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inst_simplify.cc
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//===- inst_simplify.cc ---------------------------------------------------===//
//
// Copyright (C) 2019-2020 Alibaba Group Holding Limited.
//
// 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 "halo/lib/transforms/inst_simplify.h"
#include <algorithm>
#include <numeric>
#include <random>
#include <string>
#include <unordered_set>
#include "halo/api/halo_data.h"
#include "halo/lib/framework/common.h"
#include "halo/lib/framework/data_layout.h"
#include "halo/lib/framework/global_context.h"
#include "halo/lib/ir/common_cast_instructions.h"
#include "halo/lib/ir/common_instructions.h"
#include "halo/lib/ir/common_reduction_instructions.h"
#include "halo/lib/ir/ir_builder.h"
#include "halo/lib/ir/math_instructions.h"
#include "halo/lib/ir/nn_cnn_instructions.h"
#include "halo/lib/transforms/transforms_util.h"
#include "halo/lib/transforms/type_legalizer.h"
namespace halo {
template <typename T>
static Constant* RunConstantFoldingOnMathBinary(const std::string& name,
const Type& ret_type, Def op0,
Def op1, OpCode opcode,
KindPredicate pred) {
if (!IsA<Constant>(op0.GetOwner()) || !IsA<Constant>(op1.GetOwner()) ||
op0.GetType().GetTotalNumOfElements() !=
op1.GetType().GetTotalNumOfElements()) {
return nullptr;
}
if (opcode == OpCode::CMP) {
if (pred == KindPredicate::GE) {
pred = KindPredicate::LT;
std::swap(op0, op1);
} else if (pred == KindPredicate::GT) {
pred = KindPredicate::LE;
std::swap(op0, op1);
}
}
Constant* c_lhs = DynCast<Constant>(op0.GetOwner());
Constant* c_rhs = DynCast<Constant>(op1.GetOwner());
size_t num_elements = op0.GetType().GetTotalNumOfElements();
Constant* c_ret = nullptr;
ConstantBuilder cb(DynCast<Function>(c_lhs->GetParent()));
std::vector<T> ret;
ret.reserve(num_elements);
switch (opcode) {
case OpCode::ADD: {
for (size_t i = 0; i < num_elements; ++i) {
ret.push_back(c_lhs->GetData<T>(i) + c_rhs->GetData<T>(i));
}
c_ret = cb.CreateConstant(name, ret_type, ret.data());
break;
}
case OpCode::MUL: {
for (size_t i = 0; i < num_elements; ++i) {
ret.push_back(c_lhs->GetData<T>(i) * c_rhs->GetData<T>(i));
}
c_ret = cb.CreateConstant(name, ret_type, ret.data());
break;
}
case OpCode::DIV: {
for (size_t i = 0; i < num_elements; ++i) {
ret.push_back(c_lhs->GetData<T>(i) / c_rhs->GetData<T>(i));
}
c_ret = cb.CreateConstant(name, ret_type, ret.data());
break;
}
case OpCode::CMP: {
std::vector<int8_t> ret;
switch (pred) {
case KindPredicate::LT: {
for (size_t i = 0; i < num_elements; ++i) {
if (c_lhs->GetData<T>(i) < c_rhs->GetData<T>(i)) {
ret.push_back(1);
} else {
ret.push_back(0);
}
}
c_ret = cb.CreateConstant(name, ret_type, ret.data());
break;
}
default: {
break;
}
}
break;
}
default: {
break;
}
}
return c_ret;
}
template <typename T>
static T* FuseToConvDeConv(const T* conv, OpCode opc, const Constant* c) {
HLCHECK(IsA<Constant>(conv->GetOperand(1)));
const auto kernel = DynCast<Constant>(conv->GetOperand(1));
const auto& kernel_type = kernel->GetResultType();
const auto& info = ImageAxisInfo::GetImageAxisInfo(conv->GetDataFormat(),
conv->GetFilterFormat());
auto group = conv->GetGroup();
if (group < 1 || !conv->GetResultType().IsValid()) {
return nullptr;
}
unsigned output_dim = info.kernel_output_axis;
auto output_ch =
conv->GetResultType().GetNumOfElementsInDim(info.data_channel_axis);
bool has_valid_bias =
conv->GetNumOfOperands() == 2 ||
(conv->GetNumOfOperands() == 3 && IsA<Constant>(conv->GetOperand(2)) &&
conv->GetOperand(2).GetType().GetTotalNumOfElements() == output_ch);
if (!has_valid_bias) {
return nullptr;
}
ConstantBuilder cb(conv->GetParent()->GetParent());
IRBuilder builder(conv->GetParent());
builder.SetInsertAfter(conv);
auto n = c->GetResultType().GetTotalNumOfElements();
if (!has_valid_bias || output_ch != n) {
return nullptr;
}
auto ops = conv->GetOperands();
const Constant* op_bias = conv->GetNumOfOperands() == 3
? DynCast<Constant>(conv->GetOperand(2))
: nullptr;
if (opc == OpCode::MUL) {
std::vector<float> data(kernel_type.GetTotalNumOfElements());
size_t extend = 1;
for (auto i = kernel_type.GetNumOfDims() - 1; i > output_dim; --i) {
extend *= kernel_type.GetNumOfElementsInDim(i);
