7 #ifndef TREELITE_TREE_IMPL_H_ 8 #define TREELITE_TREE_IMPL_H_ 17 #include <unordered_map> 28 inline std::string GetString(T x) {
29 return std::to_string(x);
33 inline std::string GetString<float>(
float x) {
34 std::ostringstream oss;
35 oss << std::setprecision(std::numeric_limits<float>::max_digits10) << x;
40 inline std::string GetString<double>(
double x) {
41 std::ostringstream oss;
42 oss << std::setprecision(std::numeric_limits<double>::max_digits10) << x;
51 ContiguousArray<T>::ContiguousArray()
52 : buffer_(nullptr), size_(0), capacity_(0), owned_buffer_(true) {}
55 ContiguousArray<T>::~ContiguousArray() {
56 if (buffer_ && owned_buffer_) {
62 ContiguousArray<T>::ContiguousArray(ContiguousArray&& other) noexcept
63 : buffer_(other.buffer_), size_(other.size_), capacity_(other.capacity_),
64 owned_buffer_(other.owned_buffer_) {
65 other.buffer_ =
nullptr;
66 other.size_ = other.capacity_ = 0;
71 ContiguousArray<T>::operator=(ContiguousArray&& other) noexcept {
72 if (buffer_ && owned_buffer_) {
75 buffer_ = other.buffer_;
77 capacity_ = other.capacity_;
78 owned_buffer_ = other.owned_buffer_;
79 other.buffer_ =
nullptr;
80 other.size_ = other.capacity_ = 0;
85 inline ContiguousArray<T>
86 ContiguousArray<T>::Clone()
const {
87 ContiguousArray clone;
88 clone.buffer_ =
static_cast<T*
>(std::malloc(
sizeof(T) * capacity_));
90 throw std::runtime_error(
"Could not allocate memory for the clone");
92 std::memcpy(clone.buffer_, buffer_,
sizeof(T) * size_);
94 clone.capacity_ = capacity_;
95 clone.owned_buffer_ =
true;
101 ContiguousArray<T>::UseForeignBuffer(
void* prealloc_buf, std::size_t size) {
102 if (buffer_ && owned_buffer_) {
105 buffer_ =
static_cast<T*
>(prealloc_buf);
108 owned_buffer_ =
false;
111 template <
typename T>
113 ContiguousArray<T>::Data() {
117 template <
typename T>
119 ContiguousArray<T>::Data()
const {
123 template <
typename T>
125 ContiguousArray<T>::End() {
126 return &buffer_[Size()];
129 template <
typename T>
131 ContiguousArray<T>::End()
const {
132 return &buffer_[Size()];
135 template <
typename T>
137 ContiguousArray<T>::Back() {
138 return buffer_[Size() - 1];
141 template <
typename T>
143 ContiguousArray<T>::Back()
const {
144 return buffer_[Size() - 1];
147 template <
typename T>
149 ContiguousArray<T>::Size()
const {
153 template <
typename T>
155 ContiguousArray<T>::Empty()
const {
156 return (Size() == 0);
159 template <
typename T>
161 ContiguousArray<T>::Reserve(std::size_t newsize) {
162 if (!owned_buffer_) {
163 throw std::runtime_error(
"Cannot resize when using a foreign buffer; clone first");
165 T* newbuf =
static_cast<T*
>(std::realloc(static_cast<void*>(buffer_),
sizeof(T) * newsize));
167 throw std::runtime_error(
"Could not expand buffer");
173 template <
typename T>
175 ContiguousArray<T>::Resize(std::size_t newsize) {
176 if (!owned_buffer_) {
177 throw std::runtime_error(
"Cannot resize when using a foreign buffer; clone first");
179 if (newsize > capacity_) {
180 std::size_t newcapacity = capacity_;
181 if (newcapacity == 0) {
184 while (newcapacity <= newsize) {
187 Reserve(newcapacity);
192 template <
typename T>
194 ContiguousArray<T>::Resize(std::size_t newsize, T t) {
195 if (!owned_buffer_) {
196 throw std::runtime_error(
"Cannot resize when using a foreign buffer; clone first");
198 std::size_t oldsize = Size();
