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kernel contructor cleanups (#5036)
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* ANOVA
* AUC
* Const
* Log
* DIag
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@jonpsy
jonpsy authored May 17, 2020
1 parent ca2afb8 commit e29377d
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Showing 10 changed files with 91 additions and 321 deletions.
51 changes: 16 additions & 35 deletions src/shogun/kernel/ANOVAKernel.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -7,26 +7,27 @@

#include <shogun/mathematics/Math.h>
#include <shogun/kernel/ANOVAKernel.h>
#include <shogun/mathematics/Math.h>

using namespace shogun;

ANOVAKernel::ANOVAKernel(): DotKernel(0), cardinality(1.0)
ANOVAKernel::ANOVAKernel(): DotKernel(0)
{
register_params();
SG_ADD(
&m_cardinality, "cardinality", "Kernel cardinality.",
ParameterProperties::HYPER);
}

ANOVAKernel::ANOVAKernel(int32_t cache, int32_t d)
: DotKernel(cache), cardinality(d)
ANOVAKernel::ANOVAKernel(int32_t size, int32_t d)
: ANOVAKernel()
{
register_params();
set_cache_size(size);
m_cardinality = d;
}

ANOVAKernel::ANOVAKernel(
const std::shared_ptr<DenseFeatures<float64_t>>& l, const std::shared_ptr<DenseFeatures<float64_t>>& r, int32_t d, int32_t cache)
: DotKernel(cache), cardinality(d)
: ANOVAKernel(cache, d)
{
register_params();
init(l, r);
}

Expand Down Expand Up @@ -88,20 +89,14 @@ float64_t ANOVAKernel::compute_rec2(int32_t idx_a, int32_t idx_b)
return result;
}

void ANOVAKernel::register_params()
{
SG_ADD(&cardinality, "cardinality", "Kernel cardinality.", ParameterProperties::HYPER);
}


float64_t ANOVAKernel::compute_recursive1(float64_t* avec, float64_t* bvec, int32_t len)
{
int32_t DP_len=(cardinality+1)*(len+1);
int32_t DP_len=(m_cardinality+1)*(len+1);
float64_t* DP = SG_MALLOC(float64_t, DP_len);

ASSERT(DP)
int32_t d=cardinality;
int32_t offs=cardinality+1;
int32_t d=m_cardinality;
int32_t offs=m_cardinality+1;

ASSERT(DP_len==(len+1)*offs)

Expand All @@ -128,15 +123,15 @@ float64_t ANOVAKernel::compute_recursive1(float64_t* avec, float64_t* bvec, int3

float64_t ANOVAKernel::compute_recursive2(float64_t* avec, float64_t* bvec, int32_t len)
{
float64_t* KD = SG_MALLOC(float64_t, cardinality+1);
float64_t* KS = SG_MALLOC(float64_t, cardinality+1);
float64_t* KD = SG_MALLOC(float64_t, m_cardinality+1);
float64_t* KS = SG_MALLOC(float64_t, m_cardinality+1);
float64_t* vec_pow = SG_MALLOC(float64_t, len);

ASSERT(vec_pow)
ASSERT(KS)
ASSERT(KD)

int32_t d=cardinality;
int32_t d=m_cardinality;
for (int32_t i=0; i < len; i++)
vec_pow[i] = 1;

Expand Down Expand Up @@ -171,18 +166,4 @@ float64_t ANOVAKernel::compute_recursive2(float64_t* avec, float64_t* bvec, int3
SG_FREE(KD);

return result;
}

std::shared_ptr<ANOVAKernel> ANOVAKernel::obtain_from_generic(const std::shared_ptr<Kernel>& kernel)
{
if (!kernel)
return NULL;

require(kernel->get_kernel_type()==K_ANOVA, "Provided kernel is "
"not of type CANOVAKernel, but type {}!",
kernel->get_kernel_type());

/* since an additional reference is returned */

return std::static_pointer_cast<ANOVAKernel>(kernel);
}
}
47 changes: 7 additions & 40 deletions src/shogun/kernel/ANOVAKernel.h
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Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ class Distance;
class ANOVAKernel: public DotKernel
{
public:
/** default constructor */

ANOVAKernel();

/** constructor
Expand All @@ -54,42 +54,25 @@ class ANOVAKernel: public DotKernel

virtual ~ANOVAKernel();

/** initialize kernel with features
* @param l features left-side
* @param r features right-side
* @return true if successful
*/
virtual bool init(std::shared_ptr<Features> l, std::shared_ptr<Features> r);

