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gen_policy.cpp
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/*
Copyright (c) 2015-2020, Intel Corporation
Copyright (c) 2019-2020, University of Utah
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
//////////////////////////////////////////////////////////////////////////////
#include "gen_policy.h"
#include "options.h"
using namespace yarpgen;
size_t GenPolicy::leaves_prob_bump = 30;
template <typename T>
static void shuffleProbProxy(std::vector<Probability<T>> &vec) {
Options &options = Options::getInstance();
if (!options.getUseParamShuffle())
return;
rand_val_gen->shuffleProb(vec);
}
GenPolicy::GenPolicy() {
Options &options = Options::getInstance();
stmt_num_lim = 1000;
loop_seq_num_lim = 4;
uniformProbFromMax(loop_seq_num_distr, loop_seq_num_lim, 1);
loop_nest_depth_lim = 3;
uniformProbFromMax(loop_nest_depth_distr, loop_nest_depth_lim, 2);
loop_depth_limit = 5;
if_else_depth_limit = 5;
scope_stmt_min_num = 2;
scope_stmt_max_num = 5;
uniformProbFromMax(scope_stmt_num_distr, scope_stmt_max_num,
scope_stmt_min_num);
iters_end_limit_min = 10;
iter_end_limit_max = 25;
iters_step_distr.emplace_back(Probability<size_t>{1, 10});
iters_step_distr.emplace_back(Probability<size_t>{2, 10});
iters_step_distr.emplace_back(Probability<size_t>{3, 10});
iters_step_distr.emplace_back(Probability<size_t>{4, 10});
shuffleProbProxy(iters_step_distr);
if (!options.isSYCL()) {
stmt_kind_struct_distr.emplace_back(
Probability<IRNodeKind>{IRNodeKind::LOOP_SEQ, 10});
stmt_kind_struct_distr.emplace_back(
Probability<IRNodeKind>{IRNodeKind::LOOP_NEST, 10});
}
stmt_kind_struct_distr.emplace_back(
Probability<IRNodeKind>{IRNodeKind::IF_ELSE, 10});
stmt_kind_struct_distr.emplace_back(
Probability<IRNodeKind>{IRNodeKind::STUB, 70});
shuffleProbProxy(stmt_kind_struct_distr);
else_br_distr.emplace_back(Probability<bool>{true, 20});
else_br_distr.emplace_back(Probability<bool>{false, 80});
shuffleProbProxy(else_br_distr);
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::BOOL, 10));
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::SCHAR, 10));
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::UCHAR, 10));
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::SHORT, 10));
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::USHORT, 10));
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::INT, 10));
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::UINT, 10));
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::LLONG, 10));
int_type_distr.emplace_back(Probability<IntTypeID>(IntTypeID::ULLONG, 10));
shuffleProbProxy(int_type_distr);
min_inp_vars_num = 10;
max_inp_vars_num = 20;
expr_stmt_kind_pop_distr.emplace_back(IRNodeKind::ASSIGN, 70);
expr_stmt_kind_pop_distr.emplace_back(IRNodeKind::REDUCTION, 30);
shuffleProbProxy(expr_stmt_kind_pop_distr);
min_new_arr_num = 2;
max_new_arr_num = 4;
uniformProbFromMax(new_arr_num_distr, max_new_arr_num, min_new_arr_num);
out_kind_distr.emplace_back(Probability<DataKind>(DataKind::VAR, 20));
out_kind_distr.emplace_back(Probability<DataKind>(DataKind::ARR, 20));
shuffleProbProxy(out_kind_distr);
max_arith_depth = 4;
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::CONST, 10));
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::SCALAR_VAR_USE, 10));
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::SUBSCRIPT, 10));
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::TYPE_CAST, 10));
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::UNARY, 20));
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::BINARY, 20));
if (!options.isSYCL())
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::CALL, 20));
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::TERNARY, 20));
arith_node_distr.emplace_back(IRNodeKind::STENCIL, 20);
shuffleProbProxy(arith_node_distr);
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::PLUS, 25));
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::NEGATE, 25));
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::LOG_NOT, 25));
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::BIT_NOT, 25));
shuffleProbProxy(unary_op_distr);
