Goals of this refactor: * Reduce memory consumption of `IndexMask`. The old `IndexMask` uses an `int64_t` for each index which is more than necessary in pretty much all practical cases currently. Using `int32_t` might still become limiting in the future in case we use this to index e.g. byte buffers larger than a few gigabytes. We also don't want to template `IndexMask`, because that would cause a split in the "ecosystem", or everything would have to be implemented twice or templated. * Allow for more multi-threading. The old `IndexMask` contains a single array. This is generally good but has the problem that it is hard to fill from multiple-threads when the final size is not known from the beginning. This is commonly the case when e.g. converting an array of bool to an index mask. Currently, this kind of code only runs on a single thread. * Allow for efficient set operations like join, intersect and difference. It should be possible to multi-thread those operations. * It should be possible to iterate over an `IndexMask` very efficiently. The most important part of that is to avoid all memory access when iterating over continuous ranges. For some core nodes (e.g. math nodes), we generate optimized code for the cases of irregular index masks and simple index ranges. To achieve these goals, a few compromises had to made: * Slicing of the mask (at specific indices) and random element access is `O(log #indices)` now, but with a low constant factor. It should be possible to split a mask into n approximately equally sized parts in `O(n)` though, making the time per split `O(1)`. * Using range-based for loops does not work well when iterating over a nested data structure like the new `IndexMask`. Therefor, `foreach_*` functions with callbacks have to be used. To avoid extra code complexity at the call site, the `foreach_*` methods support multi-threading out of the box. The new data structure splits an `IndexMask` into an arbitrary number of ordered `IndexMaskSegment`. Each segment can contain at most `2^14 = 16384` indices. The indices within a segment are stored as `int16_t`. Each segment has an additional `int64_t` offset which allows storing arbitrary `int64_t` indices. This approach has the main benefits that segments can be processed/constructed individually on multiple threads without a serial bottleneck. Also it reduces the memory requirements significantly. For more details see comments in `BLI_index_mask.hh`. I did a few tests to verify that the data structure generally improves performance and does not cause regressions: * Our field evaluation benchmarks take about as much as before. This is to be expected because we already made sure that e.g. add node evaluation is vectorized. The important thing here is to check that changes to the way we iterate over the indices still allows for auto-vectorization. * Memory usage by a mask is about 1/4 of what it was before in the average case. That's mainly caused by the switch from `int64_t` to `int16_t` for indices. In the worst case, the memory requirements can be larger when there are many indices that are very far away. However, when they are far away from each other, that indicates that there aren't many indices in total. In common cases, memory usage can be way lower than 1/4 of before, because sub-ranges use static memory. * For some more specific numbers I benchmarked `IndexMask::from_bools` in `index_mask_from_selection` on 10.000.000 elements at various probabilities for `true` at every index: ``` Probability Old New 0 4.6 ms 0.8 ms 0.001 5.1 ms 1.3 ms 0.2 8.4 ms 1.8 ms 0.5 15.3 ms 3.0 ms 0.8 20.1 ms 3.0 ms 0.999 25.1 ms 1.7 ms 1 13.5 ms 1.1 ms ``` Pull Request: https://projects.blender.org/blender/blender/pulls/104629
356 lines
13 KiB
C++
356 lines
13 KiB
C++
/* SPDX-License-Identifier: GPL-2.0-or-later */
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#pragma once
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/** \file
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* \ingroup fn
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*
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* This file provides an Params and ParamsBuilder structure.
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*
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* `ParamsBuilder` is used by a function caller to be prepare all parameters that are passed into
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* the function. `Params` is then used inside the called function to access the parameters.