}
for (size_t i = 0, e = data.size(); i < e; ++i) {
auto idx = (i / extend) % n;
data[i] = kernel->template GetData<float>(i) * c->GetData<float>(idx);
}
auto new_kernel =
cb.CreateConstant(kernel->GetName(), kernel_type, data.data());
ops[1] = *new_kernel;
if (op_bias != nullptr) {
std::vector<float> data(output_ch);
for (int i = 0; i < output_ch; ++i) {
data[i] = op_bias->GetData<float>(i) * c->GetData<float>(i);
}
auto new_bias = cb.CreateConstant(op_bias->GetName(),
op_bias->GetResultType(), data.data());
ops[2] = *new_bias;
}
} else {
std::vector<int64_t> shape(kernel_type.GetNumOfDims(), 1);
shape[info.data_channel_axis] = n;
halo::Type ty{kernel_type.GetDataType(), shape};
std::vector<float> data(output_ch);
for (int i = 0; i < output_ch; ++i) {
data[i] = (op_bias == nullptr ? 0 : op_bias->GetData<float>(i)) +
c->GetData<float>(i);
}
auto new_bias = cb.CreateConstant(c->GetName(), ty, data.data());
if (ops.size() == 3) {
ops.pop_back();
}
ops.push_back(*new_bias);
}
auto new_conv = builder.Clone(*conv, ops);
return DynCast<T>(new_conv);
}
static std::pair<Def, Def> RunOnMathBinaryInstruction(Instruction* binary_inst,
bool disable_broadcasting,
bool fuse_conv_bias) {
Def orig_def{binary_inst, 0};
auto op0 = binary_inst->GetOperand(0);
auto op1 = binary_inst->GetOperand(1);
bool has_swapped = false;
if (IsA<Constant>(op0)) {
std::swap(op0, op1);
has_swapped = true;
}
// MUL(x, 1) ==> x.
if (binary_inst->GetOpCode() == OpCode::MUL && IsA<Constant>(op1)) {
const Constant* c = DynCast<Constant>(op1);
if (c->HasSameValueOf(1)) {
return {orig_def, op0};
}
}
ConstantBuilder cb(binary_inst->GetParent()->GetParent());
IRBuilder builder(binary_inst->GetParent());
builder.SetInsertAfter(binary_inst);
// Fuse mul/add into conv.
auto opc = binary_inst->GetOpCode();
if ((opc == OpCode::MUL || (fuse_conv_bias && opc == OpCode::ADD)) &&
IsA<Constant>(op1)) {
const Constant* c = DynCast<Constant>(op1);
// check if mul can be fused with conv
auto op0_opc = IsA<Instruction>(op0)
? DynCast<Instruction>(op0)->GetOpCode()
: OpCode::INVALID;
Instruction* new_inst = nullptr;
if (op0_opc == OpCode::CONV2D) {
new_inst = FuseToConvDeConv(DynCast<Conv2DInst>(op0), opc, c);
} else if (op0_opc == OpCode::CONV2DTRANSPOSE) {
new_inst = FuseToConvDeConv(DynCast<Conv2DTransposeInst>(op0), opc, c);
}
if (new_inst != nullptr) {
return {orig_def, *new_inst};
}
}
const auto& op0_type = op0.GetType();
const auto& op1_type = op1.GetType();
OpCode opcode = binary_inst->GetOpCode();
/*
// Handle scalar constant
if (IsA<Constant>(op1.GetOwner())) {
Constant* c_op1 = DynCast<Constant>(op1.GetOwner());
Type ret_type = binary_inst->GetResultsTypes()[0];
HLCHECK(ret_type.IsValid());
if (c_op1->IsScalarZero()) {
if (opcode == OpCode::ADD) {
return {orig_def, op0};
}
if (opcode == OpCode::MUL) {
Constant* c_zero =
cb.SplatConstantZero(binary_inst->GetName(), ret_type);
return {orig_def, *c_zero};
}
}
if (c_op1->IsScalarOne()) {
if (opcode == OpCode::MUL) {
return {orig_def, op0};
}
}
}*/
const int64_t folding_threshold = 10;
// Both operands are constant, do constant folding
if (IsA<Constant>(op0) && IsA<Constant>(op1) &&
op0_type.GetTotalNumOfElements() == op1_type.GetTotalNumOfElements() &&
op0_type.GetTotalNumOfElements() < folding_threshold) {
Type ret_type = binary_inst->GetResultsTypes()[0];
HLCHECK(ret_type.IsValid());
KindPredicate pred = KindPredicate::INVALID;
if (opcode == OpCode::CMP) {
pred = static_cast<CmpInst*>(binary_inst)->GetPredicator(); // NOLINT
}
if (has_swapped) {
std::swap(op0, op1);
}
Constant* c_ret = nullptr;
switch (op0_type.GetDataType()) {
case DataType::INT32: {
c_ret = RunConstantFoldingOnMathBinary<int>(
binary_inst->GetName() + "_folding", ret_type, op0, op1, opcode,
pred);
break;
}
case DataType::INT64: {
c_ret = RunConstantFoldingOnMathBinary<int64_t>(
binary_inst->GetName() + "_folding", ret_type, op0, op1, opcode,
pred);
break;
}
case DataType::FLOAT32: {
c_ret = RunConstantFoldingOnMathBinary<float>(
binary_inst->GetName() + "_folding", ret_type, op0, op1, opcode,
pred);
break;
}
default:
c_ret = nullptr;
}
if (c_ret != nullptr) {
return {orig_def, *c_ret};
}
return {orig_def, orig_def};
}
// Do offline broadcasting.
