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Halide
/
src
/
Associativity.cpp
Halide
/
src
/
Associativity.cpp
Associativity.cpp 36.92 KB
一键复制 编辑 原始数据 按行查看 历史
Shihpo Hung 提交于 2020年10月22日 21:45 +08:00 . Fix transitive dependencies
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#include "Associativity.h"
#include "CSE.h"
#include "ExprUsesVar.h"
#include "IREquality.h"
#include "IRMatch.h"
#include "IRMutator.h"
#include "IROperator.h"
#include "IRPrinter.h"
#include "Simplify.h"
#include "Solve.h"
#include "Substitute.h"
#include "Util.h"
#include <algorithm>
#include <iterator>
namespace Halide {
namespace Internal {
using std::map;
using std::pair;
using std::set;
using std::string;
using std::vector;
namespace {
template<typename T>
vector<T> get_subvector(const vector<T> &v, const set<int> &indices) {
vector<T> sub;
for (const auto &index : indices) {
internal_assert(index < (int)v.size());
sub.push_back(v[index]);
}
return sub;
}
// Replace self-references to 'func' with arguments 'args' at
// 'value_index' in the Expr/Stmt with some Var
class ConvertSelfRef : public IRGraphMutator {
using IRGraphMutator::visit;
const string &func;
const vector<Expr> &args;
// If that function has multiple values, which value does this
// call node refer to?
const int value_index;
const vector<string> &op_x_names;
Expr visit(const Call *op) override {
if (!is_solvable) {
return op;
}
Expr expr = IRGraphMutator::visit(op);
op = expr.as<Call>();
internal_assert(op);
if ((op->call_type == Call::Halide) && (func == op->name)) {
internal_assert(args.size() == op->args.size())
<< "Self-reference should have the same number of args as the original\n";
for (size_t i = 0; i < op->args.size(); i++) {
if (!graph_equal(op->args[i], args[i])) {
debug(5) << "Self-reference of " << op->name
<< " with different args from the LHS. Operation is not associative\n";
is_solvable = false;
return expr;
}
}
// Substitute the call
internal_assert(op->value_index < (int)op_x_names.size());
debug(5) << " Substituting Call " << op->name << " at value index "
<< op->value_index << " with " << op_x_names[op->value_index] << "\n";
expr = Variable::make(op->type, op_x_names[op->value_index]);
if (op->value_index == value_index) {
x_part = op;
} else {
x_dependencies.insert(op->value_index);
}
}
return expr;
}
public:
ConvertSelfRef(const string &f, const vector<Expr> &args, int idx,
const vector<string> &x_names)
: func(f), args(args), value_index(idx), op_x_names(x_names) {
}
bool is_solvable = true;
set<int> x_dependencies; // Contains dependencies on self-reference at different tuple indices
Expr x_part; // Undefined if there is no self-reference at value_index
};
bool associative_op_pattern_match(const Expr &e,
const Expr &op,
const vector<string> &x_names,
const vector<string> &y_names,
const Scope<> &x_scope,
map<string, Expr> &match) {
internal_assert(e.type() == op.type())
<< "Expr has type " << e.type() << ", while pattern has type " << op.type() << "\n";
map<string, Expr> result;
if (expr_match(op, e, result)) {
debug(5) << "Found associative ops for " << e << " -> " << op
<< ", y_part: " << result["y0"] << "\n";
for (size_t i = 0; i < x_names.size(); ++i) {
const auto &iter = result.find("x" + std::to_string(i));
if (iter != result.end()) {
const Variable *xvar = iter->second.as<Variable>();
if ((xvar == nullptr) || (xvar->name != x_names[i])) {
debug(5) << "...Skipping match since the x_part is different than expected. "
<< "Expect: " << x_names[i] << "; get: " << iter->second << "\n";
return false;
}
}
}
for (size_t i = 0; i < y_names.size(); ++i) {
const auto &iter = result.find("y" + std::to_string(i));
if (iter != result.end()) {
// Make sure that y_part should not depend on x vars
if (expr_uses_vars(iter->second, x_scope)) {
debug(5) << "...Skipping match since the y_part depends on x vars\n";
return false;
}
}
}
for (size_t i = 0; i < x_names.size(); ++i) {
const auto &iter = result.find("k" + std::to_string(i));
if (iter != result.end()) {
// Make sure that k_part is constant
if (!is_const(iter->second)) {
debug(5) << "...Skipping match since the k_part is not constant\n";
return false;
}
}
}
// Make sure that the new matches are in agreement with any previous matches
for (const auto &iter : result) {
const auto &match_iter = match.find(iter.first);
if (match_iter == match.end()) {
debug(5) << "Adding result: " << iter.first << " -> " << iter.second << "\n";
match.emplace(iter.first, iter.second);
} else {
if (!equal(iter.first, match_iter->first) || !equal(iter.second, match_iter->second)) {
return false;
}
}
}
return true;
}
return false;
}
// Return true if we are able to find a match in the table (i.e. the op can be
// proven associative) and update 'assoc_op'.
