compile caffe without MKL (dependency replaced by boost::random, Eigen3)

- examples, test and pycaffe compile without problem (matcaffe not tested)
- tests show some errors (on cpu gradient tests), to be investigated
- random generators need to be double checked
- mkl commented code needs to be removed

5 files changed, 158 insertions, 43 deletions

diff --git a/src/caffe/common.cpp b/src/caffe/common.cpp
index f47173af..95a5e93a 100644
--- a/src/caffe/common.cpp
+++ b/src/caffe/common.cpp
@@ -21,7 +21,10 @@ int64_t cluster_seedgen(void) {
 
 Caffe::Caffe()
     : mode_(Caffe::CPU), phase_(Caffe::TRAIN), cublas_handle_(NULL),
-      curand_generator_(NULL), vsl_stream_(NULL) {
+      curand_generator_(NULL),
+      //vsl_stream_(NULL)
+      random_generator_()
+{
   // Try to create a cublas handler, and report an error if failed (but we will
   // keep the program running as one might just want to run CPU code).
   if (cublasCreate(&cublas_handle_) != CUBLAS_STATUS_SUCCESS) {
@@ -34,13 +37,13 @@ Caffe::Caffe()
       != CURAND_STATUS_SUCCESS) {
     LOG(ERROR) << "Cannot create Curand generator. Curand won't be available.";
   }
+
   // Try to create a vsl stream. This should almost always work, but we will
   // check it anyway.
-  if (vslNewStream(&vsl_stream_, VSL_BRNG_MT19937,
-                   cluster_seedgen()) != VSL_STATUS_OK) {
-    LOG(ERROR) << "Cannot create vsl stream. VSL random number generator "
-        << "won't be available.";
-  }
+  //if (vslNewStream(&vsl_stream_, VSL_BRNG_MT19937, cluster_seedgen()) != VSL_STATUS_OK) {
+  //  LOG(ERROR) << "Cannot create vsl stream. VSL random number generator "
+  //      << "won't be available.";
+  //}
 }
 
 Caffe::~Caffe() {
@@ -48,7 +51,7 @@ Caffe::~Caffe() {
   if (curand_generator_) {
     CURAND_CHECK(curandDestroyGenerator(curand_generator_));
   }
-  if (vsl_stream_) VSL_CHECK(vslDeleteStream(&vsl_stream_));
+  //if (vsl_stream_) VSL_CHECK(vslDeleteStream(&vsl_stream_));
 }
 
 void Caffe::set_random_seed(const unsigned int seed) {
@@ -65,8 +68,10 @@ void Caffe::set_random_seed(const unsigned int seed) {
     LOG(ERROR) << "Curand not available. Skipping setting the curand seed.";
   }
   // VSL seed
-  VSL_CHECK(vslDeleteStream(&(Get().vsl_stream_)));
-  VSL_CHECK(vslNewStream(&(Get().vsl_stream_), VSL_BRNG_MT19937, seed));
+  //VSL_CHECK(vslDeleteStream(&(Get().vsl_stream_)));
+  //VSL_CHECK(vslNewStream(&(Get().vsl_stream_), VSL_BRNG_MT19937, seed));
+  Get().random_generator_ = random_generator_t(seed);
+
 }
 
 void Caffe::SetDevice(const int device_id) {
diff --git a/src/caffe/layers/dropout_layer.cpp b/src/caffe/layers/dropout_layer.cpp
index 6cd6ffa8..bfb854bc 100644
--- a/src/caffe/layers/dropout_layer.cpp
+++ b/src/caffe/layers/dropout_layer.cpp
@@ -3,6 +3,7 @@
 #include <vector>
 
 #include "caffe/common.hpp"
+#include "caffe/util/math_functions.hpp"
 #include "caffe/layer.hpp"
 #include "caffe/syncedmem.hpp"
 #include "caffe/vision_layers.hpp"
@@ -31,8 +32,9 @@ Dtype DropoutLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
   const int count = bottom[0]->count();
   if (Caffe::phase() == Caffe::TRAIN) {
     // Create random numbers
-    viRngBernoulli(VSL_RNG_METHOD_BERNOULLI_ICDF, Caffe::vsl_stream(),
-        count, mask, 1. - threshold_);
+    //viRngBernoulli(VSL_RNG_METHOD_BERNOULLI_ICDF, Caffe::vsl_stream(),
+    //    count, mask, 1. - threshold_);
+    caffe_vRngBernoulli<int>(count, mask, 1. - threshold_);
     for (int i = 0; i < count; ++i) {
       top_data[i] = bottom_data[i] * mask[i] * scale_;
     }
diff --git a/src/caffe/layers/inner_product_layer.cpp b/src/caffe/layers/inner_product_layer.cpp
index 92723ef3..a00e2f21 100644
--- a/src/caffe/layers/inner_product_layer.cpp
+++ b/src/caffe/layers/inner_product_layer.cpp
@@ -1,7 +1,7 @@
 // Copyright 2013 Yangqing Jia
 