200 for (std::size_t i = oldsize; i < newsize; ++i) {
205 template <
typename T>
207 ContiguousArray<T>::Clear() {
208 if (!owned_buffer_) {
209 throw std::runtime_error(
"Cannot clear when using a foreign buffer; clone first");
214 template <
typename T>
216 ContiguousArray<T>::PushBack(T t) {
217 if (!owned_buffer_) {
218 throw std::runtime_error(
"Cannot add element when using a foreign buffer; clone first");
220 if (size_ == capacity_) {
221 Reserve(capacity_ * 2);
223 buffer_[size_++] = t;
226 template <
typename T>
228 ContiguousArray<T>::Extend(
const std::vector<T>& other) {
229 if (!owned_buffer_) {
230 throw std::runtime_error(
"Cannot add elements when using a foreign buffer; clone first");
232 std::size_t newsize = size_ + other.size();
233 if (newsize > capacity_) {
234 std::size_t newcapacity = capacity_;
235 if (newcapacity == 0) {
238 while (newcapacity <= newsize) {
241 Reserve(newcapacity);
243 std::memcpy(&buffer_[size_], static_cast<const void*>(other.data()),
sizeof(T) * other.size());
247 template <
typename T>
249 ContiguousArray<T>::operator[](std::size_t idx) {
253 template <
typename T>
255 ContiguousArray<T>::operator[](std::size_t idx)
const {
259 template <
typename T>
261 ContiguousArray<T>::at(std::size_t idx) {
263 throw std::runtime_error(
"nid out of range");
268 template <
typename T>
270 ContiguousArray<T>::at(std::size_t idx)
const {
272 throw std::runtime_error(
"nid out of range");
277 template <
typename T>
279 ContiguousArray<T>::at(
int idx) {
280 if (idx < 0 || static_cast<std::size_t>(idx) >= Size()) {
281 throw std::runtime_error(
"nid out of range");
283 return buffer_[
static_cast<std::size_t
>(idx)];
286 template <
typename T>
288 ContiguousArray<T>::at(
int idx)
const {
289 if (idx < 0 || static_cast<std::size_t>(idx) >= Size()) {
290 throw std::runtime_error(
"nid out of range");
292 return buffer_[
static_cast<std::size_t
>(idx)];
295 template<
typename Container>
296 inline std::vector<std::pair<std::string, std::string> >
297 ModelParam::InitAllowUnknown(
const Container& kwargs) {
298 std::vector<std::pair<std::string, std::string>> unknowns;
299 for (
const auto& e : kwargs) {
300 if (e.first ==
"pred_transform") {
301 std::strncpy(this->pred_transform, e.second.c_str(),
302 TREELITE_MAX_PRED_TRANSFORM_LENGTH - 1);
303 this->pred_transform[TREELITE_MAX_PRED_TRANSFORM_LENGTH - 1] =
'\0';
304 }
else if (e.first ==
"sigmoid_alpha") {
305 this->sigmoid_alpha = std::stof(e.second,
nullptr);
306 }
else if (e.first ==
"global_bias") {
307 this->global_bias = std::stof(e.second,
nullptr);
313 inline std::map<std::string, std::string>
314 ModelParam::__DICT__()
const {
315 std::map<std::string, std::string> ret;
316 ret.emplace(
"pred_transform", std::string(this->pred_transform));
317 ret.emplace(
"sigmoid_alpha", GetString(this->sigmoid_alpha));
318 ret.emplace(
"global_bias", GetString(this->global_bias));
322 inline PyBufferFrame GetPyBufferFromArray(
void* data,
const char* format,
323 std::size_t itemsize, std::size_t nitem) {
324 return PyBufferFrame{data,
const_cast<char*
>(format), itemsize, nitem};
328 template <
typename T>
329 inline const char* InferFormatString() {
332 return (std::is_unsigned<T>::value ?
"=B" :
"=b");
334 return (std::is_unsigned<T>::value ?
"=H" :
"=h");
336 if (std::is_integral<T>::value) {
337 return (std::is_unsigned<T>::value ?
