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#include "slang-ir-pytorch-cpp-binding.h"
#include "slang-diagnostics.h"
#include "slang-ir-autodiff.h"
#include "slang-ir-insts.h"
#include "slang-ir-lower-cuda-builtin-types.h"
#include "slang-ir.h"
namespace Slang
{
// Convert a type to a target tuple type.
static IRType* translateToTupleType(IRBuilder& builder, IRType* type)
{
if (as<IRVoidType>(type))
return type;
else if (as<IRBasicType>(type))
return type;
else if (as<IRTorchTensorType>(type))
return type;
else if (auto matrixType = as<IRMatrixType>(type))
{
auto rowCount = as<IRIntLit>(matrixType->getRowCount());
auto colCount = as<IRIntLit>(matrixType->getColumnCount());
if (!rowCount || !colCount)
{
return nullptr;
}
List<IRType*> elementTypes;
for (IRIntegerValue i = 0; i < rowCount->getValue(); i++)
{
elementTypes.addRange(matrixType->getElementType());
}
auto elementTupleType =
builder.getTargetTupleType((UInt)elementTypes.getCount(), elementTypes.getBuffer());
List<IRType*> rowTypes;
for (IRIntegerValue i = 0; i < colCount->getValue(); i++)
{
rowTypes.add(elementTupleType);
}
return builder.getTargetTupleType((UInt)rowTypes.getCount(), rowTypes.getBuffer());
}
else if (auto vectorType = as<IRVectorType>(type))
{
auto count = as<IRIntLit>(vectorType->getElementCount());
if (!count)
{
return nullptr;
}
List<IRType*> elementTypes;
for (IRIntegerValue i = 0; i < count->getValue(); i++)
{
elementTypes.addRange(vectorType->getElementType());
}
return builder.getTargetTupleType((UInt)elementTypes.getCount(), elementTypes.getBuffer());
}
else if (auto arrayType = as<IRArrayType>(type))
{
auto arraySize = as<IRIntLit>(arrayType->getElementCount());
if (!arraySize)
{
return nullptr;
}
List<IRType*> subElementTypes;
auto subElementType = translateToTupleType(builder, arrayType->getElementType());
for (IRIntegerValue i = 0; i < arraySize->getValue(); i++)
{
subElementTypes.addRange(subElementType);
}
return builder.getTargetTupleType(
(UInt)subElementTypes.getCount(),
subElementTypes.getBuffer());
}
else if (auto structType = as<IRStructType>(type))
{
List<IRType*> elementTypes;
for (auto field : structType->getFields())
{
auto fieldType = translateToTupleType(builder, field->getFieldType());
if (!fieldType)
{
return nullptr;
}
elementTypes.addRange(fieldType);
}
return builder.getTargetTupleType((UInt)elementTypes.getCount(), elementTypes.getBuffer());
}
else if (as<IRTargetTupleType>(type))
{
return type;
}
else
{
return nullptr;
}
}
// Convert a value to a target tuple type.
static IRInst* makeTargetTuple(IRBuilder& builder, IRInst* val)
{
auto type = val->getDataType();
if (as<IRVoidType>(type))
return val;
if (as<IRBasicType>(type))
return val;
else if (as<IRTorchTensorType>(type))
return val;
else if (auto matrixType = as<IRMatrixType>(type))
{
auto rowCount = as<IRIntLit>(matrixType->getRowCount());
auto colCount = as<IRIntLit>(matrixType->getColumnCount());
if (!rowCount || !colCount)
{
return nullptr;
}
List<IRInst*> rowElements;
List<IRType*> rowTypes;
for (IRIntegerValue i = 0; i < rowCount->getValue(); i++)
{
List<IRInst*> colElements;
List<IRType*> colTypes;
for (IRIntegerValue j = 0; j < colCount->getValue(); j++)
{
auto elementVal =
builder.emitElementExtract(val, builder.getIntValue(builder.getIntType(), i));
auto tupleElement = makeTargetTuple(builder, elementVal);
if (!tupleElement)
return nullptr;
colElements.add(tupleElement);
colTypes.add(tupleElement->getFullType());
}
auto rowType =
builder.getTargetTupleType((UInt)colTypes.getCount(), colTypes.getBuffer());
rowTypes.add(rowType);
rowElements.add(builder.emitMakeTargetTuple(
rowType,
(UInt)colElements.getCount(),
colElements.getBuffer()));
}
return builder.emitMakeTargetTuple(
builder.getTargetTupleType((UInt)rowTypes.getCount(), rowTypes.getBuffer()),
(UInt)rowElements.getCount(),
rowElements.getBuffer());
}
else if (auto vectorType = as<IRVectorType>(type))
{
auto count = as<IRIntLit>(vectorType->getElementCount());
if (!count)
{
return nullptr;
}
List<IRInst*> resultElements;
List<IRType*> elementTypes;
for (IRIntegerValue i = 0; i < count->getValue(); i++)
{
auto elementVal =
builder.emitElementExtract(val, builder.getIntValue(builder.getIntType(), i));
auto tupleElement = makeTargetTuple(builder, elementVal);
if (!tupleElement)
return nullptr;
resultElements.add(tupleElement);
elementTypes.add(tupleElement->getFullType());
}
auto resultType =
builder.getTargetTupleType((UInt)elementTypes.getCount(), elementTypes.getBuffer());
return builder.emitMakeTargetTuple(
resultType,
(UInt)resultElements.getCount(),
resultElements.getBuffer());
}
else if (auto arrayType = as<IRArrayType>(type))
{
auto arraySize = as<IRIntLit>(arrayType->getElementCount());
if (!arraySize)
{
return nullptr;
}
List<IRInst*> resultElements;
List<IRType*> elementTypes;
for (IRIntegerValue i = 0; i < arraySize->getValue(); i++)
{
auto elementVal =
builder.emitElementExtract(val, builder.getIntValue(builder.getIntType(), i));
auto tupleElement = makeTargetTuple(builder, elementVal);
if (!tupleElement)
return nullptr;
resultElements.add(tupleElement);
elementTypes.add(tupleElement->getFullType());
}
auto resultType =
builder.getTargetTupleType((UInt)elementTypes.getCount(), elementTypes.getBuffer());
return builder.emitMakeTargetTuple(
resultType,
(UInt)resultElements.getCount(),
resultElements.getBuffer());
}
else if (auto structType = as<IRStructType>(type))
{
List<IRInst*> resultElements;
List<IRType*> elementTypes;
for (auto field : structType->getFields())
{
auto elementVal = builder.emitFieldExtract(field->getFieldType(), val, field->getKey());
auto tupleElement = makeTargetTuple(builder, elementVal);
if (!tupleElement)
return nullptr;
resultElements.add(tupleElement);
elementTypes.add(tupleElement->getFullType());
}
auto resultType =
builder.getTargetTupleType((UInt)elementTypes.getCount(), elementTypes.getBuffer());
return builder.emitMakeTargetTuple(
resultType,
(UInt)resultElements.getCount(),
resultElements.getBuffer());
}
else if (as<IRTargetTupleType>(type))
{
return val;
}
else
{
return nullptr;
}
}
// Convert a target tuple type to a value.
