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blender-archive/source/blender/functions/tests/FN_multi_function_procedure_test.cc

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/* SPDX-License-Identifier: Apache-2.0 */
#include "testing/testing.h"
#include "FN_multi_function_builder.hh"
#include "FN_multi_function_procedure_builder.hh"
#include "FN_multi_function_procedure_executor.hh"
#include "FN_multi_function_test_common.hh"
namespace blender::fn::multi_function::tests {
Geometry Nodes: refactor virtual array system Goals of this refactor: * Simplify creating virtual arrays. * Simplify passing virtual arrays around. * Simplify converting between typed and generic virtual arrays. * Reduce memory allocations. As a quick reminder, a virtual arrays is a data structure that behaves like an array (i.e. it can be accessed using an index). However, it may not actually be stored as array internally. The two most important implementations of virtual arrays are those that correspond to an actual plain array and those that have the same value for every index. However, many more implementations exist for various reasons (interfacing with legacy attributes, unified iterator over all points in multiple splines, ...). With this refactor the core types (`VArray`, `GVArray`, `VMutableArray` and `GVMutableArray`) can be used like "normal values". They typically live on the stack. Before, they were usually inside a `std::unique_ptr`. This makes passing them around much easier. Creation of new virtual arrays is also much simpler now due to some constructors. Memory allocations are reduced by making use of small object optimization inside the core types. Previously, `VArray` was a class with virtual methods that had to be overridden to change the behavior of a the virtual array. Now,`VArray` has a fixed size and has no virtual methods. Instead it contains a `VArrayImpl` that is similar to the old `VArray`. `VArrayImpl` should rarely ever be used directly, unless a new virtual array implementation is added. To support the small object optimization for many `VArrayImpl` classes, a new `blender::Any` type is added. It is similar to `std::any` with two additional features. It has an adjustable inline buffer size and alignment. The inline buffer size of `std::any` can't be relied on and is usually too small for our use case here. Furthermore, `blender::Any` can store additional user-defined type information without increasing the stack size. Differential Revision: https://developer.blender.org/D12986
2021-11-16 10:15:51 +01:00
TEST(multi_function_procedure, ConstantOutput)
{
/**
* procedure(int *var2) {
* var1 = 5;
* var2 = var1 + var1;
* }
*/
CustomMF_Constant<int> constant_fn{5};
auto add_fn = build::SI2_SO<int, int, int>("Add", [](int a, int b) { return a + b; });
Geometry Nodes: refactor virtual array system Goals of this refactor: * Simplify creating virtual arrays. * Simplify passing virtual arrays around. * Simplify converting between typed and generic virtual arrays. * Reduce memory allocations. As a quick reminder, a virtual arrays is a data structure that behaves like an array (i.e. it can be accessed using an index). However, it may not actually be stored as array internally. The two most important implementations of virtual arrays are those that correspond to an actual plain array and those that have the same value for every index. However, many more implementations exist for various reasons (interfacing with legacy attributes, unified iterator over all points in multiple splines, ...). With this refactor the core types (`VArray`, `GVArray`, `VMutableArray` and `GVMutableArray`) can be used like "normal values". They typically live on the stack. Before, they were usually inside a `std::unique_ptr`. This makes passing them around much easier. Creation of new virtual arrays is also much simpler now due to some constructors. Memory allocations are reduced by making use of small object optimization inside the core types. Previously, `VArray` was a class with virtual methods that had to be overridden to change the behavior of a the virtual array. Now,`VArray` has a fixed size and has no virtual methods. Instead it contains a `VArrayImpl` that is similar to the old `VArray`. `VArrayImpl` should rarely ever be used directly, unless a new virtual array implementation is added. To support the small object optimization for many `VArrayImpl` classes, a new `blender::Any` type is added. It is similar to `std::any` with two additional features. It has an adjustable inline buffer size and alignment. The inline buffer size of `std::any` can't be relied on and is usually too small for our use case here. Furthermore, `blender::Any` can store additional user-defined type information without increasing the stack size. Differential Revision: https://developer.blender.org/D12986