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*/
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#include <mutex>
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#include <variant>
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#include "BLI_generic_pointer.hh"
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#include "BLI_generic_vector_array.hh"
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#include "BLI_generic_virtual_vector_array.hh"
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#include "BLI_resource_scope.hh"
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#include "FN_multi_function_signature.hh"
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namespace blender::fn::multi_function {
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class ParamsBuilder {
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private:
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std::unique_ptr<ResourceScope> scope_;
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const Signature *signature_;
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const IndexMask &mask_;
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int64_t min_array_size_;
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Vector<std::variant<GVArray, GMutableSpan, const GVVectorArray *, GVectorArray *>>
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actual_params_;
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friend class Params;
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ParamsBuilder(const Signature &signature, const IndexMask &mask)
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: signature_(&signature), mask_(mask), min_array_size_(mask.min_array_size())
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{
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actual_params_.reserve(signature.params.size());
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}
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public:
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/**
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* The indices referenced by the #mask has to live longer than the params builder. This is
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* because the it might have to destruct elements for all masked indices in the end.
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*/
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ParamsBuilder(const class MultiFunction &fn, const IndexMask *mask);
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template<typename T> void add_readonly_single_input_value(T value, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForSingleInput(CPPType::get<T>()), expected_name);
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actual_params_.append_unchecked_as(std::in_place_type<GVArray>,
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varray_tag::single{},
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CPPType::get<T>(),
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min_array_size_,
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&value);
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}
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template<typename T> void add_readonly_single_input(const T *value, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForSingleInput(CPPType::get<T>()), expected_name);
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actual_params_.append_unchecked_as(std::in_place_type<GVArray>,
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varray_tag::single_ref{},
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CPPType::get<T>(),
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min_array_size_,
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value);
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}
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void add_readonly_single_input(const GSpan span, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForSingleInput(span.type()), expected_name);
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BLI_assert(span.size() >= min_array_size_);
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actual_params_.append_unchecked_as(std::in_place_type<GVArray>, varray_tag::span{}, span);
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}
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void add_readonly_single_input(GPointer value, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForSingleInput(*value.type()), expected_name);
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actual_params_.append_unchecked_as(std::in_place_type<GVArray>,
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varray_tag::single_ref{},
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*value.type(),
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min_array_size_,
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value.get());
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}
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void add_readonly_single_input(GVArray varray, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForSingleInput(varray.type()), expected_name);
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BLI_assert(varray.size() >= min_array_size_);
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actual_params_.append_unchecked_as(std::in_place_type<GVArray>, std::move(varray));
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}
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void add_readonly_vector_input(const GVectorArray &vector_array, StringRef expected_name = "")
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{
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this->add_readonly_vector_input(
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this->resource_scope().construct<GVVectorArray_For_GVectorArray>(vector_array),
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expected_name);
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}
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void add_readonly_vector_input(const GSpan single_vector, StringRef expected_name = "")
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{
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this->add_readonly_vector_input(
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this->resource_scope().construct<GVVectorArray_For_SingleGSpan>(single_vector,
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min_array_size_),
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expected_name);
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}
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void add_readonly_vector_input(const GVVectorArray &ref, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForVectorInput(ref.type()), expected_name);
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BLI_assert(ref.size() >= min_array_size_);
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actual_params_.append_unchecked_as(std::in_place_type<const GVVectorArray *>, &ref);
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}
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template<typename T> void add_uninitialized_single_output(T *value, StringRef expected_name = "")
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{
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this->add_uninitialized_single_output(GMutableSpan(CPPType::get<T>(), value, 1),
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expected_name);
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}
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void add_uninitialized_single_output(GMutableSpan ref, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForSingleOutput(ref.type()), expected_name);
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BLI_assert(ref.size() >= min_array_size_);
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actual_params_.append_unchecked_as(std::in_place_type<GMutableSpan>, ref);
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}
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void add_ignored_single_output(StringRef expected_name = "")
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{
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this->assert_current_param_name(expected_name);
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const int param_index = this->current_param_index();
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const ParamType ¶m_type = signature_->params[param_index].type;
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BLI_assert(param_type.category() == ParamCategory::SingleOutput);
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const DataType data_type = param_type.data_type();