bool find_match(const vector<AssociativePattern> &table, const vector<string> &op_x_names,
const vector<string> &op_y_names, const vector<Expr> &x_parts,
const vector<Expr> &exprs, AssociativeOp &assoc_op) {
internal_assert(op_x_names.size() == op_y_names.size());
internal_assert(op_x_names.size() == x_parts.size());
internal_assert(op_x_names.size() == exprs.size());
internal_assert(op_x_names.size() == assoc_op.size());
Scope<> x_scope;
for (const auto &x : op_x_names) {
x_scope.push(x);
}
for (const AssociativePattern &pattern : table) {
internal_assert(pattern.size() == op_x_names.size());
map<string, Expr> pattern_match;
bool matched = true;
// If any of element in 'pattern' does not match, try the next thing in
// the table.
for (size_t i = 0; i < pattern.size(); ++i) {
if (!associative_op_pattern_match(exprs[i], pattern.ops[i], op_x_names,
op_y_names, x_scope, pattern_match)) {
matched = false;
break;
}
}
if (!matched) {
continue;
}
vector<pair<Expr, Expr>> replacement; // find -> replacement
for (size_t index = 0; index < op_y_names.size(); ++index) {
const auto &y_iter = pattern_match.find("y" + std::to_string(index));
if (y_iter == pattern_match.end()) {
// Didn't find y{index} during pattern matching. Try next pattern.
matched = false;
break;
}
Expr y_part = y_iter->second;
debug(5) << "Pattern at index " << index << ":\n " << op_x_names[index]
<< " -> " << x_parts[index] << "\n " << op_y_names[index]
<< " -> " << y_part << "\n";
assoc_op.xs[index] = {op_x_names[index], x_parts[index]};
assoc_op.ys[index] = {op_y_names[index], y_part};
replacement.emplace_back(y_part, Variable::make(y_part.type(), op_y_names[index]));
}
if (!matched) {
continue;
}
for (size_t index = 0; index < exprs.size(); ++index) {
Expr e = exprs[index];
// Order of substitution matters, e.g. in the argmin case, _y_0 -> g(rx)[0]
// and _y_1 -> rx. If we substitute the 2nd element rx first, substitution
// of g(rx)[0] will fail.
for (const auto &iter : replacement) {
e = substitute(iter.first, iter.second, e);
}
assoc_op.pattern.ops[index] = e;
assoc_op.pattern.identities[index] = pattern.identities[index];
}
assoc_op.pattern.is_commutative = pattern.is_commutative;
return true;
}
return false;
}
// Return a pair of booleans indicating if an operator is associative.
// 'assoc_op' contains the the equivalent associative binary/unary operator
// for that operator. If the operator is non-associative, 'assoc_op' is not valid.
bool extract_associative_op(const vector<Expr> &exprs, const vector<string> &op_x_names,
const vector<string> &op_y_names, const vector<Expr> &x_parts,
AssociativeOp &assoc_op) {
if (exprs.size() == 1) {
Type t = exprs[0].type();
if (!x_parts[0].defined()) {
// Update with no self-recurrence is associative and the identity
// can be anything since it's going to be replaced anyway, but it's
// not commutative
assoc_op.pattern.ops[0] = Variable::make(t, op_y_names[0]);
assoc_op.pattern.identities[0] = make_const(t, 0);
assoc_op.pattern.is_commutative = false;
assoc_op.xs[0] = {"", Expr()};
assoc_op.ys[0] = {op_y_names[0], exprs[0]};
return true;
} else if (equal(exprs[0], Variable::make(t, op_x_names[0]))) {
// Self assignment, f(x) = f(x), is both associative
// and commutative. The identity can be anything since it's
// going to be replaced by itself.