"=L" :
"=l");
339 if (!std::is_floating_point<T>::value) {
340 throw std::runtime_error(
"Could not infer format string");
345 if (std::is_integral<T>::value) {
346 return (std::is_unsigned<T>::value ?
"=Q" :
"=q");
348 if (!std::is_floating_point<T>::value) {
349 throw std::runtime_error(
"Could not infer format string");
354 throw std::runtime_error(
"Unrecognized type");
359 template <
typename T>
360 inline PyBufferFrame GetPyBufferFromArray(ContiguousArray<T>* vec,
const char* format) {
361 return GetPyBufferFromArray(static_cast<void*>(vec->Data()), format,
sizeof(T), vec->Size());
364 template <
typename T>
365 inline PyBufferFrame GetPyBufferFromArray(ContiguousArray<T>* vec) {
366 static_assert(std::is_arithmetic<T>::value,
367 "Use GetPyBufferFromArray(vec, format) for composite types; specify format string manually");
368 return GetPyBufferFromArray(vec, InferFormatString<T>());
371 inline PyBufferFrame GetPyBufferFromScalar(
void* data,
const char* format, std::size_t itemsize) {
372 return GetPyBufferFromArray(data, format, itemsize, 1);
375 template <
typename T>
376 inline PyBufferFrame GetPyBufferFromScalar(T* scalar,
const char* format) {
377 static_assert(std::is_standard_layout<T>::value,
"T must be in the standard layout");
378 return GetPyBufferFromScalar(static_cast<void*>(scalar), format,
sizeof(T));
381 inline PyBufferFrame GetPyBufferFromScalar(TypeInfo* scalar) {
382 using T = std::underlying_type<TypeInfo>::type;
383 return GetPyBufferFromScalar(reinterpret_cast<T*>(scalar), InferFormatString<T>());
386 inline PyBufferFrame GetPyBufferFromScalar(TaskType* scalar) {
387 using T = std::underlying_type<TaskType>::type;
388 return GetPyBufferFromScalar(reinterpret_cast<T*>(scalar), InferFormatString<T>());
391 template <
typename T>
392 inline PyBufferFrame GetPyBufferFromScalar(T* scalar) {
393 static_assert(std::is_arithmetic<T>::value,
394 "Use GetPyBufferFromScalar(scalar, format) for composite types; " 395 "specify format string manually");
396 return GetPyBufferFromScalar(scalar, InferFormatString<T>());
399 template <
typename T>
400 inline void InitArrayFromPyBuffer(ContiguousArray<T>* vec, PyBufferFrame frame) {
401 if (
sizeof(T) != frame.itemsize) {
402 throw std::runtime_error(
"Incorrect itemsize");
404 vec->UseForeignBuffer(frame.buf, frame.nitem);
407 inline void InitScalarFromPyBuffer(TypeInfo* scalar, PyBufferFrame buffer) {
408 using T = std::underlying_type<TypeInfo>::type;
409 if (
sizeof(T) != buffer.itemsize) {
410 throw std::runtime_error(
"Incorrect itemsize");
412 if (buffer.nitem != 1) {
413 throw std::runtime_error(
"nitem must be 1 for a scalar");
415 T* t =
static_cast<T*
>(buffer.buf);
416 *scalar =
static_cast<TypeInfo>(*t);
419 inline void InitScalarFromPyBuffer(TaskType* scalar, PyBufferFrame buffer) {
420 using T = std::underlying_type<TaskType>::type;
421 if (
sizeof(T) != buffer.itemsize) {
422 throw std::runtime_error(
"Incorrect itemsize");
424 if (buffer.nitem != 1) {
425 throw std::runtime_error(
"nitem must be 1 for a scalar");
427 T* t =
static_cast<T*
>(buffer.buf);
428 *scalar =
static_cast<TaskType>(*t);
431 template <
typename T>
432 inline void InitScalarFromPyBuffer(T* scalar, PyBufferFrame buffer) {
433 static_assert(std::is_standard_layout<T>::value,
"T must be in the standard layout");
434 if (
sizeof(T) != buffer.itemsize) {
435 throw std::runtime_error(
"Incorrect itemsize");