static IRInst* makeValueFromTargetTuple(IRBuilder& builder, IRType* type, IRInst* val)
{
if (as<IRVoidType>(type))
return val;
if (as<IRBasicType>(type))
return val;
else if (as<IRTorchTensorType>(type))
return val;
else if (auto matrixType = as<IRMatrixType>(type))
{
auto rowCount = as<IRIntLit>(matrixType->getRowCount());
auto colCount = as<IRIntLit>(matrixType->getColumnCount());
SLANG_ASSERT(rowCount && colCount);
List<IRInst*> resultElements;
auto rowType = builder.getTargetTupleType(
(UInt)colCount->getValue(),
List<IRType*>()
.makeRepeated(matrixType->getElementType(), (Index)colCount->getValue())
.getBuffer());
for (IRIntegerValue i = 0; i < rowCount->getValue(); i++)
{
auto rowElement = builder.emitTargetTupleGetElement(
rowType,
val,
builder.getIntValue(builder.getIntType(), i));
for (IRIntegerValue j = 0; j < colCount->getValue(); j++)
{
auto element = builder.emitTargetTupleGetElement(
matrixType->getElementType(),
rowElement,
builder.getIntValue(builder.getIntType(), j));
resultElements.add(element);
}
}
return builder.emitMakeMatrix(
type,
(UInt)resultElements.getCount(),
resultElements.getBuffer());
}
else if (auto vectorType = as<IRVectorType>(type))
{
auto count = as<IRIntLit>(vectorType->getElementCount());
if (!count)
{
return nullptr;
}
List<IRInst*> resultElements;
auto elementType = vectorType->getElementType();
for (IRIntegerValue i = 0; i < count->getValue(); i++)
{
auto tupleElement = builder.emitTargetTupleGetElement(
elementType,
val,
builder.getIntValue(builder.getIntType(), i));
auto convertedElement = makeValueFromTargetTuple(builder, elementType, tupleElement);
if (!convertedElement)
return nullptr;
resultElements.add(convertedElement);
}
return builder.emitMakeVector(
type,
(UInt)resultElements.getCount(),
resultElements.getBuffer());
}
else if (auto arrayType = as<IRArrayType>(type))
{
auto arraySize = as<IRIntLit>(arrayType->getElementCount());
if (!arraySize)
{
return nullptr;
}
List<IRInst*> resultElements;
auto elementType = arrayType->getElementType();
auto tupleElementType = translateToTupleType(builder, elementType);
for (IRIntegerValue i = 0; i < arraySize->getValue(); i++)
{
auto tupleElement = builder.emitTargetTupleGetElement(
tupleElementType,
val,
builder.getIntValue(builder.getIntType(), i));
// Make a name hint: <valname>_<i>
if (auto nameHint = val->findDecoration<IRNameHintDecoration>())
{
StringBuilder newName;
newName << nameHint->getName() << "_" << i;
builder.addNameHintDecoration(tupleElement, newName.getUnownedSlice());
}
auto convertedElement = makeValueFromTargetTuple(builder, elementType, tupleElement);
if (!convertedElement)
return nullptr;
resultElements.add(convertedElement);
}
return builder.emitMakeArray(
type,
(UInt)resultElements.getCount(),
resultElements.getBuffer());
}
else if (auto structType = as<IRStructType>(type))
{
List<IRInst*> resultElements;
IRIntegerValue i = 0;
for (auto field : structType->getFields())
{
auto tupleElement = builder.emitTargetTupleGetElement(
translateToTupleType(builder, field->getFieldType()),
val,
builder.getIntValue(builder.getIntType(), i));
// Make a name hint: <valname>_<fieldname>
if (auto nameHint = val->findDecoration<IRNameHintDecoration>())
{
if (auto fieldHint = field->getKey()->findDecoration<IRNameHintDecoration>())
{
StringBuilder newName;
newName << nameHint->getName() << "_" << fieldHint->getName();
builder.addNameHintDecoration(tupleElement, newName.getUnownedSlice());
}
}
auto convertedElement =
makeValueFromTargetTuple(builder, field->getFieldType(), tupleElement);
if (!convertedElement)
return nullptr;
resultElements.add(convertedElement);
i++;
}
return builder.emitMakeStruct(
type,
(UInt)resultElements.getCount(),
resultElements.getBuffer());
}
else if (as<IRTargetTupleType>(type))
{
return val;
}
else
{
return nullptr;
}
}
static void generateCppBindingForFunc(IRFunc* func, DiagnosticSink* sink)
{
IRBuilder builder(func);
builder.setInsertBefore(func);
auto hostReturnType = translateToTupleType(builder, func->getResultType());
if (!hostReturnType)
{
sink->diagnose(
func->sourceLoc,
Diagnostics::invalidTorchKernelReturnType,
func->getResultType());
return;
}
List<IRType*> hostParamTypes;
auto funcType = as<IRFuncType>(func->getDataType());
for (UInt i = 0; i < funcType->getParamCount(); i++)
{
hostParamTypes.add(translateToTupleType(builder, funcType->getParamType(i)));
}
auto bindingFuncType = builder.getFuncType(hostParamTypes, hostReturnType);
func->setFullType(bindingFuncType);
builder.setInsertBefore(func->getFirstBlock()->getFirstOrdinaryInst());
List<IRInst*> instsToRemove;
List<IRInst*> oldParams;
for (auto param : func->getFirstBlock()->getParams())
{
oldParams.add(param);
}
List<IRInst*> newParams;
for (auto param : oldParams)
{
auto paramType = param->getFullType();
auto newParamType = translateToTupleType(builder, paramType);
if (!newParamType)
{
sink->diagnose(param->sourceLoc, Diagnostics::invalidTorchKernelParamType, paramType);
return;
}
auto newParam = builder.emitParam(newParamType);
param->transferDecorationsTo(newParam);
newParams.add(newParam);
}
// Convert all new parameters from tuples to their original types.