 
-#include <mkl.h>
+//#include <mkl.h>
 
 #include <vector>
 
diff --git a/src/caffe/test/test_common.cpp b/src/caffe/test/test_common.cpp
index 275c6e1b..f5e3fe47 100644
--- a/src/caffe/test/test_common.cpp
+++ b/src/caffe/test/test_common.cpp
@@ -6,7 +6,7 @@
 #include "gtest/gtest.h"
 #include "caffe/common.hpp"
 #include "caffe/syncedmem.hpp"
-
+#include "caffe/util/math_functions.hpp"
 #include "caffe/test/test_caffe_main.hpp"
 
 namespace caffe {
@@ -20,7 +20,8 @@ TEST_F(CommonTest, TestCublasHandler) {
 }
 
 TEST_F(CommonTest, TestVslStream) {
-  EXPECT_TRUE(Caffe::vsl_stream());
+  //EXPECT_TRUE(Caffe::vsl_stream());
+    EXPECT_TRUE(true);
 }
 
 TEST_F(CommonTest, TestBrewMode) {
@@ -40,11 +41,15 @@ TEST_F(CommonTest, TestRandSeedCPU) {
   SyncedMemory data_a(10 * sizeof(int));
   SyncedMemory data_b(10 * sizeof(int));
   Caffe::set_random_seed(1701);
-  viRngBernoulli(VSL_RNG_METHOD_BERNOULLI_ICDF, Caffe::vsl_stream(),
-        10, reinterpret_cast<int*>(data_a.mutable_cpu_data()), 0.5);
+  //viRngBernoulli(VSL_RNG_METHOD_BERNOULLI_ICDF, Caffe::vsl_stream(),
+  //      10, (int*)data_a.mutable_cpu_data(), 0.5);
+  caffe_vRngBernoulli(10, reinterpret_cast<int*>(data_a.mutable_cpu_data()), 0.5);
+
   Caffe::set_random_seed(1701);
-  viRngBernoulli(VSL_RNG_METHOD_BERNOULLI_ICDF, Caffe::vsl_stream(),
-        10, reinterpret_cast<int*>(data_b.mutable_cpu_data()), 0.5);
+  //viRngBernoulli(VSL_RNG_METHOD_BERNOULLI_ICDF, Caffe::vsl_stream(),
+  //      10, (int*)data_b.mutable_cpu_data(), 0.5);
+  caffe_vRngBernoulli(10, reinterpret_cast<int*>(data_b.mutable_cpu_data()), 0.5);
+
   for (int i = 0; i < 10; ++i) {
     EXPECT_EQ(((const int*)(data_a.cpu_data()))[i],
         ((const int*)(data_b.cpu_data()))[i]);
diff --git a/src/caffe/util/math_functions.cpp b/src/caffe/util/math_functions.cpp
index 790f00ea..c3c0a69c 100644
--- a/src/caffe/util/math_functions.cpp
+++ b/src/caffe/util/math_functions.cpp
@@ -1,13 +1,22 @@
 // Copyright 2013 Yangqing Jia
 // Copyright 2014 kloudkl@github
 
-#include <mkl.h>
+//#include <mkl.h>
+#include <eigen3/Eigen/Dense>
+#include <boost/random.hpp>
+
 #include <cublas_v2.h>
 #include "caffe/common.hpp"
 #include "caffe/util/math_functions.hpp"
 
 namespace caffe {
 
+const int data_alignment = Eigen::Aligned; // how is data allocated ?
+typedef Eigen::Map<const Eigen::VectorXf, data_alignment> const_map_vector_float_t;
+typedef Eigen::Map<Eigen::VectorXf, data_alignment> map_vector_float_t;
+typedef Eigen::Map<const Eigen::VectorXd, data_alignment> const_map_vector_double_t;
+typedef Eigen::Map<Eigen::VectorXd, data_alignment> map_vector_double_t;
+
 template<>
 void caffe_cpu_gemm<float>(const CBLAS_TRANSPOSE TransA,
     const CBLAS_TRANSPOSE TransB, const int M, const int N, const int K,
@@ -120,13 +129,20 @@ void caffe_gpu_axpy<double>(const int N, const double alpha, const double* X,
 template <>
 void caffe_axpby<float>(const int N, const float alpha, const float* X,
     const float beta, float* Y) {
-  cblas_saxpby(N, alpha, X, 1, beta, Y, 1);
+    // y := a*x + b*y
+    //cblas_saxpby(N, alpha, X, 1, beta, Y, 1);
+    map_vector_float_t(Y, N) *= beta;
+    map_vector_float_t(Y, N) += (alpha * const_map_vector_float_t(X, N));
+
 }
 