437 if (buffer.nitem != 1) {
438 throw std::runtime_error(
"nitem must be 1 for a scalar");
440 T* t =
static_cast<T*
>(buffer.buf);
444 template <
typename T>
445 inline void ReadScalarFromFile(T* scalar, FILE* fp) {
446 static_assert(std::is_standard_layout<T>::value,
"T must be in the standard layout");
447 if (std::fread(scalar,
sizeof(T), 1, fp) < 1) {
448 throw std::runtime_error(
"Could not read a scalar");
452 template <
typename T>
453 inline void WriteScalarToFile(T* scalar, FILE* fp) {
454 static_assert(std::is_standard_layout<T>::value,
"T must be in the standard layout");
455 if (std::fwrite(scalar,
sizeof(T), 1, fp) < 1) {
456 throw std::runtime_error(
"Could not write a scalar");
460 template <
typename T>
461 inline void ReadArrayFromFile(ContiguousArray<T>* vec, FILE* fp) {
463 if (std::fread(&nelem,
sizeof(nelem), 1, fp) < 1) {
464 throw std::runtime_error(
"Could not read the number of elements");
468 const auto nelem_size_t =
static_cast<std::size_t
>(nelem);
469 if (std::fread(vec->Data(),
sizeof(T), nelem_size_t, fp) < nelem_size_t) {
470 throw std::runtime_error(
"Could not read an array");
474 template <
typename T>
475 inline void WriteArrayToFile(ContiguousArray<T>* vec, FILE* fp) {
476 static_assert(
sizeof(uint64_t) >=
sizeof(
size_t),
"size_t too large");
477 const auto nelem =
static_cast<uint64_t
>(vec->Size());
478 if (std::fwrite(&nelem,
sizeof(nelem), 1, fp) < 1) {
479 throw std::runtime_error(
"Could not write the number of elements");
481 const auto nelem_size_t = vec->Size();
482 if (std::fwrite(vec->Data(),
sizeof(T), nelem_size_t, fp) < nelem_size_t) {
483 throw std::runtime_error(
"Could not write an array");
487 template <
typename ThresholdType,
typename LeafOutputType>
488 inline Tree<ThresholdType, LeafOutputType>
489 Tree<ThresholdType, LeafOutputType>::Clone()
const {
490 Tree<ThresholdType, LeafOutputType> tree;
491 tree.num_nodes = num_nodes;
492 tree.nodes_ = nodes_.Clone();
493 tree.leaf_vector_ = leaf_vector_.Clone();
494 tree.leaf_vector_begin_ = leaf_vector_begin_.Clone();
495 tree.leaf_vector_end_ = leaf_vector_end_.Clone();
496 tree.matching_categories_ = matching_categories_.Clone();
497 tree.matching_categories_offset_ = matching_categories_offset_.Clone();
501 template <
typename ThresholdType,
typename LeafOutputType>
503 Tree<ThresholdType, LeafOutputType>::GetFormatStringForNode() {
504 if (std::is_same<ThresholdType, float>::value) {
505 return "T{=l=l=L=f=Q=d=d=b=b=?=?=?=?xx}";
507 return "T{=l=l=Lxxxx=d=Q=d=d=b=b=?=?=?=?xx}";
511 constexpr std::size_t kNumFramePerTree = 7;
513 template <
typename ThresholdType,
typename LeafOutputType>
514 template <
typename ScalarHandler,
typename PrimitiveArrayHandler,
typename CompositeArrayHandler>
516 Tree<ThresholdType, LeafOutputType>::SerializeTemplate(
517 ScalarHandler scalar_handler, PrimitiveArrayHandler primitive_array_handler,
518 CompositeArrayHandler composite_array_handler) {
519 scalar_handler(&num_nodes);
520 composite_array_handler(&nodes_, GetFormatStringForNode());
521 primitive_array_handler(&leaf_vector_);
522 primitive_array_handler(&leaf_vector_begin_);
523 primitive_array_handler(&leaf_vector_end_);
524 primitive_array_handler(&matching_categories_);
525 primitive_array_handler(&matching_categories_offset_);
528 template <
typename ThresholdType,
typename LeafOutputType>
529 template <
typename ScalarHandler,
typename ArrayHandler>