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::ADD, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::SUB, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::MUL, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::DIV, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::MOD, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::LT, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::GT, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::LE, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::GE, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::EQ, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::NE, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::LOG_AND, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::LOG_OR, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::BIT_AND, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::BIT_OR, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::BIT_XOR, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::SHL, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::SHR, 10));
shuffleProbProxy(binary_op_distr);
foreach_distr.emplace_back(Probability<bool>(true, 20));
foreach_distr.emplace_back(Probability<bool>(false, 80));
shuffleProbProxy(foreach_distr);
c_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::MAX, 20));
c_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::MIN, 20));
shuffleProbProxy(c_lib_call_distr);
cxx_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::MAX, 20));
cxx_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::MIN, 20));
shuffleProbProxy(cxx_lib_call_distr);
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::MAX, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::MIN, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::SELECT, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::ANY, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::ALL, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::NONE, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::RED_MIN, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::RED_MAX, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::RED_EQ, 20));
ispc_lib_call_distr.emplace_back(
Probability<LibCallKind>(LibCallKind::EXTRACT, 20));
shuffleProbProxy(ispc_lib_call_distr);
reduction_as_bin_op_prob.emplace_back(true, 65);
reduction_as_bin_op_prob.emplace_back(false, 35);
shuffleProbProxy(reduction_as_bin_op_prob);
reduction_bin_op_distr.emplace_back(BinaryOp::ADD, 10);
reduction_bin_op_distr.emplace_back(BinaryOp::SUB, 10);
reduction_bin_op_distr.emplace_back(BinaryOp::MUL, 10);
// Division and modulo do not make sense for reductions
// reduction_bin_op_distr.emplace_back(BinaryOp::DIV, 10);
// reduction_bin_op_distr.emplace_back(BinaryOp::MOD, 10);
reduction_bin_op_distr.emplace_back(BinaryOp::BIT_AND, 10);
reduction_bin_op_distr.emplace_back(BinaryOp::BIT_OR, 10);
reduction_bin_op_distr.emplace_back(BinaryOp::BIT_XOR, 10);
// reduction_bin_op_distr.emplace_back(BinaryOp::SHL, 10);
// reduction_bin_op_distr.emplace_back(BinaryOp::SHR, 10);
shuffleProbProxy(reduction_bin_op_distr);
reduction_as_lib_call_distr.emplace_back(LibCallKind::MAX, 50);
reduction_as_lib_call_distr.emplace_back(LibCallKind::MIN, 50);
shuffleProbProxy(reduction_as_lib_call_distr);
loop_end_kind_distr.emplace_back(
Probability<LoopEndKind>(LoopEndKind::CONST, 30));
if (!options.getExplLoopParams()) {
loop_end_kind_distr.emplace_back(
Probability<LoopEndKind>(LoopEndKind::VAR, 30));
loop_end_kind_distr.emplace_back(
Probability<LoopEndKind>(LoopEndKind::EXPR, 30));
shuffleProbProxy(loop_end_kind_distr);
}
uniformProbFromMax(pragma_num_distr,
static_cast<int>(PragmaKind::MAX_PRAGMA_KIND) - 1,
static_cast<size_t>(PragmaKind::CLANG_VECTORIZE));
pragma_kind_distr.emplace_back(
Probability<PragmaKind>(PragmaKind::CLANG_VECTORIZE, 20));
pragma_kind_distr.emplace_back(
Probability<PragmaKind>(PragmaKind::CLANG_INTERLEAVE, 20));
pragma_kind_distr.emplace_back(
Probability<PragmaKind>(PragmaKind::CLANG_VEC_PREDICATE, 20));
pragma_kind_distr.emplace_back(
Probability<PragmaKind>(PragmaKind::CLANG_UNROLL, 20));
pragma_kind_distr.emplace_back(
Probability<PragmaKind>(PragmaKind::OMP_SIMD, 20));
shuffleProbProxy(pragma_kind_distr);
active_similar_op = SimilarOperators::MAX_SIMILAR_OP;
apply_similar_op_distr.emplace_back(Probability<bool>(true, 10));
apply_similar_op_distr.emplace_back(Probability<bool>(false, 90));
shuffleProbProxy(apply_similar_op_distr);
similar_op_distr.emplace_back(
Probability<SimilarOperators>(SimilarOperators::ADDITIVE, 10));
similar_op_distr.emplace_back(
Probability<SimilarOperators>(SimilarOperators::BITWISE, 10));
similar_op_distr.emplace_back(
Probability<SimilarOperators>(SimilarOperators::LOGIC, 10));
similar_op_distr.emplace_back(