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const CPPType &type = data_type.single_type();
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if (bool(signature_->params[param_index].flag & ParamFlag::SupportsUnusedOutput)) {
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/* An empty span indicates that this is ignored. */
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const GMutableSpan dummy_span{type};
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actual_params_.append_unchecked_as(std::in_place_type<GMutableSpan>, dummy_span);
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}
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else {
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this->add_unused_output_for_unsupporting_function(type);
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}
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}
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void add_vector_output(GVectorArray &vector_array, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForVectorOutput(vector_array.type()),
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expected_name);
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BLI_assert(vector_array.size() >= min_array_size_);
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actual_params_.append_unchecked_as(std::in_place_type<GVectorArray *>, &vector_array);
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}
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void add_single_mutable(GMutableSpan ref, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForMutableSingle(ref.type()), expected_name);
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BLI_assert(ref.size() >= min_array_size_);
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actual_params_.append_unchecked_as(std::in_place_type<GMutableSpan>, ref);
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}
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void add_vector_mutable(GVectorArray &vector_array, StringRef expected_name = "")
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{
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this->assert_current_param_type(ParamType::ForMutableVector(vector_array.type()),
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expected_name);
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BLI_assert(vector_array.size() >= min_array_size_);
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actual_params_.append_unchecked_as(std::in_place_type<GVectorArray *>, &vector_array);
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}
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GMutableSpan computed_array(int param_index)
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{
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BLI_assert(ELEM(signature_->params[param_index].type.category(),
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ParamCategory::SingleOutput,
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ParamCategory::SingleMutable));
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return std::get<GMutableSpan>(actual_params_[param_index]);
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}
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GVectorArray &computed_vector_array(int param_index)
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{
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BLI_assert(ELEM(signature_->params[param_index].type.category(),
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ParamCategory::VectorOutput,
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ParamCategory::VectorMutable));
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return *std::get<GVectorArray *>(actual_params_[param_index]);
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}
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private:
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void assert_current_param_type(ParamType param_type, StringRef expected_name = "")
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{
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UNUSED_VARS_NDEBUG(param_type, expected_name);
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#ifdef DEBUG
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int param_index = this->current_param_index();
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if (expected_name != "") {
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StringRef actual_name = signature_->params[param_index].name;
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BLI_assert(actual_name == expected_name);
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}
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ParamType expected_type = signature_->params[param_index].type;
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BLI_assert(expected_type == param_type);
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#endif
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}
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void assert_current_param_name(StringRef expected_name)
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{
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UNUSED_VARS_NDEBUG(expected_name);
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#ifdef DEBUG
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if (expected_name.is_empty()) {
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return;
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}
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const int param_index = this->current_param_index();
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StringRef actual_name = signature_->params[param_index].name;
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BLI_assert(actual_name == expected_name);
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#endif
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}
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int current_param_index() const
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{
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return actual_params_.size();
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}
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ResourceScope &resource_scope()
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{
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if (!scope_) {
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scope_ = std::make_unique<ResourceScope>();
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}
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return *scope_;
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}
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void add_unused_output_for_unsupporting_function(const CPPType &type);
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};
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class Params {
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private:
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ParamsBuilder *builder_;
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public:
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Params(ParamsBuilder &builder) : builder_(&builder) {}
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template<typename T> VArray<T> readonly_single_input(int param_index, StringRef name = "")
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{
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const GVArray &varray = this->readonly_single_input(param_index, name);
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return varray.typed<T>();
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}
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const GVArray &readonly_single_input(int param_index, StringRef name = "")
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{
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this->assert_correct_param(param_index, name, ParamCategory::SingleInput);
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return std::get<GVArray>(builder_->actual_params_[param_index]);
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}
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/**
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* \return True when the caller provided a buffer for this output parameter. This allows the
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* called multi-function to skip some computation. It is still valid to call
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* #uninitialized_single_output when this returns false. In this case a new temporary buffer is
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* allocated.