for (Index i = 0; i < newParams.getCount(); i++)
{
auto oldParam = oldParams[i];
auto newParam = newParams[i];
auto convertedParam = makeValueFromTargetTuple(builder, oldParam->getFullType(), newParam);
if (!convertedParam)
{
return;
}
oldParam->replaceUsesWith(convertedParam);
oldParam->removeAndDeallocate();
}
for (auto block : func->getBlocks())
{
for (auto inst : block->getChildren())
{
if (auto kernelDispatch = as<IRDispatchKernel>(inst))
{
builder.setInsertBefore(kernelDispatch);
List<IRInst*> kernelArgs;
auto kernelArgCount = kernelDispatch->getArgCount();
auto argArrayType = builder.getArrayType(
builder.getPtrType(builder.getVoidType()),
builder.getIntValue(builder.getIntType(), kernelArgCount));
auto argArrayVar = builder.emitVar(argArrayType);
for (UInt i = 0; i < kernelArgCount; i++)
{
auto arg = kernelDispatch->getArg(i);
auto argVar = builder.emitVar(arg->getFullType());
builder.emitStore(argVar, arg);
auto addr = builder.emitElementAddress(
argArrayVar,
builder.getIntValue(builder.getIntType(), i));
builder.emitStore(addr, argVar);
}
auto argArrayPtr = builder.emitElementAddress(
argArrayVar,
builder.getIntValue(builder.getIntType(), 0));
builder.emitCudaKernelLaunch(
kernelDispatch->getBaseFn(),
kernelDispatch->getDispatchSize(),
kernelDispatch->getThreadGroupSize(),
argArrayPtr,
builder.emitGetTorchCudaStream());
instsToRemove.add(inst);
}
else if (auto getView = as<IRTorchTensorGetView>(inst))
{
builder.setInsertBefore(getView);
auto makeView =
builder.emitMakeTensorView(getView->getFullType(), inst->getOperand(0));
getView->replaceUsesWith(makeView);
instsToRemove.add(getView);
}
else if (auto ret = as<IRReturn>(inst))
{
builder.setInsertBefore(ret);
auto retVal = makeTargetTuple(builder, ret->getVal());
ret->setOperand(0, retVal);
}
}
}
for (auto inst : instsToRemove)
inst->removeAndDeallocate();
}
IRType* translateToHostType(
IRBuilder* builder,
IRType* type,
IRInst* func,
DiagnosticSink* sink = nullptr)
{
if (as<IRBasicType>(type) || as<IRVectorType>(type) || as<IRMatrixType>(type))
return type;
switch (type->getOp())
{
case kIROp_TensorViewType:
return builder->getTorchTensorType(as<IRTensorViewType>(type)->getElementType());
case kIROp_StructType:
{
// Create a new struct type with translated fields.
List<IRType*> fieldTypes;
List<IRNameHintDecoration*> fieldNames;
for (auto field : as<IRStructType>(type)->getFields())
{
fieldTypes.add(translateToHostType(builder, field->getFieldType(), func, sink));
fieldNames.add(field->getKey()->findDecoration<IRNameHintDecoration>());
}
auto hostStructType = builder->createStructType();
// Add fields to the struct.
for (UInt i = 0; i < (UInt)fieldTypes.getCount(); i++)
{
auto structKey = builder->createStructKey();
if (fieldNames[i])
builder->addNameHintDecoration(structKey, fieldNames[i]->getName());
builder->createStructField(hostStructType, structKey, fieldTypes[i]);
}
return hostStructType;
}
case kIROp_ArrayType:
{
auto elementType =
translateToHostType(builder, as<IRArrayType>(type)->getElementType(), func, sink);
if (!elementType)
return nullptr;
return builder->getArrayType(elementType, as<IRArrayType>(type)->getElementCount());
}
default:
break;
}
if (sink)
sink->diagnose(type->sourceLoc, Diagnostics::unableToAutoMapCUDATypeToHostType, type, func);
return nullptr;
}
// Propagates name hints through field extracts.
IRInst* propagateNameHint(IRBuilder* builder, IRFieldExtract* inst)
{
// If the field has a name hint, propagate it to the inst by appending the field name to the
// inst name (which must be fetched from the inst's name hint decoration).
//
// This is useful for propagating the name hint from a struct field to the inst that extracts
// the field.
if (auto nameHint = inst->getField()->findDecoration<IRNameHintDecoration>())
{
if (auto instNameHint = inst->getBase()->findDecoration<IRNameHintDecoration>())
{
StringBuilder newName;
newName << instNameHint->getName() << "_" << nameHint->getName();
builder->addNameHintDecoration(inst, newName.getUnownedSlice());
}
}
return inst;
}
// Propagates name hints through array indexing
IRInst* propagateNameHint(IRBuilder* builder, IRGetElement* inst)
{
// If the index is a constant, we can propagate the name hint from the inst to the index.