Probability<SimilarOperators>(SimilarOperators::MULTIPLICATIVE, 10));
similar_op_distr.emplace_back(
Probability<SimilarOperators>(SimilarOperators::BIT_SH, 10));
similar_op_distr.emplace_back(
Probability<SimilarOperators>(SimilarOperators::ADD_MUL, 10));
shuffleProbProxy(similar_op_distr);
active_const_use = ConstUse::MAX_CONST_USE;
apply_const_use_distr.emplace_back(Probability<bool>(true, 10));
apply_const_use_distr.emplace_back(Probability<bool>(false, 90));
shuffleProbProxy(apply_const_use_distr);
const_use_distr.emplace_back(Probability<ConstUse>(ConstUse::HALF, 50));
const_use_distr.emplace_back(Probability<ConstUse>(ConstUse::ALL, 50));
shuffleProbProxy(const_use_distr);
use_special_const_distr.emplace_back(Probability<bool>(true, 30));
use_special_const_distr.emplace_back(Probability<bool>(false, 70));
shuffleProbProxy(use_special_const_distr);
special_const_distr.emplace_back(
Probability<SpecialConst>(SpecialConst::ZERO, 10));
special_const_distr.emplace_back(
Probability<SpecialConst>(SpecialConst::MIN, 10));
special_const_distr.emplace_back(
Probability<SpecialConst>(SpecialConst::MAX, 10));
special_const_distr.emplace_back(
Probability<SpecialConst>(SpecialConst::BIT_BLOCK, 10));
special_const_distr.emplace_back(
Probability<SpecialConst>(SpecialConst::END_BITS, 10));
shuffleProbProxy(special_const_distr);
use_lsb_bit_end_distr.emplace_back(Probability<bool>(true, 50));
use_lsb_bit_end_distr.emplace_back(Probability<bool>(false, 50));
shuffleProbProxy(use_lsb_bit_end_distr);
use_const_offset_distr.emplace_back(Probability<bool>(true, 50));
use_const_offset_distr.emplace_back(Probability<bool>(false, 50));
shuffleProbProxy(use_const_offset_distr);
min_offset = 1;
max_offset = 32;
uniformProbFromMax(const_offset_distr, max_offset, min_offset);
pos_const_offset_distr.emplace_back(Probability<bool>(true, 50));
pos_const_offset_distr.emplace_back(Probability<bool>(false, 50));
shuffleProbProxy(pos_const_offset_distr);
replace_in_buf_distr.emplace_back(Probability<bool>(true, 50));
replace_in_buf_distr.emplace_back(Probability<bool>(false, 50));
shuffleProbProxy(replace_in_buf_distr);
reuse_const_prob.emplace_back(Probability<bool>(true, 30));
reuse_const_prob.emplace_back(Probability<bool>(false, 70));
shuffleProbProxy(reuse_const_prob);
use_const_transform_distr.emplace_back(Probability<bool>(true, 50));
use_const_transform_distr.emplace_back(Probability<bool>(false, 50));
shuffleProbProxy(use_const_offset_distr);
const_transform_distr.emplace_back(
Probability<UnaryOp>(UnaryOp::NEGATE, 30));
const_transform_distr.emplace_back(
Probability<UnaryOp>(UnaryOp::BIT_NOT, 30));
shuffleProbProxy(const_transform_distr);
mutation_probability.emplace_back(Probability<bool>(true, 10));
mutation_probability.emplace_back(Probability<bool>(false, 90));
ub_in_dc_prob.emplace_back(Probability<bool>(true, 30));
ub_in_dc_prob.emplace_back(Probability<bool>(false, 70));
shuffleProbProxy(ub_in_dc_prob);
allow_stencil_prob.emplace_back(Probability<bool>(true, 40));
allow_stencil_prob.emplace_back(Probability<bool>(false, 60));
shuffleProbProxy(allow_stencil_prob);
uniformProbFromMax(stencil_span_distr, max_stencil_span, 1);
ispc_iter_end_limit_max = ISPC_MAX_VECTOR_SIZE + max_stencil_span;
arrs_in_stencil_distr.emplace_back(Probability<size_t>(1, 50));
arrs_in_stencil_distr.emplace_back(Probability<size_t>(2, 25));
arrs_in_stencil_distr.emplace_back(Probability<size_t>(3, 15));
arrs_in_stencil_distr.emplace_back(Probability<size_t>(4, 10));
stencil_same_dims_one_arr_distr.emplace_back(Probability<bool>(true, 70));
stencil_same_dims_one_arr_distr.emplace_back(Probability<bool>(false, 30));
shuffleProbProxy(stencil_same_dims_one_arr_distr);
stencil_same_dims_all_distr.emplace_back(Probability<bool>(true, 40));
stencil_same_dims_all_distr.emplace_back(Probability<bool>(false, 60));
shuffleProbProxy(stencil_same_dims_all_distr);
stencil_same_offset_all_distr.emplace_back(Probability<bool>(true, 30));
stencil_same_offset_all_distr.emplace_back(Probability<bool>(false, 70));
shuffleProbProxy(stencil_same_offset_all_distr);
stencil_dim_num_distr.emplace_back(0, 5);
stencil_dim_num_distr.emplace_back(1, 30);
stencil_dim_num_distr.emplace_back(2, 30);
stencil_dim_num_distr.emplace_back(3, 20);
stencil_dim_num_distr.emplace_back(4, 10);
shuffleProbProxy(stencil_dim_num_distr);
array_dims_num_limit = 7;
// It looks like ISPC has trouble allocating arrays that require a lot of
// memory. We limit the number of dimensions to 4.