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*/
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bool single_output_is_required(int param_index, StringRef name = "")
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{
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this->assert_correct_param(param_index, name, ParamCategory::SingleOutput);
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return !std::get<GMutableSpan>(builder_->actual_params_[param_index]).is_empty();
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}
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template<typename T>
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MutableSpan<T> uninitialized_single_output(int param_index, StringRef name = "")
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{
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return this->uninitialized_single_output(param_index, name).typed<T>();
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}
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GMutableSpan uninitialized_single_output(int param_index, StringRef name = "")
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{
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this->assert_correct_param(param_index, name, ParamCategory::SingleOutput);
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BLI_assert(
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!bool(builder_->signature_->params[param_index].flag & ParamFlag::SupportsUnusedOutput));
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GMutableSpan span = std::get<GMutableSpan>(builder_->actual_params_[param_index]);
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BLI_assert(span.size() >= builder_->min_array_size_);
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return span;
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}
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/**
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* Same as #uninitialized_single_output, but returns an empty span when the output is not
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* required.
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*/
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template<typename T>
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MutableSpan<T> uninitialized_single_output_if_required(int param_index, StringRef name = "")
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{
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return this->uninitialized_single_output_if_required(param_index, name).typed<T>();
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}
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GMutableSpan uninitialized_single_output_if_required(int param_index, StringRef name = "")
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{
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this->assert_correct_param(param_index, name, ParamCategory::SingleOutput);
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BLI_assert(
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bool(builder_->signature_->params[param_index].flag & ParamFlag::SupportsUnusedOutput));
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return std::get<GMutableSpan>(builder_->actual_params_[param_index]);
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}
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template<typename T>
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const VVectorArray<T> &readonly_vector_input(int param_index, StringRef name = "")
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{
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const GVVectorArray &vector_array = this->readonly_vector_input(param_index, name);
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return builder_->resource_scope().construct<VVectorArray_For_GVVectorArray<T>>(vector_array);
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}
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const GVVectorArray &readonly_vector_input(int param_index, StringRef name = "")
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{
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this->assert_correct_param(param_index, name, ParamCategory::VectorInput);
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return *std::get<const GVVectorArray *>(builder_->actual_params_[param_index]);
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}
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template<typename T>
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GVectorArray_TypedMutableRef<T> vector_output(int param_index, StringRef name = "")
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{
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return {this->vector_output(param_index, name)};
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}
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GVectorArray &vector_output(int param_index, StringRef name = "")
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{
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this->assert_correct_param(param_index, name, ParamCategory::VectorOutput);
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return *std::get<GVectorArray *>(builder_->actual_params_[param_index]);
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}
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template<typename T> MutableSpan<T> single_mutable(int param_index, StringRef name = "")
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{
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return this->single_mutable(param_index, name).typed<T>();
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}
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GMutableSpan single_mutable(int param_index, StringRef name = "")
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{
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this->assert_correct_param(param_index, name, ParamCategory::SingleMutable);
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return std::get<GMutableSpan>(builder_->actual_params_[param_index]);
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}
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template<typename T>
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GVectorArray_TypedMutableRef<T> vector_mutable(int param_index, StringRef name = "")
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{
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return {this->vector_mutable(param_index, name)};
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}
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GVectorArray &vector_mutable(int param_index, StringRef name = "")
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{
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this->assert_correct_param(param_index, name, ParamCategory::VectorMutable);
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return *std::get<GVectorArray *>(builder_->actual_params_[param_index]);
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}
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private:
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void assert_correct_param(int param_index, StringRef name, ParamType param_type)
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{
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UNUSED_VARS_NDEBUG(param_index, name, param_type);
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#ifdef DEBUG
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BLI_assert(builder_->signature_->params[param_index].type == param_type);
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if (name.size() > 0) {
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BLI_assert(builder_->signature_->params[param_index].name == name);
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}
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#endif
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}
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void assert_correct_param(int param_index, StringRef name, ParamCategory category)
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{
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UNUSED_VARS_NDEBUG(param_index, name, category);
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#ifdef DEBUG
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BLI_assert(builder_->signature_->params[param_index].type.category() == category);
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if (name.size() > 0) {
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BLI_assert(builder_->signature_->params[param_index].name == name);
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}
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#endif
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}
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};
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} // namespace blender::fn::multi_function
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