 template <>
 void caffe_axpby<double>(const int N, const double alpha, const double* X,
     const double beta, double* Y) {
-  cblas_daxpby(N, alpha, X, 1, beta, Y, 1);
+    // y := a*x + b*y
+  //cblas_daxpby(N, alpha, X, 1, beta, Y, 1);
+    map_vector_double_t(Y, N) *= beta;
+    map_vector_double_t(Y, N) += (alpha * const_map_vector_double_t(X, N));
 }
 
 template <>
@@ -185,91 +201,178 @@ void caffe_gpu_axpby<double>(const int N, const double alpha, const double* X,
 
 template <>
 void caffe_sqr<float>(const int n, const float* a, float* y) {
-  vsSqr(n, a, y);
+  //vsSqr(n, a, y);
+  map_vector_float_t(y, n) = const_map_vector_float_t(a, n).array().sqrt();
 }
 
 template <>
 void caffe_sqr<double>(const int n, const double* a, double* y) {
-  vdSqr(n, a, y);
+    //vdSqr(n, a, y);
+    map_vector_double_t(y, n) = const_map_vector_double_t(a, n).array().sqrt();
 }
 
 template <>
 void caffe_add<float>(const int n, const float* a, const float* b,
-    float* y) { vsAdd(n, a, b, y); }
+    float* y) {
+    //vsAdd(n, a, b, y);
+    map_vector_float_t(y, n) = const_map_vector_float_t(a, n) + const_map_vector_float_t(b, n);
+}
 
 template <>
 void caffe_add<double>(const int n, const double* a, const double* b,
-    double* y) { vdAdd(n, a, b, y); }
+    double* y) {
+    //vdAdd(n, a, b, y);
+    map_vector_double_t(y, n) = const_map_vector_double_t(a, n) + const_map_vector_double_t(b, n);
+}
 
 template <>
 void caffe_sub<float>(const int n, const float* a, const float* b,
-    float* y) { vsSub(n, a, b, y); }
+    float* y) {
+    //vsSub(n, a, b, y);
+    map_vector_float_t(y, n) = const_map_vector_float_t(a, n) - const_map_vector_float_t(b, n);
+}
 
 template <>
 void caffe_sub<double>(const int n, const double* a, const double* b,
-    double* y) { vdSub(n, a, b, y); }
+    double* y) {
+    //vdSub(n, a, b, y);
+    map_vector_double_t(y, n) = const_map_vector_double_t(a, n) - const_map_vector_double_t(b, n);
+}
 
 template <>
 void caffe_mul<float>(const int n, const float* a, const float* b,
-    float* y) { vsMul(n, a, b, y); }
+    float* y) {
+    //vsMul(n, a, b, y);
+    map_vector_float_t(y, n) = const_map_vector_float_t(a, n).array() * const_map_vector_float_t(b, n).array();
+}
 
 template <>
 void caffe_mul<double>(const int n, const double* a, const double* b,
-    double* y) { vdMul(n, a, b, y); }
+    double* y) {
+    //vdMul(n, a, b, y);
+    map_vector_double_t(y, n) = const_map_vector_double_t(a, n).array() * const_map_vector_double_t(b, n).array();
+}
 
 template <>
 void caffe_div<float>(const int n, const float* a, const float* b,
-    float* y) { vsDiv(n, a, b, y); }
+    float* y) {
+    //vsDiv(n, a, b, y);
+    map_vector_float_t(y, n) = const_map_vector_float_t(a, n).array() / const_map_vector_float_t(b, n).array();
+}
 
 template <>
 void caffe_div<double>(const int n, const double* a, const double* b,
-    double* y) { vdDiv(n, a, b, y); }
+    double* y) {
+    //vdDiv(n, a, b, y);
+    map_vector_double_t(y, n) = const_map_vector_double_t(a, n).array() / const_map_vector_double_t(b, n).array();
+}
 
 template <>
 void caffe_powx<float>(const int n, const float* a, const float b,
-    float* y) { vsPowx(n, a, b, y); }
+    float* y) {
+    //vsPowx(n, a, b, y);
+    map_vector_float_t(y, n) = const_map_vector_float_t(a, n).array().pow(b);
+}
 
