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#ifndef CAFFE_OPERATORS_BATCH_BOX_COX_OPS_H_
#define CAFFE_OPERATORS_BATCH_BOX_COX_OPS_H_
#include "caffe2/core/context.h"
#include "caffe2/core/export_caffe2_op_to_c10.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
C10_DECLARE_EXPORT_CAFFE2_OP_TO_C10(BatchBoxCox);
namespace caffe2 {
template <class Context>
class BatchBoxCoxOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit BatchBoxCoxOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...),
min_block_size_(
this->template GetSingleArgument<int>("min_block_size", 256)) {}
bool RunOnDevice() override {
return DispatchHelper<TensorTypes<float, double>>::call(this, Input(DATA));
}
template <typename T>
bool DoRunWithType();
protected:
template <typename T>
void BoxCoxNaive(
int64_t N,
int64_t D,
const T* data_ptr,
const T* lambda1_ptr,
const T* lambda2_ptr,
T k_eps,
T* output_ptr);
#ifdef CAFFE2_USE_MKL
template <typename T>
void BoxCoxNonzeroLambda(
int64_t D,
const T* data_ptr,
const T* lambda1,
const T* lambda2,
T k_eps,
T* output_ptr);
template <typename T>
void BoxCoxZeroLambda(
int64_t D,
const T* data_ptr,
const T* lambda2,
T k_eps,
T* output_ptr);
template <typename T>
void BoxCoxMixedLambda(
const T* data_ptr,
const vector<int>& nonzeros,
const vector<int>& zeros,
const T* lambda1,
const T* lambda2,
const T* lambda2_z,
T k_eps,
T* buffer,
T* output_ptr);
vector<int> nonzeros_, zeros_;
// Buffers used by the MKL version are cached across calls.
struct CachedBuffers {
virtual ~CachedBuffers() {}
int type_;
};
template <typename T>
struct TypedCachedBuffers : public CachedBuffers {
vector<T> lambda1_, lambda2_, lambda2_z_;
vector<T> accumulator_;
};
template <typename T>
TypedCachedBuffers<T>& GetBuffers();
unique_ptr<CachedBuffers> buffers_;
#endif // CAFFE2_USE_MKL
int min_block_size_;
INPUT_TAGS(DATA, LAMBDA1, LAMBDA2);
};
} // namespace caffe2
#endif // CAFFE_OPERATORS_BATCH_BOX_COX_OPS_H_
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