if (!disable_broadcasting && op0_type.IsValid() && IsA<Constant>(op1) &&
op0_type.GetNumOfDims() != op1_type.GetNumOfDims() &&
op0_type.GetTotalNumOfElements() >= op1_type.GetTotalNumOfElements() &&
op0_type.GetNumOfElementsInDim(op0_type.GetNumOfDims() - 1) != 1) {
size_t lhs_cnt = op0_type.GetTotalNumOfElements();
size_t rhs_cnt = op1_type.GetTotalNumOfElements();
auto orig_addend = DynCast<Constant>(op1.GetOwner());
HLCHECK(lhs_cnt % rhs_cnt == 0);
HLCHECK(op1_type.GetDataType() == op0_type.GetDataType());
auto copies = lhs_cnt / rhs_cnt;
size_t copy_size = rhs_cnt * orig_addend->GetElementSizeInBytes();
std::vector<char> buf(copies * copy_size);
for (size_t i = 0; i < copies; ++i) {
memcpy(&buf[copy_size * i], orig_addend->GetRawDataPtr(), copy_size);
}
auto addend = cb.CreateConstant(orig_addend->GetName() + "_broadcasted_" +
std::to_string(binary_inst->GetId()),
op0_type, buf.data());
auto new_add = has_swapped ? builder.CreateBinary(binary_inst->GetName(),
*addend, op0, opcode)
: builder.CreateBinary(binary_inst->GetName(),
op0, *addend, opcode);
new_add->GetResultsTypes()[0] = binary_inst->GetResultsTypes()[0];
return {orig_def, *new_add};
}
if (op0_type.IsValid() && IsA<Constant>(op1) && IsA<Instruction>(op0) &&
op1_type.BroadcastableTo(op0_type)) {
Instruction* op0_inst = DynCast<Instruction>(op0.GetDef());
if (op0_inst->GetOpCode() == OpCode::TRANSPOSE &&
!IsA<Argument>(op0_inst->GetOperand(0))) {
// Add(transpose(op0), op1) ==> transpose(add(op0, transpose'(op1))
TransposeInst* orig_transpose = DynCast<TransposeInst>(op0_inst);
IRBuilder builder(binary_inst->GetParent());
builder.SetInsertAfter(binary_inst);
const auto& orig_perm = orig_transpose->GetPermutation();
Instruction* new_op1 = nullptr;
if (op1_type.GetSqueezedNumOfDims() == 1) {
auto dims = std::vector<int64_t>(op0_type.GetNumOfDims(), 1);
int64_t op1_vector_axis = op0_type.GetNumOfDims() - 1;
for (auto n = op1_type.GetTotalNumOfElements(); op1_vector_axis >= 0;
--op1_vector_axis) {
if (op0_type.GetNumOfElementsInDim(op1_vector_axis) == n) {
break;
}
}
dims[orig_perm[op1_vector_axis]] = op1_type.GetTotalNumOfElements();
ConstantBuilder cb(binary_inst->GetParent()->GetParent());
Constant* c_shape = cb.CreateConstant(
op1.GetDef()->GetName() + "_shape",
halo::Type{DataType::INT64, {static_cast<int64_t>(dims.size())}},
dims.data());
auto new_addend = builder.CreateReshape(op1.GetDef()->GetName() + "_r",
{op1, *c_shape});
new_op1 = new_addend;
new_addend->GetResultsTypes()[0] =
Type{op1.GetType().GetDataType(), dims};
} else {
auto reverse_perm = orig_perm;
for (int i = 0, e = orig_perm.size(); i < e; ++i) {
reverse_perm[orig_perm[i]] = i;
}
auto new_addend =
builder.CreateTranspose(op1.GetDef()->GetName() + "_t", {op1});
new_addend->SetPermutation(reverse_perm);
new_op1 = new_addend;
}
auto new_binary =
builder.CreateBinary(binary_inst->GetName(),
op0.GetDef()->GetOperand(0), *new_op1, opcode);
TransposeInst* new_transpose =
builder.CreateTranspose("t_" + binary_inst->GetName(), {*new_binary});
new_transpose->SetPermutation(orig_perm);
return {orig_def, *new_transpose};
}
}
// add(transpose(v0), transpose(v1)) => transpose(v0, v1)
if (IsA<Instruction>(op0) && IsA<Instruction>(op1)) {
const Instruction* op0_inst = DynCast<Instruction>(op0);
const Instruction* op1_inst = DynCast<Instruction>(op1);
if (op0_inst->GetOpCode() == OpCode::TRANSPOSE &&