debug(5) << "Self assignment: " << x_parts[0] << " = " << x_parts[0] << "\n";
assoc_op.pattern.ops[0] = Variable::make(t, op_x_names[0]);
assoc_op.pattern.identities[0] = make_const(t, 0);
assoc_op.pattern.is_commutative = true;
assoc_op.xs[0] = {op_x_names[0], x_parts[0]};
assoc_op.ys[0] = {"", Expr()};
return true;
}
}
return find_match(get_ops_table(exprs), op_x_names, op_y_names,
x_parts, exprs, assoc_op);
}
void add_transitive_dependencies(vector<set<int>> &dependencies) {
// TODO(psuriana): there might be a better way to find all the transitive dependencies
bool change = true;
while (change) {
change = false;
for (size_t i = 0; i < dependencies.size(); ++i) {
for (size_t j = 0; j < dependencies.size(); ++j) {
if (i == j) {
continue;
}
if (dependencies[i].count(j)) {
for (const auto &idx : dependencies[j]) {
if (dependencies[i].count(idx) == 0) {
dependencies[i].insert(idx);
change = true;
}
}
}
}
}
}
}
// Given dependencies of each tuple element, compute the set of subgraphs:
// all vertices that are reachable from a given vertex. If a subgraph is fully
// contained in another subgraph, remove it from the final output.
vector<set<int>> compute_subgraphs(vector<set<int>> dependencies) {
vector<set<int>> subgraphs(dependencies.size());
for (size_t i = 0; i < dependencies.size(); ++i) {
// Check if the current subgraph is a subset of another
const auto &current = dependencies[i];
if (current.empty()) {
continue;
}
bool should_remove = false;
for (size_t j = 0; j < dependencies.size(); ++j) {
const auto &other = dependencies[j];
if ((i == j) || (current.size() > other.size()) || (j < i && subgraphs[i].empty())) {
continue;
}
vector<int> diff;
// Compute the vertices in the current set that are not contained in the other
std::set_difference(current.begin(), current.end(), other.begin(), other.end(),
std::inserter(diff, diff.begin()));
if (diff.empty()) {
// 'current' is fully contained in 'other'
should_remove = true;
break;
}
}
if (!should_remove) {
subgraphs[i] = current;
}
}
return subgraphs;
}
} // anonymous namespace
AssociativeOp prove_associativity(const string &f, vector<Expr> args, vector<Expr> exprs) {
AssociativeOp assoc_op(exprs.size());
for (Expr &arg : args) {
// Undo the existing CSE pass done at function definition time
// to ensure things like += are in the expected form. Make no
// further transformations so that the LHS and RHS don't
// diverge.
arg = substitute_in_all_lets(arg);
}
vector<string> op_x_names(exprs.size()), op_y_names(exprs.size());
for (size_t idx = 0; idx < exprs.size(); ++idx) {
op_x_names[idx] = unique_name("_x_" + std::to_string(idx));
op_y_names[idx] = unique_name("_y_" + std::to_string(idx));
}
vector<set<int>> dependencies(exprs.size());
vector<Expr> x_parts(exprs.size());
bool all_independent = true;
// For a Tuple of exprs to be associative, each element of the Tuple
// has to be associative.
for (int idx = exprs.size() - 1; idx >= 0; --idx) {
// Undo the existing CSE pass done at function definition time.