/**
* @return kernel type
*/
virtual EKernelType get_kernel_type() { return K_ANOVA; }

/**
* @return type of features
*/
virtual EFeatureType get_feature_type() { return F_DREAL; }

/**
* @return class of features
*/
virtual EFeatureClass get_feature_class() { return C_DENSE; }

/**
* @return name of kernel
*/
virtual const char* get_name() const { return "ANOVAKernel"; }

/** getter for degree parameter
* @return kernel parameter cardinality
*/
inline int32_t get_cardinality() { return this->cardinality; }
int32_t get_cardinality() { return this->m_cardinality; }

/** setter for degree parameter
* @param value kernel parameter cardinality
*/
inline void set_cardinality(int32_t value) { this->cardinality = value; }
void set_cardinality(int32_t value) { this->m_cardinality = value; }

/** compute rec 1
* @param idx_a
Expand All @@ -105,32 +88,16 @@ class ANOVAKernel: public DotKernel
*/
float64_t compute_rec2(int32_t idx_a, int32_t idx_b);

/** Casts the given kernel to CANOVAKernel.
* @param kernel Kernel to cast. Must be CANOVAKernel. Might be NULL
* @return casted CANOVAKernel object, NULL if input was NULL
*/
static std::shared_ptr<ANOVAKernel> obtain_from_generic(const std::shared_ptr<Kernel>& kernel);
protected:

/**
* compute kernel for specific feature vectors
* corresponding to [idx_a] of left-side and [idx_b] of right-side
* @param idx_a left-side index
* @param idx_b right-side index
* @return kernel value
*/
virtual float64_t compute(int32_t idx_a, int32_t idx_b);

/** register params */
void register_params();

private:
float64_t compute_recursive1(float64_t* avec, float64_t* bvec, int32_t len);
float64_t compute_recursive2(float64_t* avec, float64_t* bvec, int32_t len);

protected:
virtual float64_t compute(int32_t idx_a, int32_t idx_b);

protected:
/// degree parameter of kernel
int32_t cardinality;
int32_t m_cardinality = 1;
};
}

Expand Down
37 changes: 17 additions & 20 deletions src/shogun/kernel/AUCKernel.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -15,23 +15,20 @@

using namespace shogun;

void AUCKernel::init()
AUCKernel::AUCKernel() : DotKernel(0)
{
SG_ADD(
&subkernel, "subkernel", "The subkernel.", ParameterProperties::HYPER);
SG_ADD(&labels, "labels", "The labels.");
&m_subkernel, "subkernel", "The subkernel.", ParameterProperties::HYPER);
SG_ADD(&m_labels, "labels", "The labels.");
watch_method("setup_auc_maximization", &AUCKernel::setup_auc_maximization);
}

AUCKernel::AUCKernel() : DotKernel(0), subkernel(nullptr), labels(nullptr)
{
init();
}

AUCKernel::AUCKernel(int32_t size, std::shared_ptr<Kernel> s, std::shared_ptr<Labels> l)
: DotKernel(size), subkernel(std::move(s)), labels(std::move(l))
: AUCKernel()
{
init();
set_cache_size(size);
m_subkernel = std::move(s);
m_labels = std::move(l);
}

AUCKernel::~AUCKernel()
Expand All @@ -42,14 +39,14 @@ AUCKernel::~AUCKernel()
bool AUCKernel::setup_auc_maximization()
{
io::info("setting up AUC maximization");
ASSERT(labels)
ASSERT(labels->get_label_type() == LT_BINARY)
labels->ensure_valid();
ASSERT(m_labels)
ASSERT(m_labels->get_label_type() == LT_BINARY)
m_labels->ensure_valid();

// get the original labels
SGVector<int32_t> int_labels = binary_labels(labels)->get_int_labels();
SGVector<int32_t> int_labels = binary_labels(m_labels)->get_int_labels();

ASSERT(subkernel->get_num_vec_rhs() == int_labels.vlen)
ASSERT(m_subkernel->get_num_vec_rhs() == int_labels.vlen)

// count positive and negative
int32_t num_pos = 0;
Expand Down Expand Up @@ -135,16 +132,16 @@ float64_t AUCKernel::compute(int32_t idx_a, int32_t idx_b)
ASSERT(alen == 2)
ASSERT(blen == 2)