531 Tree<ThresholdType, LeafOutputType>::DeserializeTemplate(
532 ScalarHandler scalar_handler, ArrayHandler array_handler) {
533 scalar_handler(&num_nodes);
534 array_handler(&nodes_);
535 if (static_cast<std::size_t>(num_nodes) != nodes_.Size()) {
536 throw std::runtime_error(
"Could not load the correct number of nodes");
538 array_handler(&leaf_vector_);
539 array_handler(&leaf_vector_begin_);
540 array_handler(&leaf_vector_end_);
541 array_handler(&matching_categories_);
542 array_handler(&matching_categories_offset_);
545 template <
typename ThresholdType,
typename LeafOutputType>
547 Tree<ThresholdType, LeafOutputType>::GetPyBuffer(std::vector<PyBufferFrame>* dest) {
548 auto scalar_handler = [dest](
auto* field) {
549 dest->push_back(GetPyBufferFromScalar(field));
551 auto primitive_array_handler = [dest](
auto* field) {
552 dest->push_back(GetPyBufferFromArray(field));
554 auto composite_array_handler = [dest](
auto* field,
const char* format) {
555 dest->push_back(GetPyBufferFromArray(field, format));
557 SerializeTemplate(scalar_handler, primitive_array_handler, composite_array_handler);
560 template <
typename ThresholdType,
typename LeafOutputType>
562 Tree<ThresholdType, LeafOutputType>::SerializeToFile(FILE* dest_fp) {
563 auto scalar_handler = [dest_fp](
auto* field) {
564 WriteScalarToFile(field, dest_fp);
566 auto primitive_array_handler = [dest_fp](
auto* field) {
567 WriteArrayToFile(field, dest_fp);
569 auto composite_array_handler = [dest_fp](
auto* field,
const char* format) {
570 WriteArrayToFile(field, dest_fp);
572 SerializeTemplate(scalar_handler, primitive_array_handler, composite_array_handler);
575 template <
typename ThresholdType,
typename LeafOutputType>
577 Tree<ThresholdType, LeafOutputType>::InitFromPyBuffer(std::vector<PyBufferFrame>::iterator begin,
578 std::vector<PyBufferFrame>::iterator end) {
579 if (std::distance(begin, end) != kNumFramePerTree) {
580 throw std::runtime_error(
"Wrong number of frames specified");
582 auto scalar_handler = [&begin](
auto* field) {
583 InitScalarFromPyBuffer(field, *begin++);
585 auto array_handler = [&begin](
auto* field) {
586 InitArrayFromPyBuffer(field, *begin++);
588 DeserializeTemplate(scalar_handler, array_handler);
591 template <
typename ThresholdType,
typename LeafOutputType>
593 Tree<ThresholdType, LeafOutputType>::DeserializeFromFile(FILE* src_fp) {
594 auto scalar_handler = [src_fp](
auto* field) {
595 ReadScalarFromFile(field, src_fp);
597 auto array_handler = [src_fp](
auto* field) {
598 ReadArrayFromFile(field, src_fp);
600 DeserializeTemplate(scalar_handler, array_handler);
603 template <
typename ThresholdType,
typename LeafOutputType>
605 std::memset(
this, 0,
sizeof(
Node));
606 cleft_ = cright_ = -1;
608 info_.leaf_value =
static_cast<LeafOutputType
>(0);
609 info_.threshold =
static_cast<ThresholdType
>(0);
611 sum_hess_ = gain_ = 0.0;
612 data_count_present_ = sum_hess_present_ = gain_present_ =
false;
613 categories_list_right_child_ =
false;
614 split_type_ = SplitFeatureType::kNone;
615 cmp_ = Operator::kNone;
618 template <
typename ThresholdType,
typename LeafOutputType>
621 int nd = num_nodes++;
622 if (nodes_.Size() !=
static_cast<std::size_t
>(nd)) {
623 throw std::runtime_error(
"Invariant violated: nodes_ contains incorrect number of nodes");
625 for (
int nid = nd; nid < num_nodes; ++nid) {
626 leaf_vector_begin_.PushBack(0);
627 leaf_vector_end_.PushBack(0);