// The issue is that we have to always allocate arrays that contain at
// least max_ispc_vector size elements. Otherwise, we get a runtime error.
if (options.isISPC())
array_dims_num_limit = 4;
// Arrays with single dimension require a separate treatment. Otherwise, we
// do not get the desired distribution.
stencil_in_dim_prob.emplace(
1, std::initializer_list<Probability<bool>>{{true, 80}, {false, 20}});
shuffleProbProxy(stencil_in_dim_prob[1]);
for (size_t i = 2; i <= array_dims_num_limit; i++) {
size_t gen_prob = (1.0 / i + stencil_in_dim_prob_offset) * 100;
stencil_in_dim_prob.emplace(
i, std::initializer_list<Probability<bool>>{
{true, gen_prob}, {false, 100 - gen_prob}});
shuffleProbProxy(stencil_in_dim_prob[i]);
}
subs_order_kind_distr.emplace_back(SubscriptOrderKind::IN_ORDER, 40);
subs_order_kind_distr.emplace_back(SubscriptOrderKind::REVERSE, 20);
subs_order_kind_distr.emplace_back(SubscriptOrderKind::DIAGONAL, 20);
subs_order_kind_distr.emplace_back(SubscriptOrderKind::RANDOM, 30);
shuffleProbProxy(subs_order_kind_distr);
subs_kind_prob.emplace_back(SubscriptKind::CONST, 10);
subs_kind_prob.emplace_back(SubscriptKind::ITER, 35);
subs_kind_prob.emplace_back(SubscriptKind::OFFSET, 15);
subs_kind_prob.emplace_back(SubscriptKind::REPEAT, 15);
shuffleProbProxy(subs_kind_prob);
subs_diagonal_prob.emplace_back(true, 5);
subs_diagonal_prob.emplace_back(false, 95);
shuffleProbProxy(subs_diagonal_prob);
array_dims_use_kind.emplace_back(
Probability<ArrayDimsUseKind>(ArrayDimsUseKind::FEWER, 33));
array_dims_use_kind.emplace_back(
Probability<ArrayDimsUseKind>(ArrayDimsUseKind::SAME, 33));
array_dims_use_kind.emplace_back(
Probability<ArrayDimsUseKind>(ArrayDimsUseKind::MORE, 33));
use_iters_cache_prob.emplace_back(true, 70);
use_iters_cache_prob.emplace_back(false, 30);
shuffleProbProxy(use_iters_cache_prob);
same_iter_space.emplace_back(true, 20);
same_iter_space.emplace_back(false, 80);
shuffleProbProxy(same_iter_space);
uniformProbFromMax(same_iter_space_span, loop_seq_num_lim, 2);
array_with_mul_vals_prob.emplace_back(true, 40);
array_with_mul_vals_prob.emplace_back(false, 60);
shuffleProbProxy(array_with_mul_vals_prob);
loop_body_with_mul_vals_prob.emplace_back(true, 40);
loop_body_with_mul_vals_prob.emplace_back(false, 60);
shuffleProbProxy(loop_body_with_mul_vals_prob);
hide_zero_in_versioning_prob.emplace_back(true, 50);
hide_zero_in_versioning_prob.emplace_back(false, 50);
vectorizable_loop_distr.emplace_back(true, 20);
vectorizable_loop_distr.emplace_back(false, 70);
shuffleProbProxy(vectorizable_loop_distr);
}
void GenPolicy::makeVectorizable() {
Options &options = Options::getInstance();
removeProbability(stmt_kind_struct_distr, IRNodeKind::LOOP_NEST);
max_arith_depth = 3;
removeProbability(arith_node_distr, IRNodeKind::CALL);
loop_end_kind_distr.clear();
loop_end_kind_distr.emplace_back(LoopEndKind::CONST, 70);
if (!options.getExplLoopParams()) {
loop_end_kind_distr.emplace_back(LoopEndKind::VAR, 15);
loop_end_kind_distr.emplace_back(LoopEndKind::EXPR, 15);
shuffleProbProxy(loop_end_kind_distr);
}
uniformProbFromMax(pragma_num_distr, 2);
pragma_kind_distr.clear();
pragma_kind_distr.emplace_back(PragmaKind::CLANG_VECTORIZE, 20);
pragma_kind_distr.emplace_back(PragmaKind::CLANG_VEC_PREDICATE, 20);
shuffleProbProxy(pragma_kind_distr);
vectorizable_loop_distr.clear();