if (auto intLit = as<IRIntLit>(inst->getIndex()))
{
if (auto nameHint = inst->getBase()->findDecoration<IRNameHintDecoration>())
{
StringBuilder newName;
newName << nameHint->getName() << "_" << intLit->getValue();
builder->addNameHintDecoration(inst, newName.getUnownedSlice());
}
}
return inst;
}
IRInst* castHostToCUDAType(IRBuilder* builder, IRType* hostType, IRType* cudaType, IRInst* inst)
{
if (hostType == cudaType)
return inst;
if (as<IRBasicType>(hostType) && as<IRBasicType>(cudaType))
return inst;
switch (cudaType->getOp())
{
case kIROp_TensorViewType:
return builder->emitMakeTensorView(cudaType, inst);
case kIROp_StructType:
{
auto cudaStructType = cast<IRStructType>(cudaType);
auto hostStructType = cast<IRStructType>(hostType);
List<IRStructField*> cudaFields;
for (auto field : cudaStructType->getFields())
cudaFields.add(field);
List<IRStructField*> hostFields;
for (auto field : hostStructType->getFields())
hostFields.add(field);
List<IRInst*> resultFields;
for (auto ii = 0; ii < cudaFields.getCount(); ii++)
{
auto cudaField = cudaFields[ii];
auto hostField = hostFields[ii];
auto cudaFieldType = cudaField->getFieldType();
auto hostFieldType = hostField->getFieldType();
auto castedField = castHostToCUDAType(
builder,
hostFieldType,
cudaFieldType,
propagateNameHint(
builder,
cast<IRFieldExtract>(
builder->emitFieldExtract(hostFieldType, inst, hostField->getKey()))));
SLANG_RELEASE_ASSERT(castedField);
resultFields.add(castedField);
}
return builder->emitMakeStruct(
cudaType,
(UInt)resultFields.getCount(),
resultFields.getBuffer());
}
case kIROp_ArrayType:
{
auto cudaArrayType = cast<IRArrayType>(cudaType);
auto hostArrayType = cast<IRArrayType>(hostType);
List<IRInst*> resultElements;
for (UInt i = 0; i < (UInt)cast<IRIntLit>(cudaArrayType->getElementCount())->getValue();
i++)
{
auto cudaElementType = cudaArrayType->getElementType();
auto hostElementType = hostArrayType->getElementType();
auto castedElement = castHostToCUDAType(
builder,
hostElementType,
cudaElementType,
propagateNameHint(
builder,
cast<IRGetElement>(builder->emitElementExtract(
inst,
builder->getIntValue(builder->getIntType(), i)))));
SLANG_RELEASE_ASSERT(castedElement);
resultElements.add(castedElement);
}
return builder->emitMakeArray(
cudaType,
(UInt)resultElements.getCount(),
resultElements.getBuffer());
}
default:
break;
}
// If translateToHostType worked correctly, there should be no unhandled cases here.
// However, we won't diagnose here since its already diagnosed in translateToHostType()
return nullptr;
}
void generateReflectionFunc(IRBuilder* builder, IRFunc* kernelFunc, IRFunc* hostFunc)
{
// Given a func with torch binding, we'll generate a reflection function that returns
// a tuple where the first element is another tuple of parameter names, the second
// element is a string containing the name of the fwd-diff function, and the third
// element is a string containing the name of the bwd-diff function.
//
// Create a new function.
auto reflectionFunc = builder->createFunc();
builder->setInsertInto(reflectionFunc);
builder->emitBlock();
// Go through func & generate a tuple of parameter names.
List<IRInst*> paramNames;
List<IRInst*> paramTypeNames;
UIndex paramCount = 0;
for (auto param : hostFunc->getFirstBlock()->getParams())
{
if (auto nameHint = param->findDecoration<IRNameHintDecoration>())
{
paramNames.add(
builder->emitGetNativeString(builder->getStringValue(nameHint->getName())));
}
else
{
StringBuilder argNameBuilder;
argNameBuilder << "param";
argNameBuilder << paramCount;
paramNames.add(builder->emitGetNativeString(
builder->getStringValue(argNameBuilder.getUnownedSlice())));
}
paramCount++;
}
for (auto param : kernelFunc->getParams())
{
// Check for py-export decoration.
if (auto pyExportHint = param->getDataType()->findDecoration<IRPyExportDecoration>())
{
paramTypeNames.add(builder->emitGetNativeString(
builder->getStringValue(pyExportHint->getExportName())));
}
else
{
paramTypeNames.add(
builder->emitGetNativeString(builder->getStringValue(UnownedStringSlice(""))));
}
}
// Create a target-tuple-type for the names
auto paramNamesTupleType = builder->getTargetTupleType(
(UInt)paramNames.getCount(),
List<IRType*>()
.makeRepeated(builder->getNativeStringType(), paramNames.getCount())
.getBuffer());
auto paramNamesTuple = builder->emitMakeTargetTuple(
paramNamesTupleType,
paramNames.getCount(),
paramNames.getBuffer());
// Create a target-tuple-type for the type names
auto paramTypeNamesTupleType = builder->getTargetTupleType(
(UInt)paramTypeNames.getCount(),
List<IRType*>()
.makeRepeated(builder->getNativeStringType(), paramTypeNames.getCount())
.getBuffer());
auto paramTypeNamesTuple = builder->emitMakeTargetTuple(
paramTypeNamesTupleType,
paramTypeNames.getCount(),
paramTypeNames.getBuffer());
// Find the fwd-diff function name (blank string indicates no fwd-diff)
IRInst* fwdDiffName = builder->getStringValue(UnownedStringSlice(""));
if (auto fwdDiffHint = kernelFunc->findDecoration<IRCudaKernelForwardDerivativeDecoration>())
{
auto fwdDiffFunc = fwdDiffHint->getForwardDerivativeFunc();
if (auto fwdDiffFuncExternHint = fwdDiffFunc->findDecoration<IRExternCppDecoration>())
{
fwdDiffName = builder->emitGetNativeString(
builder->getStringValue(fwdDiffFuncExternHint->getName()));
}
}
// Find the bwd-diff function name (blank string indicates no bwd-diff)
IRInst* bwdDiffName = builder->getStringValue(UnownedStringSlice(""));
if (auto bwdDiffHint = kernelFunc->findDecoration<IRCudaKernelBackwardDerivativeDecoration>())
{
auto bwdDiffFunc = bwdDiffHint->getBackwardDerivativeFunc();
if (auto bwdDiffFuncExternHint = bwdDiffFunc->findDecoration<IRExternCppDecoration>())
{
bwdDiffName = builder->emitGetNativeString(
builder->getStringValue(bwdDiffFuncExternHint->getName()));
}
}
auto stringType = builder->getNativeStringType();
auto returnTupleType = builder->getTargetTupleType(
4,
List<IRType*>(paramNamesTupleType, paramTypeNamesTupleType, stringType, stringType)
.getBuffer());
// Create a target-tuple-type for the names
auto returnTupleArgs =
List<IRInst*>(paramNamesTuple, paramTypeNamesTuple, fwdDiffName, bwdDiffName);
auto returnTuple = builder->emitMakeTargetTuple(
returnTupleType,
returnTupleArgs.getCount(),
returnTupleArgs.getBuffer());
builder->emitReturn(returnTuple);
// Set function type.
auto funcType = builder->getFuncType(List<IRType*>(), returnTupleType);
reflectionFunc->setFullType(funcType);
// Set function name.