628 matching_categories_offset_.PushBack(matching_categories_offset_.Back());
629 nodes_.Resize(nodes_.Size() + 1);
630 nodes_.Back().Init();
635 template <
typename ThresholdType,
typename LeafOutputType>
639 leaf_vector_.Clear();
640 leaf_vector_begin_.Resize(1, {});
641 leaf_vector_end_.Resize(1, {});
642 matching_categories_.Clear();
643 matching_categories_offset_.Resize(2, 0);
646 SetLeaf(0, static_cast<LeafOutputType>(0));
649 template <
typename ThresholdType,
typename LeafOutputType>
652 const int cleft = this->AllocNode();
653 const int cright = this->AllocNode();
654 nodes_.at(nid).cleft_ = cleft;
655 nodes_.at(nid).cright_ = cright;
658 template <
typename ThresholdType,
typename LeafOutputType>
659 inline std::vector<unsigned>
661 std::unordered_map<unsigned, bool> tmp;
662 for (
int nid = 0; nid < num_nodes; ++nid) {
664 if (type != SplitFeatureType::kNone) {
665 const bool flag = (type == SplitFeatureType::kCategorical);
666 const uint32_t split_index = SplitIndex(nid);
667 if (tmp.count(split_index) == 0) {
668 tmp[split_index] = flag;
670 if (tmp[split_index] != flag) {
671 throw std::runtime_error(
"Feature " + std::to_string(split_index) +
672 " cannot be simultaneously be categorical and numerical.");
677 std::vector<unsigned> result;
678 for (
const auto& kv : tmp) {
680 result.push_back(kv.first);
683 std::sort(result.begin(), result.end());
687 template <
typename ThresholdType,
typename LeafOutputType>
690 int nid,
unsigned split_index, ThresholdType threshold,
bool default_left,
Operator cmp) {
691 Node& node = nodes_.at(nid);
692 if (split_index >= ((1U << 31U) - 1)) {
693 throw std::runtime_error(
"split_index too big");
695 if (default_left) split_index |= (1U << 31U);
696 node.sindex_ = split_index;
697 (node.info_).threshold = threshold;
699 node.split_type_ = SplitFeatureType::kNumerical;
700 node.categories_list_right_child_ =
false;
703 template <
typename ThresholdType,
typename LeafOutputType>
706 int nid,
unsigned split_index,
bool default_left,
707 const std::vector<uint32_t>& categories_list,
bool categories_list_right_child) {
708 if (split_index >= ((1U << 31U) - 1)) {
709 throw std::runtime_error(
"split_index too big");
712 const std::size_t end_oft = matching_categories_offset_.Back();
713 const std::size_t new_end_oft = end_oft + categories_list.size();
714 if (end_oft != matching_categories_.Size()) {
715 throw std::runtime_error(
"Invariant violated");
717 if (!std::all_of(&matching_categories_offset_.at(nid + 1), matching_categories_offset_.End(),
718 [end_oft](std::size_t x) {
return (x == end_oft); })) {
719 throw std::runtime_error(
"Invariant violated");
722 matching_categories_.Extend(categories_list);
723 if (new_end_oft != matching_categories_.Size()) {
724 throw std::runtime_error(
"Invariant violated");
726 std::for_each(&matching_categories_offset_.at(nid + 1), matching_categories_offset_.End(),
727 [new_end_oft](std::size_t& x) { x = new_end_oft; });
728 if (!matching_categories_.Empty()) {
729 std::sort(&matching_categories_.at(end_oft), matching_categories_.End());
732 Node& node = nodes_.at(nid);
733 if (default_left) split_index |= (1U << 31U);
734 node.sindex_ = split_index;
735 node.split_type_ = SplitFeatureType::kCategorical;
736 node.categories_list_right_child_ = categories_list_right_child;
739 template <
typename ThresholdType,
typename LeafOutputType>
742 Node& node = nodes_.at(nid);