op1_inst->GetOpCode() == OpCode::TRANSPOSE) {
const TransposeInst* tr0 = DynCast<const TransposeInst>(op0_inst);
const TransposeInst* tr1 = DynCast<const TransposeInst>(op1_inst);
if (tr0->GetPermutation() == tr1->GetPermutation()) {
IRBuilder builder(binary_inst->GetParent());
builder.SetInsertAfter(binary_inst);
auto new_binary = builder.CreateAdd(
binary_inst->GetName(), tr0->GetOperand(0), tr1->GetOperand(0));
TransposeInst* new_tr = builder.CreateTranspose(
binary_inst->GetName() + "_t", {*new_binary});
new_tr->SetPermutation(tr0->GetPermutation());
return {orig_def, *new_tr};
}
}
}
return {orig_def, orig_def};
}
template <typename ReduceInstTy, typename Build>
static std::pair<Def, Def> EliminateTranspose(ReduceInstTy* inst, Build build) {
Def orig_def{inst, 0};
std::pair<Def, Def> ret{orig_def, orig_def};
// ReduceMean(tranpose(x, {t0, t1, t2, t3}, {a0, a1, a2...}) => ReduceMean(x,
// permed_axis)
Def op0 = inst->GetOperand(0);
if (IsA<Instruction>(op0.GetOwner()) &&
DynCast<Instruction>(op0.GetOwner())->GetOpCode() == OpCode::TRANSPOSE) {
IRBuilder builder(inst->GetParent());
builder.SetInsertAfter(inst);
const TransposeInst* transpose = DynCast<TransposeInst>(op0.GetOwner());
const auto& perm = transpose->GetPermutation();
const auto& orig_axes = inst->GetAxis();
std::vector<int> new_axes(orig_axes.size());
std::transform(orig_axes.begin(), orig_axes.end(), new_axes.begin(),
[&perm](int x) { return perm[x]; });
ReduceInstTy* new_inst =
build(builder, inst->GetName(), transpose->GetOperand(0));
new_inst->SetAxis(new_axes);
ret.second = *new_inst;
return ret;
}
return ret;
}
static std::pair<Def, Def> RunOnCommonReductionInstruction(Instruction* inst) {
Def orig_def{inst, 0};
auto op0 = inst->GetOperand(0);
const Type& dst_type = inst->GetResultsTypes()[0];
const Type& op0_type = op0.GetType();
OpCode opcode = inst->GetOpCode();
// Move the constant axis into attribute.
if (inst->GetNumOfOperands() > 1 && IsA<Constant>(inst->GetOperand(1))) {
const Constant* data = DynCast<Constant>(inst->GetOperand(1).GetOwner());
const Type& ty = data->GetResultType();
if (ty.GetDataType() == DataType::INT32) {
const int32_t* ptr = data->GetDataPtr<int32_t>();
std::vector<int> axis(ptr, ptr + ty.GetTotalNumOfElements()); // NOLINT
IRBuilder builder(inst->GetParent());
builder.SetInsertAfter(inst);
Instruction* ret = nullptr;
switch (opcode) {
case OpCode::REDUCEMEAN: {
ReduceMeanInst* new_inst = DynCast<ReduceMeanInst>(
builder.Clone(*inst, {inst->GetOperand(0)}));
new_inst->SetAxis(axis);
ret = new_inst;
break;
}
case OpCode::ARGMAX: {
ArgmaxInst* new_inst =
DynCast<ArgmaxInst>(builder.Clone(*inst, {inst->GetOperand(0)}));
new_inst->SetAxis(axis.at(0));
ret = new_inst;
break;
}
default: {
break;
}
}
if (ret != nullptr) {
ret->GetResultsTypes()[0] = inst->GetResultType();
return {orig_def, *ret};
}
}
}
if (inst->GetNumOfOperands() == 1) {
std::pair<Def, Def> ret{orig_def, orig_def};
switch (opcode) {
case OpCode::REDUCEMIN: {
ret = EliminateTranspose(
DynCast<ReduceMinInst>(inst),
[](IRBuilder& builder, const std::string& name, const Def& def) {
return builder.CreateReduceMin(name, {def});
});
break;
}
case OpCode::REDUCEMAX: {
ret = EliminateTranspose(
DynCast<ReduceMaxInst>(inst),
[](IRBuilder& builder, const std::string& name, const Def& def) {
return builder.CreateReduceMax(name, {def});
});