2021-11-16 10:15:51 +01:00
Procedure procedure;
ProcedureBuilder builder{procedure};
Geometry Nodes: refactor virtual array system Goals of this refactor: * Simplify creating virtual arrays. * Simplify passing virtual arrays around. * Simplify converting between typed and generic virtual arrays. * Reduce memory allocations. As a quick reminder, a virtual arrays is a data structure that behaves like an array (i.e. it can be accessed using an index). However, it may not actually be stored as array internally. The two most important implementations of virtual arrays are those that correspond to an actual plain array and those that have the same value for every index. However, many more implementations exist for various reasons (interfacing with legacy attributes, unified iterator over all points in multiple splines, ...). With this refactor the core types (`VArray`, `GVArray`, `VMutableArray` and `GVMutableArray`) can be used like "normal values". They typically live on the stack. Before, they were usually inside a `std::unique_ptr`. This makes passing them around much easier. Creation of new virtual arrays is also much simpler now due to some constructors. Memory allocations are reduced by making use of small object optimization inside the core types. Previously, `VArray` was a class with virtual methods that had to be overridden to change the behavior of a the virtual array. Now,`VArray` has a fixed size and has no virtual methods. Instead it contains a `VArrayImpl` that is similar to the old `VArray`. `VArrayImpl` should rarely ever be used directly, unless a new virtual array implementation is added. To support the small object optimization for many `VArrayImpl` classes, a new `blender::Any` type is added. It is similar to `std::any` with two additional features. It has an adjustable inline buffer size and alignment. The inline buffer size of `std::any` can't be relied on and is usually too small for our use case here. Furthermore, `blender::Any` can store additional user-defined type information without increasing the stack size. Differential Revision: https://developer.blender.org/D12986
2021-11-16 10:15:51 +01:00
auto [var1] = builder.add_call<1>(constant_fn);
auto [var2] = builder.add_call<1>(add_fn, {var1, var1});
builder.add_destruct(*var1);
builder.add_return();
builder.add_output_parameter(*var2);
EXPECT_TRUE(procedure.validate());
ProcedureExecutor executor{procedure};
Geometry Nodes: refactor virtual array system Goals of this refactor: * Simplify creating virtual arrays. * Simplify passing virtual arrays around. * Simplify converting between typed and generic virtual arrays. * Reduce memory allocations. As a quick reminder, a virtual arrays is a data structure that behaves like an array (i.e. it can be accessed using an index). However, it may not actually be stored as array internally. The two most important implementations of virtual arrays are those that correspond to an actual plain array and those that have the same value for every index. However, many more implementations exist for various reasons (interfacing with legacy attributes, unified iterator over all points in multiple splines, ...). With this refactor the core types (`VArray`, `GVArray`, `VMutableArray` and `GVMutableArray`) can be used like "normal values". They typically live on the stack. Before, they were usually inside a `std::unique_ptr`. This makes passing them around much easier. Creation of new virtual arrays is also much simpler now due to some constructors. Memory allocations are reduced by making use of small object optimization inside the core types. Previously, `VArray` was a class with virtual methods that had to be overridden to change the behavior of a the virtual array. Now,`VArray` has a fixed size and has no virtual methods. Instead it contains a `VArrayImpl` that is similar to the old `VArray`. `VArrayImpl` should rarely ever be used directly, unless a new virtual array implementation is added. To support the small object optimization for many `VArrayImpl` classes, a new `blender::Any` type is added. It is similar to `std::any` with two additional features. It has an adjustable inline buffer size and alignment. The inline buffer size of `std::any` can't be relied on and is usually too small for our use case here. Furthermore, `blender::Any` can store additional user-defined type information without increasing the stack size. Differential Revision: https://developer.blender.org/D12986