exprs[idx] = substitute_in_all_lets(exprs[idx]);
// Replace any self-reference to Func 'f' with a Var
ConvertSelfRef csr(f, args, idx, op_x_names);
exprs[idx] = csr.mutate(exprs[idx]);
if (!csr.is_solvable) {
return AssociativeOp();
}
if (!csr.x_dependencies.empty()) {
all_independent = false;
}
x_parts[idx] = csr.x_part;
dependencies[idx] = csr.x_dependencies;
// Add dependency on itself (regardless whether it actually depends on
// its previous values) for the purpose of computing the subgraph
dependencies[idx].insert(idx);
exprs[idx] = common_subexpression_elimination(exprs[idx]);
exprs[idx] = simplify(exprs[idx]);
exprs[idx] = solve_expression(exprs[idx], op_x_names[idx]).result; // Move 'x' to the left as possible
exprs[idx] = substitute_in_all_lets(exprs[idx]);
}
internal_assert((exprs.size() != 1) || all_independent) << "1D tuple should be all independent\n";
vector<set<int>> subgraphs;
if (!all_independent) {
debug(5) << "There are cross-dependencies. Need to prove associativity in bulk.\n";
// Find all transitive dependencies and add them to the graph
add_transitive_dependencies(dependencies);
// Decompose the tuple into subgraphs and solve for each separately
subgraphs = compute_subgraphs(dependencies);
} else {
debug(5) << "All tuple elements are independent. Try proving associativity of "
<< "each element separately.\n";
// If all elements are independent, the subgraph is equal to the dependencies graph
subgraphs = dependencies;
}
internal_assert(subgraphs.size() == exprs.size());
for (size_t i = 0; i < subgraphs.size(); ++i) {
if (subgraphs[i].empty()) {
debug(5) << "Empty subgraph " << i << "\n";
continue;
}
if (subgraphs[i].size() > 2) {
// TODO(psuriana): Currently only support max of 2 tuple elements
debug(5) << "Subgraph " << i << " size is " << subgraphs[i].size() << " which is bigger than 2\n";
return AssociativeOp();
}
vector<Expr> sub_exprs = get_subvector(exprs, subgraphs[i]);
vector<string> sub_op_x_names = get_subvector(op_x_names, subgraphs[i]);
vector<string> sub_op_y_names = get_subvector(op_y_names, subgraphs[i]);
vector<Expr> sub_x_parts = get_subvector(x_parts, subgraphs[i]);
AssociativeOp sub_assoc_op(sub_exprs.size());
// TODO(psuriana): In general, if we fail to find a match for the
// set of initial subgraphs, we need to consider other possible
// grouping of those initial subgraphs. Since only the 'x' is
// apparent from the Halide update definition, the compute_subgraphs
// method over-partitions the graph (e.g. 2x2 matrix multiplication
// written as a four-dimensional reduction).
if (!extract_associative_op(sub_exprs, sub_op_x_names, sub_op_y_names,
sub_x_parts, sub_assoc_op)) {
debug(5) << "Cannot find matching associative ops\n";
return AssociativeOp();
}
debug(5) << "...Proving associativity of subgraph " << i << "\n";
const set<int> &indices = subgraphs[i];
for (auto iter = indices.begin(); iter != indices.end(); ++iter) {
int index = *iter;
int j = std::distance(indices.begin(), iter);
// If the ops/x/y have been extracted previously, we have to make sure
// they are consistent with the new extracted values.
if (assoc_op.pattern.ops[index].defined()) {
if (!equal(assoc_op.pattern.ops[index], sub_assoc_op.pattern.ops[j]) ||
!equal(assoc_op.pattern.identities[index], sub_assoc_op.pattern.identities[j])) {
debug(5) << "Conflicting associative ops/identities from different subgraphs\n";
return AssociativeOp();
}
}
if (assoc_op.xs[index].expr.defined()) {
if (assoc_op.xs[index] != sub_assoc_op.xs[j]) {
