#include "triton/Dialect/Triton/IR/Dialect.h"
#include "triton/Dialect/TritonGPU/IR/Dialect.h"
#include "triton/Conversion/TritonToTritonGPU/TritonToTritonGPU.h"
#include "triton/Dialect/TritonGPU/Transforms/TritonGPUConversion.h"
#include "mlir/Transforms/DialectConversion.h"
#include "mlir/Dialect/Arithmetic/IR/Arithmetic.h"
#include "../PassDetail.h"

using namespace mlir;
using namespace mlir::triton;

namespace {

class ConvertArithmeticOp: public ConversionPattern {
public:
    ConvertArithmeticOp(TritonGPUTypeConverter &typeConverter, MLIRContext *context)
        : ConversionPattern(typeConverter, MatchAnyOpTypeTag(), /*benefit=*/1,
                            context) {}

    LogicalResult matchAndRewrite(Operation* op, ArrayRef<Value> operands,
                                  ConversionPatternRewriter& rewriter) const override {
        Dialect* dialect = op->getDialect();
        if(dialect->getTypeID() != mlir::TypeID::get<arith::ArithmeticDialect>()) 
            return failure();
        return success();
    }
};

void populateArithmeticPatternsAndLegality(
    TritonGPUTypeConverter& typeConverter, RewritePatternSet &patterns,
    TritonGPUConversionTarget &target){
  // --------------
  // Add legality and rewrite pattern rules for operations
  // from the Arithmetic dialect. The basic premise is that
  // arithmetic operations require both inputs to have the same
  // non-null encoding
  // --------------
  MLIRContext *context = patterns.getContext();
  // Legality rule
  target.addDynamicallyLegalDialect<arith::ArithmeticDialect>(
      // TODO: check above rule here
      [](Operation *op){
          return true;
      }
  );
  // Rewrite rule
  patterns.add<ConvertArithmeticOp>(typeConverter, context);
}

//
// Triton patterns
//
// TODO: Do we need to put them in anonymous namespace?
struct TritonMakeRangePattern : public OpConversionPattern<triton::MakeRangeOp> {
  using OpConversionPattern<triton::MakeRangeOp>::OpConversionPattern;

  LogicalResult matchAndRewrite(triton::MakeRangeOp op, OpAdaptor adaptor,
                                ConversionPatternRewriter &rewriter) const override {
    Type retType = getTypeConverter()->convertType(op.getType());

    rewriter.replaceOpWithNewOp<triton::MakeRangeOp>(
      op.getOperation(), retType, op.start(), op.end()
    );
    return success();
  }
};

struct TritonBroadcastPattern : public OpConversionPattern<triton::BroadcastOp> {
  using OpConversionPattern<triton::BroadcastOp>::OpConversionPattern;

  LogicalResult matchAndRewrite(triton::BroadcastOp op, OpAdaptor adaptor,
                                ConversionPatternRewriter &rewriter) const override {
    Type retType = getTypeConverter()->convertType(op.getType());
    rewriter.replaceOpWithNewOp<triton::BroadcastOp>(
      op.getOperation(), retType, op.src()
    );
    return success();
  }
};

struct TritonGEPPattern : public OpConversionPattern<triton::GEPOp> {
  using OpConversionPattern<triton::GEPOp>::OpConversionPattern;

  LogicalResult matchAndRewrite(triton::GEPOp op, OpAdaptor adaptor,
                                ConversionPatternRewriter &rewriter) const override {
    Type retType = getTypeConverter()->convertType(op.getType());
    rewriter.replaceOpWithNewOp<triton::GEPOp>(
      op.getOperation(), retType, op.ptr(), op.offset()
    );
    return success();
  }
};

struct TritonLoadPattern : public OpConversionPattern<triton::LoadOp> {
  using OpConversionPattern<triton::LoadOp>::OpConversionPattern;

  LogicalResult matchAndRewrite(triton::LoadOp op, OpAdaptor adaptor,
                                ConversionPatternRewriter &rewriter) const override {
    Type retType = getTypeConverter()->convertType(op.getType());
    rewriter.replaceOpWithNewOp<triton::LoadOp>(
      op.getOperation(), retType, 
      op.ptr(), op.mask(), op.other(), op.cache(), op.evict(), op.isVolatile()
    );
    return success();
  }
};

void populateTritonPatterns(
  TritonGPUTypeConverter& typeConverter, RewritePatternSet &patterns
) {
  MLIRContext *context = patterns.getContext();
  patterns.add<TritonMakeRangePattern,
               TritonBroadcastPattern,
               TritonGEPPattern,
               TritonLoadPattern
              >(typeConverter, context);
}


class ConvertTritonToTritonGPU :
    public ConvertTritonToTritonGPUBase<ConvertTritonToTritonGPU> {

public:
  void runOnOperation() override {
    MLIRContext *context = &getContext();
    ModuleOp mod = getOperation();
    // int numThreads = mod.getAttr();
    // type converter
    TritonGPUTypeConverter typeConverter(context, /*numThreads*/128);
    TritonGPUConversionTarget target(*context, typeConverter);
    // rewrite patterns
    RewritePatternSet patterns(context);
    // add rules
    populateArithmeticPatternsAndLegality(typeConverter, patterns, target);
    populateTritonPatterns(typeConverter, patterns);


    if(failed(applyPartialConversion(mod, target, 
                                      std::move(patterns))))
        return signalPassFailure();
  }
};

}

std::unique_ptr<OperationPass<ModuleOp>>
mlir::triton::createConvertTritonToTritonGPUPass() {
  return std::make_unique<::ConvertTritonToTritonGPU>();
}