StringBuilder reflFuncExportName;
auto hostFuncExportName = hostFunc->findDecoration<IRExternCppDecoration>()->getName();
reflFuncExportName << "__funcinfo__" << hostFuncExportName;
builder->addExternCppDecoration(reflectionFunc, reflFuncExportName.getUnownedSlice());
builder->addTorchEntryPointDecoration(reflectionFunc, reflFuncExportName.getUnownedSlice());
builder->addKeepAliveDecoration(reflectionFunc);
}
IRInst* generateHostParamForCUDAParam(
IRBuilder* builder,
IRParam* param,
DiagnosticSink* sink,
IRType** outType = nullptr)
{
auto type = translateToHostType(builder, param->getDataType(), getParentFunc(param), sink);
if (outType)
*outType = type;
if (!type || sink->getErrorCount() > 0)
{
return nullptr;
}
auto hostParam = builder->emitParam(type);
// Add a namehint to the param
if (auto nameHint = param->findDecoration<IRNameHintDecoration>())
{
builder->addNameHintDecoration(hostParam, nameHint->getName());
}
// Then cast the param to the appropriate type.
if (auto castedParam = castHostToCUDAType(builder, type, param->getDataType(), hostParam))
return castedParam;
return nullptr;
}
void markTypeForPyExport(IRType* type, DiagnosticSink* sink)
{
// If it's a basic type, we're done.
if (as<IRBasicType>(type) || as<IRVoidType>(type))
return;
// If it's a struct type, mark for py-export.
if (auto structType = as<IRStructType>(type))
{
IRBuilder builder(structType->getModule());
// If it already has a py-export decoration, we're done.
if (!structType->findDecoration<IRPyExportDecoration>())
{
// Look for a name hint.
UnownedStringSlice nameHint;
if (auto nameHintDecoration = structType->findDecoration<IRNameHintDecoration>())
nameHint = nameHintDecoration->getName();
else
{
// If there's no name hint, we can't export this type.
SLANG_UNEXPECTED("struct marked for export has no name");
}
builder.addPyExportDecoration(structType, nameHint);
}
for (auto field : structType->getFields())
{
markTypeForPyExport(field->getFieldType(), sink);
}
return;
}
else if (auto arrayType = as<IRArrayType>(type))
{
IRBuilder builder(arrayType->getModule());
if (!arrayType->findDecoration<IRPyExportDecoration>())
builder.addPyExportDecoration(arrayType, UnownedStringSlice("Array"));
markTypeForPyExport(arrayType->getElementType(), sink);
return;
}
}
String tryGetExportTypeName(IRBuilder* builder, IRType* type)
{
if (as<IRStructType>(type))
{
if (auto pyExportDecoration = type->findDecoration<IRPyExportDecoration>())
return String(pyExportDecoration->getExportName());
else
return String("");
}
else if (auto arrayType = as<IRArrayType>(type))
{
StringBuilder nameBuilder;
nameBuilder << "Array_";
nameBuilder << tryGetExportTypeName(builder, arrayType->getElementType());
nameBuilder << "_";
nameBuilder << cast<IRIntLit>(arrayType->getElementCount())->getValue();
return nameBuilder.produceString();
}
else
return String();
}
void generateReflectionForType(IRType* type, DiagnosticSink* sink)
{
SLANG_UNUSED(sink);
// Emit a function that returns a py::list.
// The list will contain the names of all the fields of the type.
//
if (!type->findDecoration<IRPyExportDecoration>())
return;
IRBuilder builder(type->getModule());
auto reflFunc = builder.createFunc();
builder.setInsertInto(reflFunc);
builder.emitBlock();
List<IRInst*> fieldNames;
List<IRInst*> fieldTypeNames;
switch (type->getOp())
{
case kIROp_StructType:
{
for (auto field : as<IRStructType>(type)->getFields())
{
auto structKey = field->getKey();
// Look for a name hint.
if (auto nameHintDecoration = structKey->findDecoration<IRNameHintDecoration>())
fieldNames.add(builder.emitGetNativeString(
builder.getStringValue(nameHintDecoration->getName())));
else
fieldNames.add(builder.emitGetNativeString(
builder.getStringValue(UnownedStringSlice(""))));
auto fieldType = field->getFieldType();
auto exportName = tryGetExportTypeName(&builder, fieldType);
if (exportName.getLength() > 0)
fieldTypeNames.add(builder.emitGetNativeString(
builder.getStringValue(exportName.getUnownedSlice())));
else
fieldTypeNames.add(builder.emitGetNativeString(
builder.getStringValue(UnownedStringSlice(""))));
}
break;
}
case kIROp_ArrayType:
{
auto elementType = as<IRArrayType>(type)->getElementType();
fieldNames.add(
builder.emitGetNativeString(builder.getStringValue(UnownedStringSlice("type"))));
fieldTypeNames.add(builder.emitGetNativeString(builder.getStringValue(
tryGetExportTypeName(&builder, elementType).getUnownedSlice())));
auto elementCount = as<IRIntLit>(as<IRArrayType>(type)->getElementCount());
fieldNames.add(
builder.emitGetNativeString(builder.getStringValue(UnownedStringSlice("size"))));
StringBuilder elementCountStr;
elementCountStr << elementCount->getValue();
fieldTypeNames.add(builder.emitGetNativeString(
builder.getStringValue(elementCountStr.getUnownedSlice())));
break;
}
default:
break;
}
auto _nameListTupleType = builder.getTargetTupleType(
(UInt)fieldNames.getCount(),
List<IRType*>()
.makeRepeated(builder.getNativeStringType(), fieldNames.getCount())
.getBuffer());
auto nameListTuple = builder.emitMakeTargetTuple(
_nameListTupleType,
(UInt)fieldNames.getCount(),
fieldNames.getBuffer());
auto _typeNameListTupleType = builder.getTargetTupleType(
(UInt)fieldTypeNames.getCount(),
List<IRType*>()
.makeRepeated(builder.getNativeStringType(), fieldTypeNames.getCount())
.getBuffer());
auto typeNameListTuple = builder.emitMakeTargetTuple(
_typeNameListTupleType,
(UInt)fieldTypeNames.getCount(),
fieldTypeNames.getBuffer());
auto _nameAndTypeTupleType = builder.getTargetTupleType(
2,
List<IRType*>(_nameListTupleType, _typeNameListTupleType).getBuffer());
auto nameAndTypeTuple = builder.emitMakeTargetTuple(
_nameAndTypeTupleType,
2,
List<IRInst*>(nameListTuple, typeNameListTuple).getBuffer());
builder.emitReturn(nameAndTypeTuple);
// Set function type.
