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#include <torch/csrc/jit/tensorexpr/ir.h>
#include <torch/csrc/jit/tensorexpr/tensor.h>
#include <c10/util/irange.h>
namespace torch {
namespace jit {
namespace tensorexpr {
static Dtype ChooseDtype(const Dtype& buffer_dtype, const Dtype& index_dtype) {
return Dtype(buffer_dtype, index_dtype.lanes());
}
static Dtype dtypeOfIndices(const std::vector<ExprPtr>& indices) {
if (!indices.size()) {
// Return something so we can handle scalar buffers.
return kInt;
}
return indices.at(0)->dtype();
}
void castIndicesToInts(std::vector<ExprPtr>& indices) {
// Cast all indices to either Int or Long
auto index_dtype = ScalarType::Int;
for (auto& index : indices) {
if (index->dtype().scalar_type() == ScalarType::Long) {
// If any of the indexes is Long, cast all of them to Long
index_dtype = ScalarType::Long;
break;
}
}
for (auto& index : indices) {
const Dtype& dt = index->dtype();
if (c10::isIntegralType(dt.scalar_type(), true) &&
dt.scalar_type() != index_dtype) {
index = alloc<Cast>(Dtype(index_dtype, dt.lanes()), index);
}
}
}
Load::Load(Dtype dtype, BufPtr buf, std::vector<ExprPtr> indices)
: ExprNodeBase(dtype), buf_(buf), indices_(std::move(indices)) {
castIndicesToInts(indices_);
}
Load::Load(BufPtr buf, const std::vector<ExprPtr>& indices)
: Load(ChooseDtype(buf->dtype(), dtypeOfIndices(indices)), buf, indices) {}
ExprHandle Load::make(
Dtype dtype,
const BufHandle& buf,
const std::vector<ExprHandle>& indices) {
return ExprHandle(
alloc<Load>(dtype, buf.node(), ExprHandleVectorToExprVector(indices)));
}
ExprHandle Load::make(
const BufHandle& buf,
const std::vector<ExprHandle>& indices) {
return Load::make(buf.dtype(), buf, indices);
}
Store::Store(BufPtr buf, std::vector<ExprPtr> indices, ExprPtr value)
: buf_(buf), indices_(std::move(indices)), value_(value) {
castIndicesToInts(indices_);
}
StorePtr Store::make(
const BufHandle& buf,
const std::vector<ExprHandle>& indices,
const ExprHandle& value) {
return alloc<Store>(
buf.node(), ExprHandleVectorToExprVector(indices), value.node());
}
StorePtr BufHandle::store(
const std::vector<ExprHandle>& args,
const ExprHandle& value) const {
return Store::make(*this, args, value);
}
ExprPtr flatten_index(
const std::vector<ExprPtr>& dims,
const std::vector<ExprPtr>& indices,
const std::vector<ExprPtr>& strides) {
// Handle already flattened indices first
if (indices.size() == 1) {
return indices[0];
}
size_t ndim = dims.size();
if (ndim != indices.size()) {
throw malformed_input("dimensions mismatch in flatten_index");
}
if (ndim != strides.size()) {
throw malformed_input("strides mismatch in flatten_index");
}
if (ndim == 0) {
return alloc<LongImm>(0);
}
ExprPtr total_index = immLike(indices[0], 0);
for (const auto i : c10::irange(ndim)) {
total_index = alloc<Add>(total_index, alloc<Mul>(indices[i], strides[i]));
}
return total_index;
}
Dtype Intrinsics::IntrinsicsDtype(IntrinsicsOp op_type, Dtype dt1) {
if (op_type == kIsNan) {
return dt1.cloneWithScalarType(ScalarType::Int);
}
// TODO: check the op_type and make a real decision
return dt1;
}
Dtype Intrinsics::IntrinsicsDtype(IntrinsicsOp op_type, Dtype dt1, Dtype dt2) {
// TODO: check the op_type and make a real decision
return dt1;
}
Dtype Intrinsics::IntrinsicsDtype(
IntrinsicsOp op_type,
const std::vector<ExprPtr>& params) {
// TODO: check the op_type and make a real decision
// Doesnt this fail with kRand?