break;
}
case OpCode::REDUCEMEAN: {
ret = EliminateTranspose(
DynCast<ReduceMeanInst>(inst),
[](IRBuilder& builder, const std::string& name, const Def& def) {
return builder.CreateReduceMean(name, {def});
});
break;
}
case OpCode::REDUCEPRODUCT: {
ret = EliminateTranspose(
DynCast<ReduceProductInst>(inst),
[](IRBuilder& builder, const std::string& name, const Def& def) {
return builder.CreateReduceProduct(name, {def});
});
break;
}
default: {
break;
}
}
if (ret.first != ret.second) {
return ret;
}
}
if (!dst_type.IsValid() || !IsA<Constant>(op0.GetOwner()) ||
op0_type.GetNumOfDims() > 1) {
return {orig_def, orig_def};
}
ConstantBuilder cb(inst->GetParent()->GetParent());
Constant* c_input = DynCast<Constant>(op0.GetOwner());
DataType dt = op0_type.GetDataType();
if (op0_type.GetTotalNumOfElements() == 1) {
Constant* c_ret = nullptr;
if (opcode == OpCode::ARGMAX || opcode == OpCode::ARGMIN) {
int ret = 0;
c_ret = cb.CreateConstant(inst->GetName() + "_folding", dst_type, &ret);
} else {
c_ret = cb.CreateConstant(inst->GetName() + "_folding", dst_type,
c_input->GetRawDataPtr());
}
return {orig_def, *c_ret};
}
if (dt == DataType::INT32) {
switch (opcode) {
case OpCode::REDUCEMIN:
case OpCode::REDUCEMAX:
case OpCode::ARGMAX: {
int ret = std::numeric_limits<int32_t>::lowest();
int index = -1;
for (int i = 0; i < op0_type.GetTotalNumOfElements(); ++i) {
int data_i = c_input->GetData<int>(i);
ret = std::max(ret, data_i);
if (ret == data_i) {
index = i;
}
}
if (opcode == OpCode::REDUCEMAX || opcode == OpCode::REDUCEMIN) {
auto new_def =
cb.CreateConstant(inst->GetName() + "_folding", dst_type, &ret);
return {orig_def, *new_def};
}
// ARGMAX
auto new_def =
cb.CreateConstant(inst->GetName() + "_folding", dst_type, &index);
return {orig_def, *new_def};
}
case OpCode::REDUCEMEAN:
case OpCode::REDUCESUM: {
int ret = 0;
for (int i = 0; i < op0_type.GetTotalNumOfElements(); ++i) {
ret += c_input->GetData<int>(i);
}
if (opcode == OpCode::REDUCEMEAN) {
ret /= op0_type.GetTotalNumOfElements();
}
auto new_def =
cb.CreateConstant(inst->GetName() + "_folding", dst_type, &ret);
return {orig_def, *new_def};
}
case OpCode::REDUCEPRODUCT: {
int ret = 1;
for (int i = 0; i < op0_type.GetTotalNumOfElements(); ++i) {
ret *= c_input->GetData<int>(i);
}
auto new_def =
cb.CreateConstant(inst->GetName() + "_folding", dst_type, &ret);
return {orig_def, *new_def};
}
default: {
return {orig_def, orig_def};
}
}
}
return {orig_def, orig_def};
}
/// By default, nothing is updated.
std::pair<Def, Def> InstSimplify::RunOnInstruction(Instruction* inst) {
switch (inst->GetOpCode()) {
case OpCode::ADD:
case OpCode::MUL:
case OpCode::DIV:
case OpCode::SUB:
case OpCode::CMP: {
return RunOnMathBinaryInstruction(inst, disable_broadcasting_,
fuse_conv_bias_);
}
case OpCode::REDUCEMAX:
case OpCode::REDUCEMIN:
case OpCode::REDUCEMEAN:
case OpCode::REDUCESUM:
case OpCode::REDUCEPRODUCT:
case OpCode::ARGMAX:
case OpCode::ARGMIN: {
return RunOnCommonReductionInstruction(inst);
}
default: {
return std::make_pair(Def{inst, 0}, Def{inst, 0});
}
}
}
template <typename InstType, typename Builder>
static std::pair<Def, Def> SinkTranspose(InstType& inst, Builder build) {
std::pair<Def, Def> ret{Def{&inst, 0}, Def{&inst, 0}};
if (IsA<Instruction>(inst.GetOperand(0))) {
// Inst(transpose(x)) -> transpose(Inst(x)), this exposes opportunites
// to cancel out transposes.