ASSERT(subkernel && subkernel->has_features())
ASSERT(m_subkernel && m_subkernel->has_features())

float64_t k11, k12, k21, k22;
int32_t idx_a1 = avec[0], idx_a2 = avec[1], idx_b1 = bvec[0],
idx_b2 = bvec[1];

k11 = subkernel->kernel(idx_a1, idx_b1);
k12 = subkernel->kernel(idx_a1, idx_b2);
k21 = subkernel->kernel(idx_a2, idx_b1);
k22 = subkernel->kernel(idx_a2, idx_b2);
k11 = m_subkernel->kernel(idx_a1, idx_b1);
k12 = m_subkernel->kernel(idx_a1, idx_b2);
k21 = m_subkernel->kernel(idx_a2, idx_b1);
k22 = m_subkernel->kernel(idx_a2, idx_b2);

float64_t result = k11 + k22 - k21 - k12;
lhs->as<DenseFeatures<uint16_t>>()->free_feature_vector(avec, idx_a, afree);
Expand Down
63 changes: 8 additions & 55 deletions src/shogun/kernel/AUCKernel.h
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Original file line number Diff line number Diff line change
Expand Up @@ -31,9 +31,8 @@ namespace shogun
*/
class AUCKernel : public DotKernel
{
void init();
public:
/** default constructor */

AUCKernel();

/** constructor
Expand All @@ -44,7 +43,6 @@ namespace shogun
*/
AUCKernel(int32_t size, std::shared_ptr<Kernel> subkernel, std::shared_ptr<Labels> labels);

/** destructor */
virtual ~AUCKernel();

/** initialize kernel based on current labeling and subkernel
Expand All @@ -54,66 +52,21 @@ namespace shogun
*/
bool setup_auc_maximization();

/** initialize kernel
*
* @param l features of left-hand side
* @param r features of right-hand side
* @return if initializing was successful
*/
virtual EKernelType get_kernel_type() { return K_AUC; }
virtual bool init(std::shared_ptr<Features> l, std::shared_ptr<Features> r);

/** return what type of kernel we are
*
* @return kernel type AUC
*/
virtual EKernelType get_kernel_type()
{
return K_AUC;
}

/** return the kernel's name
*
* @return name AUC
*/
virtual const char* get_name() const
{
return "AUCKernel";
}

/** return feature class the kernel can deal with
*
* @return feature class SIMPLE
*/
virtual EFeatureClass get_feature_class()
{
return C_DENSE;
}
virtual const char* get_name() const { return "AUCKernel"; }

/** return feature type the kernel can deal with
*
* @return word feature type
*/
virtual EFeatureType get_feature_type()
{
return F_WORD;
}
virtual EFeatureClass get_feature_class() { return C_DENSE; }

virtual EFeatureType get_feature_type() { return F_WORD; }

protected:
/** compute kernel function for features a and b
* idx_{a,b} denote the index of the feature vectors
* in the corresponding feature object
*
* @param idx_a index a
* @param idx_b index b
* @return computed kernel function at indices a,b
*/
virtual float64_t compute(int32_t idx_a, int32_t idx_b);

protected:
/** the subkernel */
std::shared_ptr<Kernel> subkernel;
/** the labels */
std::shared_ptr<Labels> labels;
std::shared_ptr<Kernel> m_subkernel;
std::shared_ptr<Labels> m_labels;
};
} // namespace shogun
#endif /* _AUCKERNEL_H__ */
21 changes: 7 additions & 14 deletions src/shogun/kernel/ConstKernel.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -17,22 +17,21 @@ using namespace shogun;
ConstKernel::ConstKernel()
: Kernel()
{
init();
SG_ADD(&m_const_val, "const_value", "Value for kernel elements.",
ParameterProperties::HYPER);
}

ConstKernel::ConstKernel(float64_t c)
: Kernel()
: ConstKernel()
{
init();
const_value=c;
m_const_val = c;
}

ConstKernel::ConstKernel(std::shared_ptr<Features> l, std::shared_ptr<Features> r, float64_t c)
: Kernel()
: ConstKernel(c)
{
init();
const_value=c;
init(std::move(l), std::move(r));
Kernel::init(l, r);
ASSERT(init_normalizer());
}

ConstKernel::~ConstKernel()
Expand All @@ -45,9 +44,3 @@ bool ConstKernel::init(std::shared_ptr<Features> l, std::shared_ptr<Features> r)
return init_normalizer();
}

void ConstKernel::init()
{
const_value=1.0;
SG_ADD(&const_value, "const_value", "Value for kernel elements.",
ParameterProperties::HYPER);
}
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