auto funcType = builder.getFuncType(List<IRType*>(), _nameAndTypeTupleType);
reflFunc->setFullType(funcType);
// Set function name.
StringBuilder reflFuncExportName;
reflFuncExportName << "__typeinfo__" << tryGetExportTypeName(&builder, type).getUnownedSlice();
builder.addTorchEntryPointDecoration(reflFunc, reflFuncExportName.getUnownedSlice());
builder.addExternCppDecoration(reflFunc, reflFuncExportName.getUnownedSlice());
builder.addKeepAliveDecoration(reflFunc);
}
IRFunc* generateCUDAWrapperForFunc(IRFunc* func, DiagnosticSink* sink)
{
// Check that the function has an auto-bind decoration
if (!func->findDecoration<IRAutoPyBindCudaDecoration>())
return nullptr;
// We will create a CudaHost function that will call func.
// But before that, we need to determine the type of CudaHost.
//
// To determine the type, first we will append two uint3 parameters to the function.
// with the names "__blockSize" and "__gridSize", these will serve as input block and
// grid size parameters for the launch.
//
// Then, we will go over the parameters of func, and find a host-mapping for each type
// by calling mapTypeToCudaHostType(IRType*), which turns structs into tuples, and
// IRTensorViewType to IRTorchTensorType.
//
// Finally, we will create a CudaHost function and transfer the name of func over to
// the generated method.
//
// The function body will first perform any conversion logic needed to convert the
// parameters from the CudaHost types to the types of func, and then use dispatch_kernel
// to dispatch func with the given block and grid size.
//
// Create new function.
IRBuilder builder(func->getModule());
auto hostFunc = builder.createFunc();
builder.setInsertInto(hostFunc);
builder.emitBlock();
List<IRType*> hostParamTypes;
// Add the two uint3 parameters
auto uint3Type = builder.getVectorType(builder.getUIntType(), 3);
auto blockSizeParam = builder.emitParam(uint3Type);
hostParamTypes.add(uint3Type);
builder.addNameHintDecoration(blockSizeParam, UnownedStringSlice("__blockSize"));
auto gridSizeParam = builder.emitParam(uint3Type);
hostParamTypes.add(uint3Type);
builder.addNameHintDecoration(gridSizeParam, UnownedStringSlice("__gridSize"));
List<IRInst*> mappedParams;
for (auto param : func->getFirstBlock()->getParams())
{
IRType* hostParamType;
mappedParams.add(generateHostParamForCUDAParam(&builder, param, sink, &hostParamType));
hostParamTypes.add(hostParamType);
markTypeForPyExport(param->getDataType(), sink); // Should we be marking the host type?
}
// Dispatch the original function.
builder.emitDispatchKernelInst(
builder.getVoidType(),
func,
blockSizeParam,
gridSizeParam,
mappedParams.getCount(),
mappedParams.getBuffer());
builder.emitReturn();
IRFuncType* hostFuncType = builder.getFuncType(hostParamTypes, builder.getVoidType());
hostFunc->setFullType(hostFuncType);
// Add a torch entry point decoration to the host function to mark
// for further processing.
//
if (auto pybindCudaHint = func->findDecoration<IRAutoPyBindCudaDecoration>())
{
// Mark for further processing of torch-specific insts.
builder.addTorchEntryPointDecoration(hostFunc, pybindCudaHint->getFunctionName());
// Mark for host-side emit logic.
builder.addCudaHostDecoration(hostFunc);
// Keep alive. This method will be accessed externally.
builder.addKeepAliveDecoration(hostFunc);
}
if (auto externCppHint = func->findDecoration<IRExternCppDecoration>())
{
// Transfer to the host function.
builder.addExternCppDecoration(hostFunc, externCppHint->getName());
}
if (func->findDecoration<IRAutoPyBindExportInfoDecoration>())
generateReflectionFunc(&builder, func, hostFunc);
return hostFunc;
}
void lowerBuiltinTypesForKernelEntryPoints(IRModule* module, DiagnosticSink*)
{
List<IRFunc*> cudaKernels;
for (auto globalInst : module->getGlobalInsts())
{
if (auto func = as<IRFunc>(globalInst))
{
if (func->findDecoration<IRCudaKernelDecoration>())
{
cudaKernels.add(func);
}
}
}
BuiltinTypeLoweringEnv typeLoweringEnv;
IRBuilder builder(module);
for (auto func : cudaKernels)
{
// Go through parameters and replace any built-in types with their equivalent.
List<IRParam*> params;
for (auto param : func->getFirstBlock()->getParams())
{
params.add(param);
}
bool changed = false;
List<LoweredBuiltinTypeInfo> loweredParamTypes;
for (auto param : params)
{
LoweredBuiltinTypeInfo info =
lowerType(&typeLoweringEnv, &builder, param->getDataType());
loweredParamTypes.add(info);
if (info.convertLoweredToOriginal != nullptr)
{
// Replace parameter with the lowered type.
auto originalType = param->getDataType();
param->setFullType(info.loweredType);
// Call the conversion function to convert the lowered parameter to the original
// parameter.