2021-11-16 10:15:51 +01:00
ParamsBuilder params{executor, 2};
ContextBuilder context;
Geometry Nodes: refactor virtual array system Goals of this refactor: * Simplify creating virtual arrays. * Simplify passing virtual arrays around. * Simplify converting between typed and generic virtual arrays. * Reduce memory allocations. As a quick reminder, a virtual arrays is a data structure that behaves like an array (i.e. it can be accessed using an index). However, it may not actually be stored as array internally. The two most important implementations of virtual arrays are those that correspond to an actual plain array and those that have the same value for every index. However, many more implementations exist for various reasons (interfacing with legacy attributes, unified iterator over all points in multiple splines, ...). With this refactor the core types (`VArray`, `GVArray`, `VMutableArray` and `GVMutableArray`) can be used like "normal values". They typically live on the stack. Before, they were usually inside a `std::unique_ptr`. This makes passing them around much easier. Creation of new virtual arrays is also much simpler now due to some constructors. Memory allocations are reduced by making use of small object optimization inside the core types. Previously, `VArray` was a class with virtual methods that had to be overridden to change the behavior of a the virtual array. Now,`VArray` has a fixed size and has no virtual methods. Instead it contains a `VArrayImpl` that is similar to the old `VArray`. `VArrayImpl` should rarely ever be used directly, unless a new virtual array implementation is added. To support the small object optimization for many `VArrayImpl` classes, a new `blender::Any` type is added. It is similar to `std::any` with two additional features. It has an adjustable inline buffer size and alignment. The inline buffer size of `std::any` can't be relied on and is usually too small for our use case here. Furthermore, `blender::Any` can store additional user-defined type information without increasing the stack size. Differential Revision: https://developer.blender.org/D12986
2021-11-16 10:15:51 +01:00
Array<int> output_array(2);
params.add_uninitialized_single_output(output_array.as_mutable_span());
executor.call(IndexRange(2), params, context);
EXPECT_EQ(output_array[0], 10);
EXPECT_EQ(output_array[1], 10);
}
TEST(multi_function_procedure, SimpleTest)
{
/**
* procedure(int var1, int var2, int *var4) {
* int var3 = var1 + var2;
* var4 = var2 + var3;
* var4 += 10;
* }
*/
auto add_fn = mf::build::SI2_SO<int, int, int>("add", [](int a, int b) { return a + b; });
auto add_10_fn = mf::build::SM<int>("add_10", [](int &a) { a += 10; });
Procedure procedure;
ProcedureBuilder builder{procedure};
Variable *var1 = &builder.add_single_input_parameter<int>();
Variable *var2 = &builder.add_single_input_parameter<int>();
auto [var3] = builder.add_call<1>(add_fn, {var1, var2});
auto [var4] = builder.add_call<1>(add_fn, {var2, var3});
builder.add_call(add_10_fn, {var4});
builder.add_destruct({var1, var2, var3});
builder.add_return();
builder.add_output_parameter(*var4);
EXPECT_TRUE(procedure.validate());
ProcedureExecutor executor{procedure};
ParamsBuilder params{executor, 3};
ContextBuilder context;
Array<int> input_array = {1, 2, 3};
params.add_readonly_single_input(input_array.as_span());
params.add_readonly_single_input_value(3);
Array<int> output_array(3);
params.add_uninitialized_single_output(output_array.as_mutable_span());
executor.call(IndexRange(3), params, context);
EXPECT_EQ(output_array[0], 17);
EXPECT_EQ(output_array[1], 18);
EXPECT_EQ(output_array[2], 19);
}
TEST(multi_function_procedure, BranchTest)
{
/**
* procedure(int &var1, bool var2) {
* if (var2) {