vectorizable_loop_distr.emplace_back(false, 90);
}
size_t yarpgen::GenPolicy::const_buf_size = 10;
void GenPolicy::chooseAndApplySimilarOp() {
if (active_similar_op != SimilarOperators::MAX_SIMILAR_OP)
return;
active_similar_op = rand_val_gen->getRandId(similar_op_distr);
binary_op_distr.clear();
unary_op_distr.clear();
if (active_similar_op == SimilarOperators::ADDITIVE ||
active_similar_op == SimilarOperators::ADD_MUL) {
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::PLUS, 10));
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::NEGATE, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::ADD, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::SUB, 10));
if (active_similar_op == SimilarOperators::ADD_MUL) {
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::MUL, 10));
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::DIV, 10));
}
}
if (active_similar_op == SimilarOperators::MULTIPLICATIVE) {
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::PLUS, 10));
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::NEGATE, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::MUL, 10));
binary_op_distr.emplace_back(Probability<BinaryOp>(BinaryOp::DIV, 10));
}
if (active_similar_op == SimilarOperators::BITWISE ||
active_similar_op == SimilarOperators::BIT_SH) {
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::BIT_NOT, 10));
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::BIT_AND, 10));
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::BIT_OR, 10));
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::BIT_XOR, 10));
if (active_similar_op == SimilarOperators::BIT_SH) {
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::SHL, 10));
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::SHR, 10));
}
}
if (active_similar_op == SimilarOperators::LOGIC) {
unary_op_distr.emplace_back(Probability<UnaryOp>(UnaryOp::LOG_NOT, 10));
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::LOG_AND, 10));
binary_op_distr.emplace_back(
Probability<BinaryOp>(BinaryOp::LOG_OR, 10));
}
}
void GenPolicy::chooseAndApplyConstUse() {
if (active_const_use != ConstUse::MAX_CONST_USE)
return;
active_const_use = rand_val_gen->getRandId(const_use_distr);
if (active_const_use == ConstUse::ALL) {
arith_node_distr.clear();
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::CONST, 100));
}
else if (active_const_use == ConstUse::HALF) {
uint64_t sum = 0;
auto &vec = arith_node_distr;
std::for_each(vec.begin(), vec.end(),
[&](Probability<IRNodeKind> n) { sum += n.getProb(); });
auto search_func = [](Probability<IRNodeKind> n) -> bool {
return n.getId() == IRNodeKind::CONST;
};
auto find_res = std::find_if(vec.begin(), vec.end(), search_func);
if (find_res != vec.end()) {
sum -= find_res->getProb();
vec.erase(find_res);
}
arith_node_distr.emplace_back(
Probability<IRNodeKind>(IRNodeKind::CONST, sum));
}
}
template <typename T>
void GenPolicy::uniformProbFromMax(std::vector<Probability<T>> &distr,
size_t max_num, size_t min_num) {
distr.reserve(max_num - min_num);
for (size_t i = min_num; i <= max_num; ++i)
distr.emplace_back(i, (max_num - i + 1) * 10);
}
template <class T, class U>
void GenPolicy::removeProbability(std::vector<Probability<T>> &orig, U id) {
(void)std::remove_if(
orig.begin(), orig.end(),
[&id](Probability<T> &elem) -> bool { return elem.getId() == id; });
}