Instruction* op0_inst = DynCast<Instruction>(inst.GetOperand(0));
if (op0_inst->GetOpCode() == OpCode::TRANSPOSE) {
const TransposeInst* orig_trans = DynCast<TransposeInst>(op0_inst);
IRBuilder builder(inst.GetParent());
builder.SetInsertAfter(&inst);
InstType* new_inst =
build(builder, inst.GetName(), op0_inst->GetOperand(0));
TransposeInst* new_trans =
builder.CreateTranspose(inst.GetName() + "_t", {*new_inst});
new_trans->SetPermutation(orig_trans->GetPermutation());
ret.second = *new_trans;
return ret;
}
}
return ret;
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(LeakyReluInst* inst) {
return SinkTranspose(*inst, [inst](IRBuilder& builder,
const std::string& name, const Def& op) {
auto new_inst = builder.CreateLeakyRelu(name, op);
new_inst->SetAlpha(inst->GetAlpha());
return new_inst;
});
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(PReluInst* inst) {
auto op1 = inst->GetOperand(1);
return SinkTranspose(
*inst,
[inst, &op1](IRBuilder& builder, const std::string& name, const Def& op) {
return DynCast<PReluInst>(builder.Clone(*inst, {op, op1}));
});
}
template <typename T>
static Constant* GetPermutedConstant(ConstantBuilder* cb, const Constant* orig,
const std::vector<int32_t>& perm) {
const auto& shape_type = orig->GetResultType();
auto ranks = shape_type.GetTotalNumOfElements();
std::vector<T> data(ranks);
for (int64_t i = 0; i < ranks; ++i) {
data[perm[i]] = orig->GetData<T>(i);
}
return cb->CreateConstant(orig->GetName(), shape_type, data.data());
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(ResizeInst* inst) {
Def orig_def{inst, 0};
auto op_shape = inst->GetOperand(1);
if (IsA<Instruction>(inst->GetOperand(0))) {
Instruction* op0_inst =
DynCast<Instruction>(inst->GetOperand(0).GetOwner());
if (auto op1 = inst->GetOperand(1);
op0_inst->GetOpCode() == OpCode::TRANSPOSE && IsA<Constant>(op1)) {
Constant* shape = DynCast<Constant>(op1);
const auto& shape_type = shape->GetResultType();
ConstantBuilder cb(inst->GetParent()->GetParent());
auto orig_perm = DynCast<TransposeInst>(op0_inst)->GetPermutation();
Constant* new_shape = nullptr;
switch (shape_type.GetDataType()) {
case DataType::INT32: {
new_shape = GetPermutedConstant<int32_t>(&cb, shape, orig_perm);
break;
}
case DataType::INT64: {
new_shape = GetPermutedConstant<int64_t>(&cb, shape, orig_perm);
break;
}
case DataType::FLOAT32: {
new_shape = GetPermutedConstant<float>(&cb, shape, orig_perm);
break;
}
default:
HLCHECK(0 && "Invalid resize shape type");
}
new_shape->SetName(inst->GetName() + "_resize_shape");
return SinkTranspose(
*inst, [new_shape, inst](IRBuilder& builder, const std::string& name,
const Def& op) {
auto new_inst = builder.CreateResize(name, {op, *new_shape});
new_inst->CopyAttrsFrom(*inst);
new_inst->SetAxesMask(-1);
return new_inst;
});
}
}
return {orig_def, orig_def};
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(Relu6Inst* inst) {
return SinkTranspose(
*inst, [](IRBuilder& builder, const std::string& name, const Def& op) {
return builder.CreateRelu6(name, op);
});
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(SigmoidInst* inst) {
return SinkTranspose(
*inst, [](IRBuilder& builder, const std::string& name, const Def& op) {
return builder.CreateSigmoid(name, op);
});
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(ReluInst* inst) {
return SinkTranspose(
*inst, [](IRBuilder& builder, const std::string& name, const Def& op) {
return builder.CreateRelu(name, op);
});
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(Conv2DInst* inst) {
std::pair<Def, Def> ret{Def{inst, 0}, Def{inst, 0}};
if (!inst->GetResultType().IsValid()) {
return ret;
}
Def op_input = inst->GetOperand(0);
Def op_kernel = inst->GetOperand(1);
IRBuilder builder(inst->GetParent());
builder.SetInsertAfter(inst);
// Convert conv(pad(x, amt), kernel) to conv(x, kernel) to eliminate
// pad op.
if (IsA<Instruction>(op_input) &&
DynCast<Instruction>(op_input)->GetOpCode() == OpCode::PAD) {
const PadInst* pad = DynCast<PadInst>(op_input);
Def pad_op0 = pad->GetOperand(0);
Def pad_op1 = pad->GetOperand(1);
if (IsA<Constant>(pad_op1.GetOwner())) {
const Constant* pad_amt = DynCast<Constant>(pad_op1);
unsigned dims = pad_amt->GetResultType().GetNumOfDims();
if (dims == 2 &&
pad_amt->GetResultType().GetTotalNumOfElements() == 4 * dims) {
std::vector<int32_t> vals(
pad_amt->GetDataPtr<int32_t>(),
pad_amt->GetDataPtr<int32_t>() + 4 * dims); // NOLINT
if (vals[0] != 0 || vals[1] != 0) {
return ret;
}
const auto& info = ImageAxisInfo::GetImageAxisInfo(
inst->GetDataFormat(), inst->GetFilterFormat());
std::array<int, 4> indices_nc = {0, 1, info.data_channel_axis * 2,
info.data_channel_axis * 2 + 1};
// No paddings on N & C.