* var1 += 100;
* }
* else {
* var1 += 10;
* }
* var1 += 10;
* }
*/
auto add_10_fn = build::SM<int>("add_10", [](int &a) { a += 10; });
auto add_100_fn = build::SM<int>("add_100", [](int &a) { a += 100; });
Procedure procedure;
ProcedureBuilder builder{procedure};
Variable *var1 = &builder.add_single_mutable_parameter<int>();
Variable *var2 = &builder.add_single_input_parameter<bool>();
ProcedureBuilder::Branch branch = builder.add_branch(*var2);
branch.branch_false.add_call(add_10_fn, {var1});
branch.branch_true.add_call(add_100_fn, {var1});
builder.set_cursor_after_branch(branch);
builder.add_call(add_10_fn, {var1});
builder.add_destruct({var2});
builder.add_return();
EXPECT_TRUE(procedure.validate());
ProcedureExecutor procedure_fn{procedure};
ParamsBuilder params(procedure_fn, 5);
Array<int> values_a = {1, 5, 3, 6, 2};
Array<bool> values_cond = {true, false, true, true, false};
params.add_single_mutable(values_a.as_mutable_span());
params.add_readonly_single_input(values_cond.as_span());
ContextBuilder context;
procedure_fn.call({1, 2, 3, 4}, params, context);
EXPECT_EQ(values_a[0], 1);
EXPECT_EQ(values_a[1], 25);
EXPECT_EQ(values_a[2], 113);
EXPECT_EQ(values_a[3], 116);
EXPECT_EQ(values_a[4], 22);
}
TEST(multi_function_procedure, EvaluateOne)
{
/**
* procedure(int var1, int *var2) {
* var2 = var1 + 10;
* }
*/
int tot_evaluations = 0;
const auto add_10_fn = mf::build::SI1_SO<int, int>("add_10", [&](int a) {
tot_evaluations++;
return a + 10;
});
Procedure procedure;
ProcedureBuilder builder{procedure};
Variable *var1 = &builder.add_single_input_parameter<int>();
auto [var2] = builder.add_call<1>(add_10_fn, {var1});
builder.add_destruct(*var1);
builder.add_return();
builder.add_output_parameter(*var2);
ProcedureExecutor procedure_fn{procedure};
ParamsBuilder params{procedure_fn, 5};
Array<int> values_out = {1, 2, 3, 4, 5};
params.add_readonly_single_input_value(1);
params.add_uninitialized_single_output(values_out.as_mutable_span());
ContextBuilder context;
procedure_fn.call({0, 1, 3, 4}, params, context);
EXPECT_EQ(values_out[0], 11);
EXPECT_EQ(values_out[1], 11);
EXPECT_EQ(values_out[2], 3);
EXPECT_EQ(values_out[3], 11);
EXPECT_EQ(values_out[4], 11);
/* We expect only one evaluation, because the input is constant. */
EXPECT_EQ(tot_evaluations, 1);
}
TEST(multi_function_procedure, SimpleLoop)
{
/**
* procedure(int count, int *out) {
* out = 1;
* int index = 0'
* loop {
* if (index >= count) {
* break;
* }
* out *= 2;
* index += 1;
* }
* out += 1000;
* }
*/
CustomMF_Constant<int> const_1_fn{1};
CustomMF_Constant<int> const_0_fn{0};
auto greater_or_equal_fn = mf::build::SI2_SO<int, int, bool>(
"greater or equal", [](int a, int b) { return a >= b; });
auto double_fn = build::SM<int>("double", [](int &a) { a *= 2; });
auto add_1000_fn = build::SM<int>("add 1000", [](int &a) { a += 1000; });
auto add_1_fn = build::SM<int>("add 1", [](int &a) { a += 1; });
Procedure procedure;
ProcedureBuilder builder{procedure};
Variable *var_count = &builder.add_single_input_parameter<int>("count");
auto [var_out] = builder.add_call<1>(const_1_fn);
var_out->set_name("out");
auto [var_index] = builder.add_call<1>(const_0_fn);
var_index->set_name("index");
ProcedureBuilder::Loop loop = builder.add_loop();
auto [var_condition] = builder.add_call<1>(greater_or_equal_fn, {var_index, var_count});
var_condition->set_name("condition");
ProcedureBuilder::Branch branch = builder.add_branch(*var_condition);
branch.branch_true.add_destruct(*var_condition);
branch.branch_true.add_loop_break(loop);
branch.branch_false.add_destruct(*var_condition);
builder.set_cursor_after_branch(branch);
builder.add_call(double_fn, {var_out});
builder.add_call(add_1_fn, {var_index});
builder.add_loop_continue(loop);
builder.set_cursor_after_loop(loop);
builder.add_call(add_1000_fn, {var_out});
builder.add_destruct({var_count, var_index});
builder.add_return();
builder.add_output_parameter(*var_out);
EXPECT_TRUE(procedure.validate());
ProcedureExecutor procedure_fn{procedure};
ParamsBuilder params{procedure_fn, 5};
Array<int> counts = {4, 3, 7, 6, 4};
Array<int> results(5, -1);
params.add_readonly_single_input(counts.as_span());
params.add_uninitialized_single_output(results.as_mutable_span());
ContextBuilder context;
procedure_fn.call({0, 1, 3, 4}, params, context);
EXPECT_EQ(results[0], 1016);
EXPECT_EQ(results[1], 1008);