if (params.size() == 0) {
throw malformed_input("invalid params in Intrinsics");
} else if (params.size() == 1) {
return IntrinsicsDtype(op_type, params[0]->dtype());
} else if (params.size() == 2) {
return IntrinsicsDtype(op_type, params[0]->dtype(), params[1]->dtype());
}
return params[0]->dtype();
}
int Intrinsics::OpArgCount(IntrinsicsOp op_type) {
switch (op_type) {
case kSin:
case kCos:
case kTan:
case kAsin:
case kAcos:
case kAtan:
case kSinh:
case kCosh:
case kTanh:
case kSigmoid:
case kExp:
case kExpm1:
case kAbs:
case kLog:
case kLog2:
case kLog10:
case kLog1p:
case kErf:
case kErfc:
case kSqrt:
case kRsqrt:
case kCeil:
case kFloor:
case kRound:
case kTrunc:
case kFrac:
case kLgamma:
case kIsNan:
return 1;
case kRand:
return 0;
case kAtan2:
case kFmod:
case kPow:
case kRemainder:
return 2;
default:
throw std::runtime_error("invalid op_type: " + c10::to_string(op_type));
}
}
ExternalCallPtr ExternalCall::make(
BufHandle buf,
const std::string& func_name,
const std::vector<BufHandle>& buf_args,
const std::vector<ExprHandle>& args) {
std::vector<BufPtr> buf_arg_nodes;
buf_arg_nodes.reserve(buf_args.size());
for (const BufHandle& buf_arg : buf_args) {
buf_arg_nodes.push_back(buf_arg.node());
}
return alloc<ExternalCall>(
buf.node(), func_name, buf_arg_nodes, ExprHandleVectorToExprVector(args));
}
ExternalCallWithAllocPtr ExternalCallWithAlloc::make(
const std::string& func_name,
const std::vector<BufHandle>& buf_out_args,
const std::vector<BufHandle>& buf_args,
const std::vector<ExprHandle>& args) {
std::vector<BufPtr> buf_out_arg_nodes;
buf_out_arg_nodes.reserve(buf_out_args.size());
for (const BufHandle& buf_out_arg : buf_out_args) {
buf_out_arg_nodes.push_back(buf_out_arg.node());
}
std::vector<BufPtr> buf_arg_nodes;
buf_arg_nodes.reserve(buf_args.size());
for (const BufHandle& buf_arg : buf_args) {
buf_arg_nodes.push_back(buf_arg.node());
}
return alloc<ExternalCallWithAlloc>(
func_name,
buf_out_arg_nodes,
buf_arg_nodes,
ExprHandleVectorToExprVector(args));
}
FreeExtPtr FreeExt::make(const std::vector<BufHandle>& bufs) {
std::vector<BufPtr> buf_nodes;
buf_nodes.reserve(bufs.size());
for (const BufHandle& buf : bufs) {
buf_nodes.push_back(buf.node());
}
return alloc<FreeExt>(buf_nodes);
}
std::vector<ExprPtr> ExprHandleVectorToExprVector(
const std::vector<ExprHandle>& v) {
std::vector<ExprPtr> result(v.size());
for (const auto i : c10::irange(v.size())) {
result[i] = v[i].node();
}
return result;
}
std::vector<ExprHandle> ExprVectorToExprHandleVector(
const std::vector<ExprPtr>& v) {
std::vector<ExprHandle> result(v.size());
for (const auto i : c10::irange(v.size())) {
result[i] = ExprHandle(v[i]);
}
return result;
}
std::vector<VarPtr> VarHandleVectorToVarVector(
const std::vector<VarHandle>& v) {
std::vector<VarPtr> result(v.size());
for (const auto i : c10::irange(v.size())) {
result[i] = v[i].node();
}
return result;
}
std::vector<VarHandle> VarVectorToVarHandleVector(
const std::vector<VarPtr>& v) {
std::vector<VarHandle> result(v.size());
for (const auto i : c10::irange(v.size())) {
result[i] = VarHandle(v[i]);
}
return result;
}
bool immediateIsNegative(ExprPtr e) {
#define TYPE_CASE(Type, Name) \
if (Name##ImmPtr imm = to<Name##Imm>(e)) { \
return imm->value() < 0; \
}
AT_FORALL_SCALAR_TYPES_AND2(Half, BFloat16, TYPE_CASE);
#undef TYPE_CASE
return false;
}
bool immediateIsPositive(ExprPtr e) {
#define TYPE_CASE(Type, Name) \
if (Name##ImmPtr imm = to<Name##Imm>(e)) { \
return imm->value() > 0; \
}
AT_FORALL_SCALAR_TYPES_AND3(Bool, Half, BFloat16, TYPE_CASE);
#undef TYPE_CASE
return false;
}
bool immediateIsZero(ExprPtr e) {
#define TYPE_CASE(Type, Name) \
if (Name##ImmPtr imm = to<Name##Imm>(e)) { \
return imm->value() == 0; \
}
AT_FORALL_SCALAR_TYPES_AND3(Bool, Half, BFloat16, TYPE_CASE);
#undef TYPE_CASE
return false;
}
} // namespace tensorexpr
} // namespace jit
} // namespace torch
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