VERIFY_IS_APPROX(vec3(0), 4.0f + 0.0f);
@@ -79,8 +79,8 @@ static void test_2d()
 
   Tensor<float, 2> mat3(2,3);
   Tensor<float, 2, RowMajor> mat4(2,3);
-  mat3 = mat1.cwiseAbs();
-  mat4 = mat2.cwiseAbs();
+  mat3 = mat1.abs();
+  mat4 = mat2.abs();
 
   VERIFY_IS_APPROX(mat3(0,0), 0.0f);
   VERIFY_IS_APPROX(mat3(0,1), 1.0f);
@@ -102,7 +102,7 @@ static void test_3d()
   Tensor<float, 3> mat1(2,3,7);
   Tensor<float, 3, RowMajor> mat2(2,3,7);
 
-  float val = 0.0;
+  float val = 1.0;
   for (int i = 0; i < 2; ++i) {
     for (int j = 0; j < 3; ++j) {
       for (int k = 0; k < 7; ++k) {
@@ -118,28 +118,147 @@ static void test_3d()
   Tensor<float, 3, RowMajor> mat4(2,3,7);
   mat4 = mat2 * 3.14f;
   Tensor<float, 3> mat5(2,3,7);
-  mat5 = mat1.cwiseSqrt().cwiseSqrt();
+  mat5 = mat1.inverse().log();
   Tensor<float, 3, RowMajor> mat6(2,3,7);
-  mat6 = mat2.cwiseSqrt() * 3.14f;
+  mat6 = mat2.pow(0.5f) * 3.14f;
+  Tensor<float, 3> mat7(2,3,7);
+  mat7 = mat1.cwiseMax(mat5 * 2.0f).exp();
+  Tensor<float, 3, RowMajor> mat8(2,3,7);
+  mat8 = (-mat2).exp() * 3.14f;
 
-  val = 0.0;
+  val = 1.0;
   for (int i = 0; i < 2; ++i) {
     for (int j = 0; j < 3; ++j) {
       for (int k = 0; k < 7; ++k) {
         VERIFY_IS_APPROX(mat3(i,j,k), val + val);
         VERIFY_IS_APPROX(mat4(i,j,k), val * 3.14f);
-        VERIFY_IS_APPROX(mat5(i,j,k), sqrtf(sqrtf(val)));
+        VERIFY_IS_APPROX(mat5(i,j,k), logf(1.0f/val));
         VERIFY_IS_APPROX(mat6(i,j,k), sqrtf(val) * 3.14f);
+        VERIFY_IS_APPROX(mat7(i,j,k), expf((std::max)(val, mat5(i,j,k) * 2.0f)));
+        VERIFY_IS_APPROX(mat8(i,j,k), expf(-val) * 3.14f);
         val += 1.0;
       }
     }
   }
 }
 
+static void test_constants()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<float, 3> mat3(2,3,7);
+
+  float val = 1.0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        val += 1.0;
+      }
+    }
+  }
+  mat2 = mat1.constant(3.14f);
+  mat3 = mat1.cwiseMax(7.3f).exp();
+
+  val = 1.0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat2(i,j,k), 3.14f);
+        VERIFY_IS_APPROX(mat3(i,j,k), expf((std::max)(val, 7.3f)));
+        val += 1.0;
+      }
+    }
+  }
+}
+
+
+static void test_functors()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<float, 3> mat3(2,3,7);
+
+  float val = 1.0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        val += 1.0;
+      }
+    }
+  }
+  mat2 = mat1.inverse().unaryExpr(&asinf);
+  mat3 = mat1.unaryExpr(&tanhf);
+
+  val = 1.0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat2(i,j,k), asinf(1.0f / mat1(i,j,k)));
+        VERIFY_IS_APPROX(mat3(i,j,k), tanhf(mat1(i,j,k)));
+        val += 1.0;
+      }
+    }
+  }
+}
+
+static void test_type_casting()
+{
+  Tensor<bool, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<double, 3> mat3(2,3,7);
+  mat1.setRandom();
+  mat2.setRandom();
+
+  mat3 = mat1.template cast<double>();
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat3(i,j,k), mat1(i,j,k) ? 1.0 : 0.0);
+      }
+    }
+  }
+
+  mat3 = mat2.template cast<double>();
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat3(i,j,k), static_cast<double>(mat2(i,j,k)));
+      }
+    }
+  }
+}
+
+static void test_select()
+{
+  Tensor<float, 3> selector(2,3,7);
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<float, 3> result(2,3,7);
+
+  selector.setRandom();
+  mat1.setRandom();
+  mat2.setRandom();
+  result = (selector > selector.constant(0.5f)).select(mat1, mat2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(result(i,j,k), (selector(i,j,k) > 0.5f) ? mat1(i,j,k) : mat2(i,j,k));
+      }
+    }
+  }
+}
+
 