EXPECT_EQ(results[2], -1);
EXPECT_EQ(results[3], 1064);
EXPECT_EQ(results[4], 1016);
}
TEST(multi_function_procedure, Vectors)
{
/**
* procedure(vector<int> v1, vector<int> &v2, vector<int> *v3) {
* v1.extend(v2);
* int constant = 5;
* v2.append(constant);
* v2.extend(v1);
* int len = sum(v2);
* v3 = range(len);
* }
*/
CreateRangeFunction create_range_fn;
ConcatVectorsFunction extend_fn;
GenericAppendFunction append_fn{CPPType::get<int>()};
SumVectorFunction sum_elements_fn;
CustomMF_Constant<int> constant_5_fn{5};
Procedure procedure;
ProcedureBuilder builder{procedure};
Variable *var_v1 = &builder.add_input_parameter(DataType::ForVector<int>());
Variable *var_v2 = &builder.add_parameter(ParamType::ForMutableVector(CPPType::get<int>()));
builder.add_call(extend_fn, {var_v1, var_v2});
auto [var_constant] = builder.add_call<1>(constant_5_fn);
builder.add_call(append_fn, {var_v2, var_constant});
builder.add_destruct(*var_constant);
builder.add_call(extend_fn, {var_v2, var_v1});
auto [var_len] = builder.add_call<1>(sum_elements_fn, {var_v2});
auto [var_v3] = builder.add_call<1>(create_range_fn, {var_len});
builder.add_destruct({var_v1, var_len});
builder.add_return();
builder.add_output_parameter(*var_v3);
EXPECT_TRUE(procedure.validate());
ProcedureExecutor procedure_fn{procedure};
ParamsBuilder params{procedure_fn, 5};
Array<int> v1 = {5, 2, 3};
GVectorArray v2{CPPType::get<int>(), 5};
GVectorArray v3{CPPType::get<int>(), 5};
int value_10 = 10;
v2.append(0, &value_10);
v2.append(4, &value_10);
params.add_readonly_vector_input(v1.as_span());
params.add_vector_mutable(v2);
params.add_vector_output(v3);
ContextBuilder context;
procedure_fn.call({0, 1, 3, 4}, params, context);
EXPECT_EQ(v2[0].size(), 6);
EXPECT_EQ(v2[1].size(), 4);
EXPECT_EQ(v2[2].size(), 0);
EXPECT_EQ(v2[3].size(), 4);
EXPECT_EQ(v2[4].size(), 6);
EXPECT_EQ(v3[0].size(), 35);
EXPECT_EQ(v3[1].size(), 15);
EXPECT_EQ(v3[2].size(), 0);
EXPECT_EQ(v3[3].size(), 15);
EXPECT_EQ(v3[4].size(), 35);
}
TEST(multi_function_procedure, BufferReuse)
{
/**
* procedure(int a, int *out) {
* int b = a + 10;
* int c = c + 10;
* int d = d + 10;
* int e = d + 10;
* out = e + 10;
* }
*/
auto add_10_fn = build::SI1_SO<int, int>("add 10", [](int a) { return a + 10; });
Procedure procedure;
ProcedureBuilder builder{procedure};
Variable *var_a = &builder.add_single_input_parameter<int>();
auto [var_b] = builder.add_call<1>(add_10_fn, {var_a});
builder.add_destruct(*var_a);
auto [var_c] = builder.add_call<1>(add_10_fn, {var_b});
builder.add_destruct(*var_b);
auto [var_d] = builder.add_call<1>(add_10_fn, {var_c});
builder.add_destruct(*var_c);
auto [var_e] = builder.add_call<1>(add_10_fn, {var_d});
builder.add_destruct(*var_d);
auto [var_out] = builder.add_call<1>(add_10_fn, {var_e});
builder.add_destruct(*var_e);
builder.add_return();
builder.add_output_parameter(*var_out);
EXPECT_TRUE(procedure.validate());
ProcedureExecutor procedure_fn{procedure};
Array<int> inputs = {4, 1, 6, 2, 3};
Array<int> results(5, -1);
ParamsBuilder params{procedure_fn, 5};
params.add_readonly_single_input(inputs.as_span());
params.add_uninitialized_single_output(results.as_mutable_span());
ContextBuilder context;
procedure_fn.call({0, 2, 3, 4}, params, context);
EXPECT_EQ(results[0], 54);
EXPECT_EQ(results[1], -1);
EXPECT_EQ(results[2], 56);
EXPECT_EQ(results[3], 52);
EXPECT_EQ(results[4], 53);
}
TEST(multi_function_procedure, OutputBufferReplaced)
{
Procedure procedure;
ProcedureBuilder builder{procedure};
const int output_value = 42;
CustomMF_GenericConstant constant_fn(CPPType::get<int>(), &output_value, false);
Variable &var_o = procedure.new_variable(DataType::ForSingle<int>());
builder.add_output_parameter(var_o);
builder.add_call_with_all_variables(constant_fn, {&var_o});
builder.add_destruct(var_o);
builder.add_call_with_all_variables(constant_fn, {&var_o});
builder.add_return();
EXPECT_TRUE(procedure.validate());
ProcedureExecutor procedure_fn{procedure};
Array<int> output(3, 0);
mf::ParamsBuilder params(procedure_fn, output.size());
params.add_uninitialized_single_output(output.as_mutable_span());
mf::ContextBuilder context;
procedure_fn.call(IndexMask(output.size()), params, context);
EXPECT_EQ(output[0], output_value);
EXPECT_EQ(output[1], output_value);
EXPECT_EQ(output[2], output_value);
}
} // namespace blender::fn::multi_function::tests