debug(5) << "Conflicting associative x-replacements from different subgraphs\n";
return AssociativeOp();
}
}
if (assoc_op.ys[index].expr.defined()) {
if (assoc_op.ys[index] != sub_assoc_op.ys[j]) {
debug(5) << "Conflicting associative y-replacements from different subgraphs\n";
return AssociativeOp();
}
}
assoc_op.pattern.ops[index] = sub_assoc_op.pattern.ops[j];
assoc_op.pattern.identities[index] = sub_assoc_op.pattern.identities[j];
assoc_op.pattern.is_commutative = sub_assoc_op.pattern.is_commutative;
assoc_op.xs[index] = sub_assoc_op.xs[j];
assoc_op.ys[index] = sub_assoc_op.ys[j];
}
}
assoc_op.is_associative = true;
debug(5) << "Found associative ops:\n"
<< assoc_op << "\n";
return assoc_op;
}
namespace {
std::string print_args(const string &f, const vector<Expr> &args, const vector<Expr> &exprs) {
std::ostringstream stream;
stream << f << "(";
for (size_t i = 0; i < args.size(); ++i) {
stream << args[i];
if (i != args.size() - 1) {
stream << ", ";
}
}
stream << ") = ";
if (exprs.size() == 1) {
stream << exprs[0];
} else if (exprs.size() > 1) {
stream << "Tuple(";
for (size_t i = 0; i < exprs.size(); ++i) {
stream << exprs[i];
if (i != exprs.size() - 1) {
stream << ", ";
}
}
stream << ")";
}
return stream.str();
}
void check_associativity(const string &f, const vector<Expr> &args, const vector<Expr> &exprs,
const AssociativeOp &assoc_op) {
auto result = prove_associativity(f, args, exprs);
internal_assert(result.associative() == assoc_op.associative())
<< "Checking associativity: " << print_args(f, args, exprs) << "\n"
<< " Expect is associative: " << assoc_op.associative() << "\n"
<< " instead of " << result.associative() << "\n";
if (assoc_op.associative()) {
map<string, Expr> replacement;
for (size_t i = 0; i < assoc_op.size(); ++i) {
internal_assert(equal(result.pattern.identities[i], assoc_op.pattern.identities[i]))
<< "Checking associativity: " << print_args(f, args, exprs) << "\n"
<< " Index: " << i << "\n"
<< " Expect identity: " << assoc_op.pattern.identities[i] << "\n"
<< " instead of " << result.pattern.identities[i] << "\n";
internal_assert(equal(result.xs[i].expr, assoc_op.xs[i].expr))
<< "Checking associativity: " << print_args(f, args, exprs) << "\n"
<< " Index: " << i << "\n"
<< " Expect x: " << assoc_op.xs[i].expr << "\n"
<< " instead of " << result.xs[i].expr << "\n";
internal_assert(equal(result.ys[i].expr, assoc_op.ys[i].expr))
<< "Checking associativity: " << print_args(f, args, exprs) << "\n"
<< " Index: " << i << "\n"
<< " Expect y: " << assoc_op.ys[i].expr << "\n"
<< " instead of " << result.ys[i].expr << "\n";
if (result.xs[i].expr.defined()) {
replacement.emplace(assoc_op.xs[i].var, Variable::make(result.xs[i].expr.type(), result.xs[i].var));
}
if (result.ys[i].expr.defined()) {
replacement.emplace(assoc_op.ys[i].var, Variable::make(result.ys[i].expr.type(), result.ys[i].var));
}
}
for (size_t i = 0; i < assoc_op.size(); ++i) {
Expr expected_op = substitute(replacement, assoc_op.pattern.ops[i]);
internal_assert(equal(result.pattern.ops[i], expected_op))
<< "Checking associativity: " << print_args(f, args, exprs) << "\n"
<< " Index: " << i << "\n"
<< " Expect bin op: " << expected_op << "\n"
<< " instead of " << result.pattern.ops[i] << "\n";
debug(5) << "\nExpected op: " << expected_op << "\n";
debug(5) << "Operator: " << result.pattern.ops[i] << "\n";
debug(5) << " identity: " << result.pattern.identities[i] << "\n";
debug(5) << " x: " << result.xs[i].var << " -> " << result.xs[i].expr << "\n";