743 (node.info_).leaf_value = value;
746 node.split_type_ = SplitFeatureType::kNone;
749 template <
typename ThresholdType,
typename LeafOutputType>
752 int nid,
const std::vector<LeafOutputType>& node_leaf_vector) {
753 std::size_t begin = leaf_vector_.Size();
754 std::size_t end = begin + node_leaf_vector.size();
755 leaf_vector_.Extend(node_leaf_vector);
756 leaf_vector_begin_[nid] = begin;
757 leaf_vector_end_[nid] = end;
758 Node &node = nodes_.at(nid);
761 node.split_type_ = SplitFeatureType::kNone;
764 template <
typename ThresholdType,
typename LeafOutputType>
765 inline std::unique_ptr<Model>
767 std::unique_ptr<Model> model = std::make_unique<ModelImpl<ThresholdType, LeafOutputType>>();
768 model->threshold_type_ = TypeToInfo<ThresholdType>();
769 model->leaf_output_type_ = TypeToInfo<LeafOutputType>();
773 template <
typename ThresholdType,
typename LeafOutputType>
776 inline static std::unique_ptr<Model> Dispatch() {
777 return Model::Create<ThresholdType, LeafOutputType>();
781 inline std::unique_ptr<Model>
783 return DispatchWithModelTypes<ModelCreateImpl>(threshold_type, leaf_output_type);
786 template <
typename ThresholdType,
typename LeafOutputType>
789 template <
typename Func>
790 inline static auto Dispatch(
Model* model, Func func) {
794 template <
typename Func>
795 inline static auto Dispatch(
const Model* model, Func func) {
800 template <
typename Func>
802 Model::Dispatch(Func func) {
803 return DispatchWithModelTypes<ModelDispatchImpl>(threshold_type_, leaf_output_type_,
this, func);
806 template <
typename Func>
808 Model::Dispatch(Func func)
const {
809 return DispatchWithModelTypes<ModelDispatchImpl>(threshold_type_, leaf_output_type_,
this, func);
812 template <
typename HeaderPrimitiveFieldHandlerFunc>
814 Model::SerializeTemplate(HeaderPrimitiveFieldHandlerFunc header_primitive_field_handler) {
815 header_primitive_field_handler(&major_ver_);
816 header_primitive_field_handler(&minor_ver_);
817 header_primitive_field_handler(&patch_ver_);
818 header_primitive_field_handler(&threshold_type_);
819 header_primitive_field_handler(&leaf_output_type_);
822 template <
typename HeaderPrimitiveFieldHandlerFunc>
824 Model::DeserializeTemplate(HeaderPrimitiveFieldHandlerFunc header_primitive_field_handler,
826 int major_ver, minor_ver, patch_ver;
827 header_primitive_field_handler(&major_ver);
828 header_primitive_field_handler(&minor_ver);
829 header_primitive_field_handler(&patch_ver);
830 if (major_ver != TREELITE_VER_MAJOR || minor_ver != TREELITE_VER_MINOR) {
831 throw std::runtime_error(
"Cannot deserialize model from a different version of Treelite");
833 header_primitive_field_handler(&threshold_type);
834 header_primitive_field_handler(&leaf_output_type);
837 template <
typename ThresholdType,
typename LeafOutputType>
838 template <
typename HeaderPrimitiveFieldHandlerFunc,
typename HeaderCompositeFieldHandlerFunc,
839 typename TreeHandlerFunc>
842 HeaderPrimitiveFieldHandlerFunc header_primitive_field_handler,
843 HeaderCompositeFieldHandlerFunc header_composite_field_handler,
844 TreeHandlerFunc tree_handler) {
846 header_primitive_field_handler(&num_feature);
847 header_primitive_field_handler(&task_type);
848 header_primitive_field_handler(&average_tree_output);
849 header_composite_field_handler(&task_param,
"T{=B=?xx=I=I}");
850 header_composite_field_handler(
851 ¶m,
"T{" _TREELITE_STR(TREELITE_MAX_PRED_TRANSFORM_LENGTH)