List<IRInst*> args;
args.add(param);
setInsertAfterOrdinaryInst(&builder, param);
auto convertedParam =
builder.emitCallInst(originalType, info.convertLoweredToOriginal, args);
// Replace all uses of the lowered parameter with the converted parameter, except
// for the call instruction.
for (auto use = param->firstUse; use;)
{
auto nextUse = use->nextUse;
if (use->getUser() == convertedParam)
{
use = nextUse;
continue;
}
use->set(convertedParam);
use = nextUse;
}
changed = true;
}
}
if (!changed)
continue;
fixUpFuncType(func);
// Go through any calls to this function and insert a call to converOriginalToLowered before
// the call.
for (auto use = func->firstUse; use;)
{
auto nextUse = use->nextUse;
if (as<IRCall>(use->getUser()) || as<IRDispatchKernel>(use->getUser()))
{
auto user = use->getUser();
IROperandList<IRInst> argsList;
if (auto callInst = as<IRCall>(user))
argsList = callInst->getArgsList();
else if (auto dispatchInst = as<IRDispatchKernel>(user))
argsList = dispatchInst->getArgsList();
// Insert a call to convertOriginalToLowered before the call.
List<IRInst*> convertedArgs;
IRBuilder callBuilder(func->getModule());
callBuilder.setInsertBefore(user);
for (auto arg : argsList)
{
if (loweredParamTypes[convertedArgs.getCount()].convertOriginalToLowered !=
nullptr)
{
auto convertedArg = callBuilder.emitCallInst(
loweredParamTypes[convertedArgs.getCount()].loweredType,
loweredParamTypes[convertedArgs.getCount()].convertOriginalToLowered,
List<IRInst*>(arg));
convertedArgs.add(convertedArg);
}
else
{
convertedArgs.add(arg);
}
}
// Rebuild the call/dispatch inst.
IRInst* newCall = nullptr;
if (as<IRCall>(user))
newCall = callBuilder.emitCallInst(user->getFullType(), func, convertedArgs);
else if (auto dispatchInst = as<IRDispatchKernel>(user))
newCall = callBuilder.emitDispatchKernelInst(
user->getFullType(),
func,
dispatchInst->getThreadGroupSize(),
dispatchInst->getDispatchSize(),
convertedArgs.getCount(),
convertedArgs.getBuffer());
// Replace the call instruction.
user->replaceUsesWith(newCall);
// Remove the call instruction.
user->removeAndDeallocate();
}
use = nextUse;
}
}
}
void generateHostFunctionsForAutoBindCuda(IRModule* module, DiagnosticSink* sink)
{
List<IRFunc*> autoBindRequests;
for (auto globalInst : module->getGlobalInsts())
{
if (auto func = as<IRFunc>(globalInst))
{
if (func->findDecoration<IRAutoPyBindCudaDecoration>())
{
autoBindRequests.add(func);
}
}
}
for (auto func : autoBindRequests)
{
generateCUDAWrapperForFunc(func, sink);
}
}
void generatePyTorchCppBinding(IRModule* module, DiagnosticSink* sink)
{
List<IRFunc*> workList;
List<IRFunc*> cudaKernels;
List<IRType*> typesToExport;
for (auto globalInst : module->getGlobalInsts())
{
if (auto func = as<IRFunc>(globalInst))
{
if (func->findDecoration<IRTorchEntryPointDecoration>())
{
workList.add(func);
}
else if (func->findDecoration<IRCudaKernelDecoration>())
{
cudaKernels.add(func);
}
else
{
// Remove all other export decorations if this is not a cuda host func.
if (auto decor = func->findDecoration<IRPublicDecoration>())
decor->removeAndDeallocate();
if (auto decor = func->findDecoration<IRHLSLExportDecoration>())
decor->removeAndDeallocate();
if (auto decor = func->findDecoration<IRKeepAliveDecoration>())
decor->removeAndDeallocate();
if (auto decor = func->findDecoration<IRDllExportDecoration>())
decor->removeAndDeallocate();
}
}
}
for (auto func : workList)
generateCppBindingForFunc(func, sink);
for (auto func : cudaKernels)
{
for (auto block = func->getFirstBlock(); block;)
{
auto nextBlock = block->getNextBlock();
block->removeAndDeallocate();
block = nextBlock;
}
}
for (auto globalInst : module->getGlobalInsts())
{
if (auto type = as<IRType>(globalInst))
{
if (type->findDecoration<IRPyExportDecoration>())
{
typesToExport.add(type);
}
}
}
for (auto type : typesToExport)
generateReflectionForType(type, sink);
}
// Remove all [TorchEntryPoint] functions when emitting CUDA source.
void removeTorchKernels(IRModule* module)
{
List<IRInst*> toRemove;
for (auto globalInst : module->getGlobalInsts())
{
if (!as<IRFunc>(globalInst))
continue;
if (globalInst->findDecoration<IRTorchEntryPointDecoration>())
toRemove.add(globalInst);
}
for (auto inst : toRemove)
inst->removeAndDeallocate();
}
void handleAutoBindNames(IRModule* module)
{
// We need to rewrite extern-cpp names for functions that have an auto-bind decoration.
// since the name needs to be used for the host function.
//
for (auto globalInst : module->getGlobalInsts())
{
if (globalInst->findDecoration<IRAutoPyBindCudaDecoration>())
{
// Find an extern decoration on the original function, and append a prefix to the name.
if (auto externCppHint = globalInst->findDecoration<IRExternCppDecoration>())
{
IRBuilder builder(module);
// Change the name of the original function.
StringBuilder nameBuilder;
nameBuilder << "__kernel__" << externCppHint->getName();
externCppHint->removeAndDeallocate();
builder.addExternCppDecoration(globalInst, nameBuilder.getUnownedSlice());
}
}
}
}
void removeTorchAndCUDAEntryPoints(IRModule* module)
{
// Go through global insts, find cuda & torch related entry points and remove the keep-alive
// decoration.