 void test_cxx11_tensor_expr()
 {
   CALL_SUBTEST(test_1d());
   CALL_SUBTEST(test_2d());
   CALL_SUBTEST(test_3d());
+  CALL_SUBTEST(test_constants());
+  CALL_SUBTEST(test_functors());
+  CALL_SUBTEST(test_type_casting());
+  CALL_SUBTEST(test_select());
 }
diff --git a/unsupported/test/cxx11_tensor_fixed_size.cpp b/unsupported/test/cxx11_tensor_fixed_size.cpp
index 214f6951d..d270486f2 100644
--- a/unsupported/test/cxx11_tensor_fixed_size.cpp
+++ b/unsupported/test/cxx11_tensor_fixed_size.cpp
@@ -33,10 +33,10 @@ static void test_1d()
 
   float data3[6];
   TensorMap<TensorFixedSize<float, Sizes<6> > > vec3(data3, 6);
-  vec3 = vec1.cwiseSqrt();
+  vec3 = vec1.sqrt();
   float data4[6];
   TensorMap<TensorFixedSize<float, Sizes<6>, RowMajor> > vec4(data4, 6);
-  vec4 = vec2.cwiseSqrt();
+  vec4 = vec2.sqrt();
 
   VERIFY_IS_EQUAL((vec3.size()), 6);
   //  VERIFY_IS_EQUAL((vec3.dimensions()[0]), 6);
@@ -92,8 +92,8 @@ static void test_2d()
 
   TensorFixedSize<float, Sizes<2, 3>> mat3;
   TensorFixedSize<float, Sizes<2, 3>, RowMajor> mat4;
-  mat3 = mat1.cwiseAbs();
-  mat4 = mat2.cwiseAbs();
+  mat3 = mat1.abs();
+  mat4 = mat2.abs();
 
   VERIFY_IS_EQUAL((mat3.size()), 2*3);
     //  VERIFY_IS_EQUAL((mat3.dimension(0)), 2);
@@ -136,9 +136,9 @@ static void test_3d()
   }
 
   TensorFixedSize<float, Sizes<2, 3, 7> > mat3;
-  mat3 = mat1.cwiseSqrt();
+  mat3 = mat1.sqrt();
   TensorFixedSize<float, Sizes<2, 3, 7>, RowMajor> mat4;
-  mat4 = mat2.cwiseSqrt();
+  mat4 = mat2.sqrt();
 
   VERIFY_IS_EQUAL((mat3.size()), 2*3*7);
   //  VERIFY_IS_EQUAL((mat3.dimension(0)), 2);
@@ -173,7 +173,7 @@ static void test_array()
   }
 
   TensorFixedSize<float, Sizes<2, 3, 7> > mat3;
-  mat3 = mat1.cwisePow(3.5f);
+  mat3 = mat1.pow(3.5f);
 
   val = 0.0;
   for (int i = 0; i < 2; ++i) {
diff --git a/unsupported/test/cxx11_tensor_thread_pool.cpp b/unsupported/test/cxx11_tensor_thread_pool.cpp
index c9de71da3..b371e8a71 100644
--- a/unsupported/test/cxx11_tensor_thread_pool.cpp
+++ b/unsupported/test/cxx11_tensor_thread_pool.cpp
@@ -12,6 +12,7 @@
 
 #include "main.h"
 #include <Eigen/CXX11/Tensor>
+#include "thread/threadpool.h"
 
 using Eigen::Tensor;
 
@@ -24,8 +25,10 @@ void test_cxx11_tensor_thread_pool()
   in1.setRandom();
   in2.setRandom();
 
-  Eigen::ThreadPoolDevice thread_pool_device(3);
-  out.device(thread_pool_device) = in1 + in2 * 3.14;
+  ThreadPool thread_pool(2);
+  thread_pool.StartWorkers();
+  Eigen::ThreadPoolDevice thread_pool_device(&thread_pool, 3);
+  out.device(thread_pool_device) = in1 + in2 * 3.14f;
 
   for (int i = 0; i < 2; ++i) {
     for (int j = 0; j < 3; ++j) {