debug(5) << " y: " << result.ys[i].var << " -> " << result.ys[i].expr << "\n";
}
}
}
} // anonymous namespace
void associativity_test() {
typedef AssociativeOp::Replacement Replacement;
{
// Tests for saturating addition
Type t = UInt(8);
Expr x = Variable::make(t, "x");
Expr y = Variable::make(t, "y");
Expr x_idx = Variable::make(Int(32), "x_idx");
Expr f_call_0 = Call::make(t, "f", {x_idx}, Call::CallType::Halide, FunctionPtr(), 0);
// f(x) = uint8(uint16(x + y), 255)
check_associativity("f", {x_idx}, {Cast::make(UInt(8), min(Cast::make(UInt(16), y + f_call_0), make_const(t, 255)))},
AssociativeOp(
AssociativePattern(Cast::make(UInt(8), min(Cast::make(UInt(16), x + y), make_const(t, 255))), make_const(t, 0), true),
{Replacement("x", f_call_0)},
{Replacement("y", y)},
true));
// f(x) = uint8(uint16(x + y), uint16(255))
check_associativity("f", {x_idx}, {Cast::make(UInt(8), min(Cast::make(UInt(16), y + f_call_0), Cast::make(UInt(16), make_const(t, 255))))},
AssociativeOp(
AssociativePattern(Cast::make(UInt(8), min(Cast::make(UInt(16), x + y), make_const(t, 255))), make_const(t, 0), true),
{Replacement("x", f_call_0)},
{Replacement("y", y)},
true));
// f(x) = select(x > 255 - y, 255, y)
check_associativity("f", {x_idx}, {select(f_call_0 > make_const(t, 255) - y, make_const(t, 255), y)},
AssociativeOp(
AssociativePattern(select(x > make_const(t, 255) - y, make_const(t, 255), y), make_const(t, 0), true),
{Replacement("x", f_call_0)},
{Replacement("y", y)},
true));
// f(x) = select(x >= -y, 255, y)
check_associativity("f", {x_idx}, {select(f_call_0 >= -y, make_const(t, 255), y)},
AssociativeOp(
AssociativePattern(select(x < -y, y, make_const(t, 255)), make_const(t, 0), true),
{Replacement("x", f_call_0)},
{Replacement("y", y)},
true));
}
{
// Tests for logical And/Or
Type t = UInt(1);
Expr x = Variable::make(t, "x");
Expr y = Variable::make(t, "y");
Expr x_idx = Variable::make(Int(32), "x_idx");
Expr f_call_0 = Call::make(t, "f", {x_idx}, Call::CallType::Halide, FunctionPtr(), 0);
// f(x) = y && f(x)
check_associativity("f", {x_idx}, {And::make(y, f_call_0)},
AssociativeOp(
AssociativePattern(And::make(x, y), const_true(), true),
{Replacement("x", f_call_0)},
{Replacement("y", y)},
true));
// f(x) = y || f(x)
check_associativity("f", {x_idx}, {Or::make(y, f_call_0)},
AssociativeOp(
AssociativePattern(Or::make(x, y), const_false(), true),
{Replacement("x", f_call_0)},
{Replacement("y", y)},
true));
}
{
// Tests for 1D reduction
Type t = Int(32);
Expr x = Variable::make(t, "x");
Expr y = Variable::make(t, "y");
Expr z = Variable::make(t, "z");
Expr rx = Variable::make(t, "rx");
Expr f_call_0 = Call::make(t, "f", {x}, Call::CallType::Halide, FunctionPtr(), 0);
Expr g_call_0 = Call::make(t, "g", {rx}, Call::CallType::Halide, FunctionPtr(), 0);
// f(x) = f(x)
check_associativity("f", {x}, {f_call_0},
AssociativeOp(
AssociativePattern(x, make_const(t, 0), true),
{Replacement("x", f_call_0)},
{Replacement("", Expr())},
true));
// f(x) = min(f(x), y + int16(z))
check_associativity("f", {x}, {min(f_call_0, y + Cast::make(Int(16), z))},
AssociativeOp(
AssociativePattern(min(x, y), t.max(), true),
{Replacement("x", f_call_0)},
{Replacement("y", y + Cast::make(Int(16), z))},
true));
// f(x) = f(x) + g(rx) + y + z
check_associativity("f", {x}, {y + z + f_call_0},
AssociativeOp(
AssociativePattern(x + y, make_const(t, 0), true),
{Replacement("x", f_call_0)},
{Replacement("y", y + z)},
true));
// f(x) = max(y, f(x))