IRBuilder builder(module);
for (auto globalInst : module->getGlobalInsts())
{
if (auto func = as<IRFunc>(globalInst))
{
if (func->findDecoration<IRAutoPyBindCudaDecoration>() ||
func->findDecoration<IRTorchEntryPointDecoration>() ||
func->findDecoration<IRCudaKernelDecoration>())
{
if (auto keepAlive = func->findDecoration<IRKeepAliveDecoration>())
keepAlive->removeAndDeallocate();
if (auto hlslExport = func->findDecoration<IRHLSLExportDecoration>())
hlslExport->removeAndDeallocate();
}
}
}
}
void generateDerivativeWrappers(IRModule* module, DiagnosticSink* sink)
{
SLANG_UNUSED(sink);
for (auto globalInst : module->getGlobalInsts())
{
if (!as<IRFunc>(globalInst))
continue;
// Look for methods marked with auto-bind and are differentiable.
if (globalInst->findDecoration<IRAutoPyBindCudaDecoration>())
{
if (globalInst->findDecoration<IRForwardDifferentiableDecoration>() ||
globalInst->findDecoration<IRBackwardDifferentiableDecoration>())
{
// We'll generate a wrapper for this method that calls fwd_diff(fn)
// but an important thing to note is that we won't actually employ the usual
// differentiable typing rules. We'll assume none of the parameters are
// differentiable & throw a warning if some are. This is because, for the
// auto-binding scenario, we expect to only see tensor types, and their
// differentiation is handled using tensor _pair_ types which handle the
// differentiable loads/stores through custom derivatives
//
// For now, the user is expected to explicitly use the tensor pair types, so we will
// simply copy over the original function's signature. In the future, when we update
// the type system to be able to specify the corresponding pair type, we can update
// this logic.
//
// Create a new wrapper function.
IRBuilder builder(module);
auto func = cast<IRFunc>(globalInst);
auto wrapperFunc = builder.createFunc();
builder.setInsertInto(wrapperFunc);
builder.emitBlock();
// Clone the parameter list.
List<IRInst*> params;
for (auto param : func->getFirstBlock()->getParams())
{
auto newParam = builder.emitParam(param->getFullType());
// Copy over the name hint.
if (auto nameHint = param->findDecoration<IRNameHintDecoration>())
builder.addNameHintDecoration(newParam, nameHint->getName());
params.add(newParam);
}
wrapperFunc->setFullType(func->getFullType());
auto fwdDiffFunc = builder.emitForwardDifferentiateInst(func->getFullType(), func);
auto fwdDiffCall = builder.emitCallInst(
func->getResultType(),
fwdDiffFunc,
params.getCount(),
params.getBuffer());
builder.emitReturn(fwdDiffCall);
// If the original func is a CUDA kernel, mark the wrapper as a CUDA kernel as well.
if (func->findDecoration<IRCudaKernelDecoration>())
{
builder.addCudaKernelDecoration(wrapperFunc);
builder.addExternCDecoration(wrapperFunc);
}
// Add an auto-pybind-cuda decoration to the wrapper function to further generate
// the host-side binding for the derivative kernel.
//
{
auto autoPyBindCudaHint = func->findDecoration<IRAutoPyBindCudaDecoration>();
StringBuilder nameBuilder;
nameBuilder << autoPyBindCudaHint->getFunctionName() << "_fwd_diff";
builder.addAutoPyBindCudaDecoration(wrapperFunc, nameBuilder.getUnownedSlice());
}
// Build a name for the wrapper function: <original_name>_fwd_diff
if (auto externCppHint = func->findDecoration<IRExternCppDecoration>())
{
StringBuilder nameBuilder;
nameBuilder << externCppHint->getName() << "_fwd_diff";
builder.addExternCppDecoration(wrapperFunc, nameBuilder.getUnownedSlice());
}
builder.addKeepAliveDecoration(wrapperFunc);
builder.addCudaKernelForwardDerivativeDecoration(func, wrapperFunc);
}
if (globalInst->findDecoration<IRBackwardDifferentiableDecoration>())
{
// The reasoning for the reverse-mode is the same as the forward-mode version
// (see above)
//
// Create a new wrapper function.
IRBuilder builder(module);
auto func = cast<IRFunc>(globalInst);
auto wrapperFunc = builder.createFunc();
builder.setInsertInto(wrapperFunc);
builder.emitBlock();
// Clone the parameter list.
List<IRInst*> params;
for (auto param : func->getFirstBlock()->getParams())
{
auto newParam = builder.emitParam(param->getFullType());
// Copy over the name hint.
if (auto nameHint = param->findDecoration<IRNameHintDecoration>())
builder.addNameHintDecoration(newParam, nameHint->getName());
params.add(newParam);
}
wrapperFunc->setFullType(func->getFullType());
auto fwdDiffFunc = builder.emitBackwardDifferentiateInst(func->getFullType(), func);
auto fwdDiffCall = builder.emitCallInst(
func->getResultType(),
fwdDiffFunc,
params.getCount(),
params.getBuffer());
builder.emitReturn(fwdDiffCall);
// If the original func is a CUDA kernel, mark the wrapper as a CUDA kernel as well.
if (func->findDecoration<IRCudaKernelDecoration>())
{
builder.addCudaKernelDecoration(wrapperFunc);
builder.addExternCDecoration(wrapperFunc);
}
// Add an auto-pybind-cuda decoration to the wrapper function to further generate
// the host-side binding for the derivative kernel.
//
{
auto autoPyBindCudaHint = func->findDecoration<IRAutoPyBindCudaDecoration>();
StringBuilder nameBuilder;
nameBuilder << autoPyBindCudaHint->getFunctionName() << "_bwd_diff";
builder.addAutoPyBindCudaDecoration(wrapperFunc, nameBuilder.getUnownedSlice());
}
// Build a name for the wrapper function: <original_name>_bwd_diff
if (auto externCppHint = func->findDecoration<IRExternCppDecoration>())
{
StringBuilder nameBuilder;
nameBuilder << externCppHint->getName() << "_bwd_diff";
builder.addExternCppDecoration(wrapperFunc, nameBuilder.getUnownedSlice());
}
builder.addKeepAliveDecoration(wrapperFunc);
builder.addCudaKernelBackwardDerivativeDecoration(func, wrapperFunc);
}
}
}
}
} // namespace Slang
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