"s=f=f}");
859 template <
typename ThresholdType,
typename LeafOutputType>
860 template <
typename HeaderFieldHandlerFunc,
typename TreeHandlerFunc>
863 std::size_t num_tree,
864 HeaderFieldHandlerFunc header_field_handler,
865 TreeHandlerFunc tree_handler) {
867 header_field_handler(&num_feature);
868 header_field_handler(&task_type);
869 header_field_handler(&average_tree_output);
870 header_field_handler(&task_param);
871 header_field_handler(¶m);
874 for (std::size_t i = 0; i < num_tree; ++i) {
875 trees.emplace_back();
876 tree_handler(trees.back());
880 template <
typename ThresholdType,
typename LeafOutputType>
883 auto header_primitive_field_handler = [dest](
auto* field) {
884 dest->push_back(GetPyBufferFromScalar(field));
886 auto header_composite_field_handler = [dest](
auto* field,
const char* format) {
887 dest->push_back(GetPyBufferFromScalar(field, format));
890 tree.GetPyBuffer(dest);
892 SerializeTemplate(header_primitive_field_handler, header_composite_field_handler, tree_handler);
895 template <
typename ThresholdType,
typename LeafOutputType>
898 const auto num_tree =
static_cast<uint64_t
>(this->trees.size());
899 WriteScalarToFile(&num_tree, dest_fp);
900 auto header_primitive_field_handler = [dest_fp](
auto* field) {
901 WriteScalarToFile(field, dest_fp);
903 auto header_composite_field_handler = [dest_fp](
auto* field,
const char* format) {
904 WriteScalarToFile(field, dest_fp);
907 tree.SerializeToFile(dest_fp);
909 SerializeTemplate(header_primitive_field_handler, header_composite_field_handler, tree_handler);
912 template <
typename ThresholdType,
typename LeafOutputType>
915 std::vector<PyBufferFrame>::iterator begin, std::vector<PyBufferFrame>::iterator end) {
916 const std::size_t num_frame = std::distance(begin, end);
917 constexpr std::size_t kNumFrameInHeader = 5;
918 if (num_frame < kNumFrameInHeader || (num_frame - kNumFrameInHeader) % kNumFramePerTree != 0) {
919 throw std::runtime_error(
"Wrong number of frames");
921 const std::size_t num_tree = (num_frame - kNumFrameInHeader) / kNumFramePerTree;
923 auto header_field_handler = [&begin](
auto* field) {
924 InitScalarFromPyBuffer(field, *begin++);
929 tree.InitFromPyBuffer(begin, begin + kNumFramePerTree);
930 begin += kNumFramePerTree;
934 DeserializeTemplate(num_tree, header_field_handler, tree_handler);
937 template <
typename ThresholdType,
typename LeafOutputType>
941 ReadScalarFromFile(&num_tree, src_fp);
943 auto header_field_handler = [src_fp](
auto* field) {
944 ReadScalarFromFile(field, src_fp);
948 tree.DeserializeFromFile(src_fp);
951 DeserializeTemplate(num_tree, header_field_handler, tree_handler);
954 inline void InitParamAndCheck(
ModelParam* param,
955 const std::vector<std::pair<std::string, std::string>>& cfg) {
956 auto unknown = param->InitAllowUnknown(cfg);
957 if (!unknown.empty()) {
958 std::ostringstream oss;
959 for (
const auto& kv : unknown) {
960 oss << kv.first <<
", ";
962 std::cerr <<
"\033[1;31mWarning: Unknown parameters found; " 963 <<
"they have been ignored\u001B[0m: " << oss.str() << std::endl;
968 #endif // TREELITE_TREE_IMPL_H_ SplitFeatureType
feature split type
void Init()
initialize the model with a single root node
TaskType
Enum type representing the task type.
in-memory representation of a decision tree
TypeInfo
Types used by thresholds and leaf outputs.
thin wrapper for tree ensemble model
Operator
comparison operators