check_associativity("f", {x}, {max(y, f_call_0)},
AssociativeOp(
AssociativePattern(max(x, y), t.min(), true),
{Replacement("x", f_call_0)},
{Replacement("y", y)},
true));
// f(x) = max(f(x) + g(rx), g(rx)) -> not associative
check_associativity("f", {x}, {max(f_call_0 + g_call_0, g_call_0)}, AssociativeOp());
// f(x) = max(f(x) + g(rx), f(x) - 3) -> f(x) + max(g(rx) - 3)
check_associativity("f", {x}, {max(f_call_0 + g_call_0, f_call_0 - 3)},
AssociativeOp(
AssociativePattern(x + y, 0, true),
{Replacement("x", f_call_0)},
{Replacement("y", max(g_call_0, -3))},
true));
// f(x) = min(4, g(rx)) -> trivially associative
check_associativity("f", {x}, {min(4, g_call_0)},
AssociativeOp(
AssociativePattern(y, make_const(t, 0), true),
{Replacement("", Expr())},
{Replacement("y", min(g_call_0, 4))},
true));
// f(x) = max(max(min(f(x), g(rx) + 2), f(x)), g(rx) + 2) -> can be simplified into max(f(x), g(rx) + 2)
check_associativity("f", {x}, {max(max(min(f_call_0, g_call_0 + 2), f_call_0), g_call_0 + 2)},
AssociativeOp(
AssociativePattern(max(x, y), t.min(), true),
{Replacement("x", f_call_0)},
{Replacement("y", g_call_0 + 2)},
true));
// f(x) = max(x0, f(x)) -> x0 may conflict with the wildcard associative op pattern
Expr x0 = Variable::make(t, "x0");
check_associativity("f", {x}, {max(x0, f_call_0)},
AssociativeOp(
AssociativePattern(max(x, y), t.min(), true),
{Replacement("x", f_call_0)},
{Replacement("y", x0)},
true));
}
{
// Tests for multi-dimensional reduction (with mixed types)
Type t = Int(32);
Expr x = Variable::make(t, "x");
Expr y = Variable::make(t, "y");
Expr z = Variable::make(t, "z");
Expr rx = Variable::make(t, "rx");
vector<Type> ts = {Int(32), Int(32), Float(32)};
vector<Expr> xs(3), ys(3), zs(3);
for (size_t i = 0; i < xs.size(); ++i) {
xs[i] = Variable::make(ts[i], "x" + std::to_string(i));
ys[i] = Variable::make(ts[i], "y" + std::to_string(i));
zs[i] = Variable::make(ts[i], "z" + std::to_string(i));
}
Expr f_call_0 = Call::make(ts[0], "f", {x}, Call::CallType::Halide, FunctionPtr(), 0);
Expr f_call_1 = Call::make(ts[1], "f", {x}, Call::CallType::Halide, FunctionPtr(), 1);
Expr f_call_2 = Call::make(ts[2], "f", {x}, Call::CallType::Halide, FunctionPtr(), 2);
Expr g_call_0 = Call::make(ts[0], "g", {rx}, Call::CallType::Halide, FunctionPtr(), 0);
Expr g_call_1 = Call::make(ts[1], "g", {rx}, Call::CallType::Halide, FunctionPtr(), 1);
// f(x) = Tuple(f(x)[0], 3, f(x)[2] + z)
check_associativity("f", {x}, {f_call_0, make_const(ts[1], 3), f_call_2 + cast(ts[2], z)},
AssociativeOp(
AssociativePattern({xs[0], ys[1], xs[2] + ys[2]},
{make_const(ts[0], 0), make_const(ts[1], 0), make_const(ts[2], 0)},
true),
{Replacement("x0", f_call_0), Replacement("", Expr()), Replacement("x2", f_call_2)},
{Replacement("", Expr()), Replacement("y1", make_const(ts[1], 3)), Replacement("y2", cast(ts[2], z))},
true));
// f(x) = Tuple(2, 3, f(x)[2] + z)
check_associativity("f", {x}, {make_const(ts[0], 2), make_const(ts[1], 3), f_call_2 + cast(ts[2], z)},
AssociativeOp(
AssociativePattern({ys[0], ys[1], xs[2] + ys[2]},
{make_const(ts[0], 0), make_const(ts[1], 0), make_const(ts[2], 0)},
true),
{Replacement("", Expr()), Replacement("", Expr()), Replacement("x2", f_call_2)},
{Replacement("y0", make_const(ts[0], 2)), Replacement("y1", make_const(ts[1], 3)), Replacement("y2", cast(ts[2], z))},
true));
// f(x) = Tuple(min(f(x)[0], g(rx)), f(x)[1]*g(x)*2, f(x)[2] + z)
check_associativity("f", {x}, {min(f_call_0, g_call_0), f_call_1 * g_call_0 * 2, f_call_2 + cast(ts[2], z)},