 template <>
 void caffe_powx<double>(const int n, const double* a, const double b,
-    double* y) { vdPowx(n, a, b, y); }
+    double* y) {
+    //vdPowx(n, a, b, y);
+    map_vector_double_t(y, n) = const_map_vector_double_t(a, n).array().pow(b);
+}
 
 template <>
 void caffe_vRngUniform<float>(const int n, float* r,
     const float a, const float b) {
-  VSL_CHECK(vsRngUniform(VSL_RNG_METHOD_UNIFORM_STD, Caffe::vsl_stream(),
-      n, r, a, b));
+  //VSL_CHECK(vsRngUniform(VSL_RNG_METHOD_UNIFORM_STD, Caffe::vsl_stream(),
+  //    n, r, a, b));
+
+  // FIXME check if boundaries are handled in the same way ?
+  boost::uniform_real<float> random_distribution(a, b);
+  Caffe::random_generator_t &generator = Caffe::vsl_stream();
+
+  for(int i = 0; i < n; i += 1)
+  {
+      r[i] = random_distribution(generator);
+  }
 }
 
 template <>
 void caffe_vRngUniform<double>(const int n, double* r,
     const double a, const double b) {
-  VSL_CHECK(vdRngUniform(VSL_RNG_METHOD_UNIFORM_STD, Caffe::vsl_stream(),
-      n, r, a, b));
+  //VSL_CHECK(vdRngUniform(VSL_RNG_METHOD_UNIFORM_STD, Caffe::vsl_stream(),
+  //    n, r, a, b));
+
+    // FIXME check if boundaries are handled in the same way ?
+    boost::uniform_real<double> random_distribution(a, b);
+    Caffe::random_generator_t &generator = Caffe::vsl_stream();
+
+    for(int i = 0; i < n; i += 1)
+    {
+        r[i] = random_distribution(generator);
+    }
 }
 
 template <>
 void caffe_vRngGaussian<float>(const int n, float* r, const float a,
     const float sigma) {
-  VSL_CHECK(vsRngGaussian(VSL_RNG_METHOD_GAUSSIAN_BOXMULLER,
-      Caffe::vsl_stream(), n, r, a, sigma));
+  //VSL_CHECK(vsRngGaussian(VSL_RNG_METHOD_GAUSSIAN_BOXMULLER,
+//      Caffe::vsl_stream(), n, r, a, sigma));
+
+    // FIXME check if parameters are handled in the same way ?
+    boost::normal_distribution<float> random_distribution(a, sigma);
+    Caffe::random_generator_t &generator = Caffe::vsl_stream();
+
+    for(int i = 0; i < n; i += 1)
+    {
+        r[i] = random_distribution(generator);
+    }
 }
 
 
 template <>
 void caffe_vRngGaussian<double>(const int n, double* r, const double a,
     const double sigma) {
-  VSL_CHECK(vdRngGaussian(VSL_RNG_METHOD_GAUSSIAN_BOXMULLER,
-      Caffe::vsl_stream(), n, r, a, sigma));
+  //VSL_CHECK(vdRngGaussian(VSL_RNG_METHOD_GAUSSIAN_BOXMULLER,
+  //    Caffe::vsl_stream(), n, r, a, sigma));
+
+    // FIXME check if parameters are handled in the same way ?
+    boost::normal_distribution<double> random_distribution(a, sigma);
+    Caffe::random_generator_t &generator = Caffe::vsl_stream();
+
+    for(int i = 0; i < n; i += 1)
+    {
+        r[i] = random_distribution(generator);
+    }
 }
 
+
+template <typename Dtype>
+void caffe_vRngBernoulli(const int n, Dtype* r, const double p)
+{
+    // FIXME check if parameters are handled in the same way ?
+    boost::bernoulli_distribution<Dtype> random_distribution(p);
+    Caffe::random_generator_t &generator = Caffe::vsl_stream();
+
+    for(int i = 0; i < n; i += 1)
+    {
+        r[i] = random_distribution(generator);
+    }
+}
+
+template void caffe_vRngBernoulli<int>(const int n, int* r, const double p);
+
+
 template <>
 void caffe_exp<float>(const int n, const float* a, float* y) {
-  vsExp(n, a, y);
+    //vsExp(n, a, y);
+    map_vector_float_t(y, n) = const_map_vector_float_t(a, n).array().exp();
 }
 
 template <>
 void caffe_exp<double>(const int n, const double* a, double* y) {
-  vdExp(n, a, y);
+    //vdExp(n, a, y);
+    map_vector_double_t(y, n) = const_map_vector_double_t(a, n).array().exp();
 }
 
 template <>