for (auto idx : indices_nc) {
if (vals[idx] != 0) {
return ret;
}
}
std::array<int, 4> indices_hw = {
info.data_height_axis * 2, info.data_height_axis * 2 + 1,
info.data_width_axis * 2, info.data_width_axis + 1};
Conv2DInst* new_inst =
builder.CreateConv2D(inst->GetName(), {pad_op0, op_kernel});
new_inst->SetDataFormat(inst->GetDataFormat());
new_inst->SetFilterFormat(inst->GetFilterFormat());
new_inst->SetDilations(inst->GetDilations());
new_inst->SetStrides(inst->GetStrides());
new_inst->SetPaddingTop(inst->GetPaddingTop() + vals[indices_hw[0]]);
new_inst->SetPaddingBottom(inst->GetPaddingBottom() +
vals[indices_hw[1]]);
new_inst->SetPaddingLeft(inst->GetPaddingLeft() + vals[indices_hw[2]]);
new_inst->SetPaddingRight(inst->GetPaddingRight() +
vals[indices_hw[3]]);
new_inst->GetResultsTypes()[0] = inst->GetResultsTypes()[0];
new_inst->SetPadding(Padding::EXPLICIT);
ret.second = Def(new_inst, 0);
}
}
}
// Convert Conv(add(x, c), k) => Conv(x, k') or Conv(mul(x, c), k) ==>
// Conv(x, k') where k is a constant of scalar or channel-wise vector.
if (IsA<Instruction>(op_input) && IsA<Constant>(op_kernel) &&
inst->GetGroup() == 1 && inst->GetResultType().IsValid() &&
(DynCast<Instruction>(op_input)->GetOpCode() == OpCode::ADD ||
DynCast<Instruction>(op_input)->GetOpCode() == OpCode::MUL)) {
Instruction* binary_inst = DynCast<Instruction>(op_input);
auto binary_op0 = binary_inst->GetOperand(0);
if (IsA<Instruction>(binary_op0) &&
DynCast<Instruction>(binary_op0)->GetOpCode() == OpCode::CONV2D) {
// For pattens like a = conv(); b = a + c; d = conv(b), prefer to fuse a
// and b.
return ret;
}
auto binary_op1 = binary_inst->GetOperand(1);
if (!IsA<Constant>(binary_op1)) {
return ret;
}
const auto& kernel_type = op_kernel.GetType();
Constant* c = DynCast<Constant>(binary_op1);
if (kernel_type.GetDataType() != DataType::FLOAT32 ||
kernel_type.GetDataType() != c->GetResultType().GetDataType()) {
return ret;
}
// match shape of C: expect [..,in_chs, 1, 1].
auto n_elems = c->GetResultType().GetTotalNumOfElements();
auto dims = c->GetResultType().GetDimSizes();
auto kernel_shape = kernel_type.GetDimSizes();
const auto& info = ImageAxisInfo::GetImageAxisInfo(inst->GetDataFormat(),
inst->GetFilterFormat());
auto in_chs = kernel_shape[info.kernel_input_axis];
auto in_chs_dim_r =
info.kernel_input_axis - kernel_shape.size(); // Dims in backwards.
if (!(n_elems == in_chs &&
(dims.size() == 1 || (-in_chs_dim_r <= dims.size() &&
dims[dims.size() + in_chs_dim_r] == in_chs)))) {
return ret;
}
bool has_padding =
inst->GetPaddingBottom() != 0 || inst->GetPaddingLeft() != 0 ||
inst->GetPaddingTop() != 0 || inst->GetPaddingRight() != 0;
Constant* kernel = DynCast<Constant>(op_kernel);
ConstantBuilder cb(inst->GetParent()->GetParent());
std::vector<float> new_kernel_data(kernel_type.GetTotalNumOfElements());
auto operands = inst->GetOperands();
operands[0] = binary_op0;
std::vector<size_t> strides(kernel_shape.size(), 1);
for (int64_t i = kernel_shape.size() - 2; i >= 0; --i) {
strides[i] = strides[i + 1] * kernel_shape[i + 1];
}
if (binary_inst->GetOpCode() == OpCode::MUL) {
for (size_t i = 0, e = kernel_type.GetTotalNumOfElements(); i < e; ++i) {
size_t ch = (i / strides[info.kernel_input_axis]) % in_chs;
new_kernel_data[i] =
kernel->GetDataAsFloat32(i) * c->GetDataAsFloat32(ch);
}
auto new_kernel =
cb.CreateConstant(kernel->GetName(), kernel_type, new_kernel_data);
operands[1] = *new_kernel;
ret.second = *builder.Clone(*inst, operands);
} else if (!has_padding && (inst->GetNumOfOperands() == 2 ||
(inst->GetNumOfOperands() == 3 &&
IsA<Constant>(inst->GetOperand(2))))) {
auto out_chs = kernel_shape[info.kernel_output_axis];
// Conv(x + c), k) ==> Conv(x, k) + c * k)