AssociativeOp(
AssociativePattern(
{min(xs[0], ys[0]), xs[1] * ys[1], xs[2] + ys[2]},
{ts[0].max(), make_const(ts[1], 1), make_const(ts[2], 0)},
true),
{Replacement("x0", f_call_0), Replacement("x1", f_call_1), Replacement("x2", f_call_2)},
{Replacement("y0", g_call_0), Replacement("y1", g_call_0 * 2), Replacement("y2", cast(ts[2], z))},
true));
// Complex multiplication: f(x) = Tuple(f(x)[0]*g(r.x)[0] - f(x)[1]*g(r.x)[1], f(x)[0]*g(r.x)[1] + f(x)[1]*g(r.x)[0])
check_associativity("f", {x}, {f_call_0 * g_call_0 - f_call_1 * g_call_1, f_call_0 * g_call_1 + f_call_1 * g_call_0},
AssociativeOp(
AssociativePattern(
{xs[0] * ys[0] - ys[1] * xs[1], xs[1] * ys[0] + ys[1] * xs[0]},
{make_const(ts[0], 1), make_const(ts[1], 0)},
true),
{Replacement("x0", f_call_0), Replacement("x1", f_call_1)},
{Replacement("y0", g_call_0), Replacement("y1", g_call_1)},
true));
// 1D argmin: f(x) = Tuple(min(f(x)[0], g(r.x)[0]), select(f(x)[0] < g(r.x)[0], f(x)[1], g(r.x)[1])
check_associativity("f", {x}, {min(f_call_0, g_call_0), select(f_call_0 < g_call_0, f_call_1, g_call_1)},
AssociativeOp(
AssociativePattern(
{min(xs[0], ys[0]), select(xs[0] < ys[0], xs[1], ys[1])},
{ts[0].max(), make_const(ts[1], 0)},
true),
{Replacement("x0", f_call_0), Replacement("x1", f_call_1)},
{Replacement("y0", g_call_0), Replacement("y1", g_call_1)},
true));
}
{
Type t = Int(32);
Expr x = Variable::make(t, "x");
Expr y = Variable::make(t, "y");
Expr rx = Variable::make(t, "rx");
Expr ry = Variable::make(t, "ry");
vector<Type> ts = {UInt(8), Int(32), Int(16), Float(32)};
vector<Expr> xs(4), ys(4), zs(4);
for (size_t i = 0; i < xs.size(); ++i) {
xs[i] = Variable::make(ts[i], "x" + std::to_string(i));
ys[i] = Variable::make(ts[i], "y" + std::to_string(i));
zs[i] = Variable::make(ts[i], "z" + std::to_string(i));
}
Expr f_xy_call_0 = Call::make(ts[0], "f", {x, y}, Call::CallType::Halide, FunctionPtr(), 0);
Expr f_xy_call_1 = Call::make(ts[1], "f", {x, y}, Call::CallType::Halide, FunctionPtr(), 1);
Expr f_xy_call_2 = Call::make(ts[2], "f", {x, y}, Call::CallType::Halide, FunctionPtr(), 2);
Expr f_xy_call_3 = Call::make(ts[3], "f", {x, y}, Call::CallType::Halide, FunctionPtr(), 3);
Expr g_xy_call_0 = Call::make(ts[0], "g", {rx, ry}, Call::CallType::Halide, FunctionPtr(), 0);
// 2D argmin + trivial update (with mixed types):
// f(x, y) = Tuple(min(f(x, y)[0], g(r.x, r.y)[0]),
// r.x + r.y,
// select(f(x, y)[0] < g(r.x, r.y)[0], f(x)[2], r.x),
// select(f(x, y)[0] < g(r.x, r.y)[0], f(x)[3], r.y))
check_associativity("f", {x, y},
{min(f_xy_call_0, g_xy_call_0),
rx + ry,
select(f_xy_call_0 < g_xy_call_0, f_xy_call_2, cast(Int(16), rx)),
select(f_xy_call_0 < g_xy_call_0, f_xy_call_3, cast(Float(32), ry))},
AssociativeOp(
AssociativePattern(
{min(xs[0], ys[0]), ys[1], select(xs[0] < ys[0], xs[2], ys[2]), select(xs[0] < ys[0], xs[3], ys[3])},
{ts[0].max(), make_const(ts[1], 0), make_const(ts[2], 0), make_const(ts[3], 0)},
true),
{Replacement("x0", f_xy_call_0), Replacement("", Expr()),
Replacement("x2", f_xy_call_2), Replacement("x3", f_xy_call_3)},
{Replacement("y0", g_xy_call_0), Replacement("y1", rx + ry),
Replacement("y2", cast(Int(16), rx)), Replacement("y3", cast(Float(32), ry))},
true));
}
std::cout << "Associativity test passed" << std::endl;
}
} // namespace Internal
} // namespace Halide
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简介

MIT计算机科学和人工智能实验室的研究人员创造出一种专门设计简化图像处理的程序语言Halide,源代码托管在GitHub上,目前二进制程序只支持Mac OS X和Ubuntu 12
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