// C is vector (len = in_chs), reshape k to (H * W, out_chs, in_chs)
std::vector<float> new_bias(out_chs);
std::string bias_name = inst->GetName() + "_bias";
if (inst->GetNumOfOperands() == 3) {
auto orig_bias = DynCast<Constant>(inst->GetOperand(2));
bias_name = orig_bias->GetName() + "_fused";
HLCHECK(orig_bias->GetResultType().GetTotalNumOfElements() == out_chs);
for (int i = 0; i < out_chs; ++i) {
new_bias[i] = orig_bias->GetDataAsFloat32(i);
}
}
auto hw = kernel_type.GetTotalNumOfElements() / in_chs / out_chs;
auto stride_s = strides[info.kernel_width_axis];
auto stride_o = strides[info.kernel_output_axis];
auto stride_i = strides[info.kernel_input_axis];
for (int s = 0; s < hw; ++s) {
for (int och = 0; och < out_chs; ++och) {
std::vector<float> m(in_chs);
float t = 0;
for (int i = 0; i < in_chs; ++i) {
t += kernel->GetDataAsFloat32(s * stride_s + och * stride_o +
i * stride_i) *
c->GetDataAsFloat32(i);
}
new_bias[och] += t;
}
}
halo::Type type{kernel_type.GetDataType(), {out_chs}};
auto new_bias_op = cb.CreateConstant(bias_name, type, new_bias);
if (operands.size() >= 3) {
operands[2] = *new_bias_op;
} else {
operands.push_back(*new_bias_op);
}
ret.second = *builder.Clone(*inst, operands);
}
}
return ret;
}
static void Pad(char* dst, const char* src, size_t elems_num, size_t elem_size,
const std::vector<int64_t>& orig_shape,
const std::vector<int64_t>& new_shape,
const std::vector<int32_t>& padding_amt) {
std::vector<size_t> pos(orig_shape.size());
std::vector<size_t> dst_strides(orig_shape.size(), 1);
int dims = orig_shape.size();
for (int i = dims - 2; i >= 0; --i) {
dst_strides[i] = dst_strides[i + 1] * new_shape[i + 1];
}
for (size_t i = 0; i < elems_num; ++i) {
auto dst_pos = pos;
for (int j = 0; j < dims; ++j) {
dst_pos[j] += padding_amt[j];
}
size_t dst_offset = std::inner_product(dst_pos.begin(), dst_pos.end(),
dst_strides.begin(), 0UL) *
elem_size;
std::copy(src, src + elem_size, dst + dst_offset); // NOLINT.
src += elem_size; // NOLINT.
int c = 1;
for (int j = dims - 1; j >= 0 && c == 1; --j) {
pos[j] += c;
if (pos[j] >= static_cast<size_t>(orig_shape[j])) {
pos[j] = 0;
} else {
c = 0;
}
}
}
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(PadInst* pad_inst) {
Def orig_def{pad_inst, 0};
Def op0 = pad_inst->GetOperand(0);
Def op1 = pad_inst->GetOperand(1);
if (!IsA<Constant>(op0.GetOwner()) || !IsA<Constant>(op1.GetOwner()) ||
pad_inst->GetNumOfOperands() != 2 ||
pad_inst->GetMode() != PadMode::CONSTANT) {
return {orig_def, orig_def};
}
const Constant* data = DynCast<Constant>(op0.GetOwner());
const Constant* pad_amt = DynCast<Constant>(op1.GetOwner());
ConstantBuilder cb(pad_inst->GetParent()->GetParent());
auto dims = op0.GetType().GetNumOfDims();
std::vector<int64_t> shape(dims);
std::vector<int32_t> paddings_before(dims);
for (size_t i = 0; i < dims; ++i) {
int32_t before = pad_amt->GetDataPtr<int32_t>()[i * 2]; // NOLINT
int32_t after = pad_amt->GetDataPtr<int32_t>()[i * 2 + 1]; // NOLINT
shape[i] = op0.GetType().GetNumOfElementsInDim(i) + before + after;
paddings_before[i] = before;
}
halo::Type type{op0.GetType().GetDataType(), shape};
std::vector<char> w(type.GetTotalNumOfElements() *
data->GetElementSizeInBytes());
std::vector<size_t> dim_sizes(dims);
Pad(w.data(), static_cast<const char*>(data->GetRawDataPtr()),
op0.GetType().GetTotalNumOfElements(), data->GetElementSizeInBytes(),
op0.GetType().GetDimSizes(), shape, paddings_before);
auto new_inst = cb.CreateConstant("folded_pad", type, w.data());
return {orig_def, Def{new_inst, 0}};
}
std::pair<Def, Def> InstSimplify::RunOnInstruction(ReshapeInst* reshape_inst) {
Def orig_def{reshape_inst, 0};
// for reshape(reshape(x, c0), c1), replace it with reshape(x, c1).