//===- ExpandTanh.cpp - Code to perform expanding tanh op -----------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This file implements expansion of tanh op.
//
//===----------------------------------------------------------------------===//

#include "mlir/Dialect/Math/IR/Math.h"
#include "mlir/Dialect/Math/Transforms/Passes.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/IR/Builders.h"
#include "mlir/Transforms/DialectConversion.h"
using namespace mlir;

/// Expands tanh op into
///   1) 1-exp^{-2x} / 1+exp^{-2x}, if x => 0
///   2) exp^{2x}-1 / exp^{2x}+1  , if x < 0
static LogicalResult convertTanhOp(math::TanhOp op, PatternRewriter &rewriter) {
  auto floatType = op.operand().getType();
  Location loc = op.getLoc();
  auto floatOne = rewriter.getFloatAttr(floatType, 1.0);
  auto floatTwo = rewriter.getFloatAttr(floatType, 2.0);
  Value one = rewriter.create<ConstantOp>(loc, floatOne);
  Value two = rewriter.create<ConstantOp>(loc, floatTwo);
  Value doubledX = rewriter.create<MulFOp>(loc, op.operand(), two);

  // Case 1: tanh(x) = 1-exp^{-2x} / 1+exp^{-2x}
  Value negDoubledX = rewriter.create<NegFOp>(loc, doubledX);
  Value exp2x = rewriter.create<math::ExpOp>(loc, negDoubledX);
  Value dividend = rewriter.create<SubFOp>(loc, one, exp2x);
  Value divisor = rewriter.create<AddFOp>(loc, one, exp2x);
  Value positiveRes = rewriter.create<DivFOp>(loc, dividend, divisor);

  // Case 2: tanh(x) = exp^{2x}-1 / exp^{2x}+1
  exp2x = rewriter.create<math::ExpOp>(loc, doubledX);
  dividend = rewriter.create<SubFOp>(loc, exp2x, one);
  divisor = rewriter.create<AddFOp>(loc, exp2x, one);
  Value negativeRes = rewriter.create<DivFOp>(loc, dividend, divisor);

  // tanh(x) = x >= 0 ? positiveRes : negativeRes
  auto floatZero = rewriter.getFloatAttr(floatType, 0.0);
  Value zero = rewriter.create<ConstantOp>(loc, floatZero);
  Value cmpRes =
      rewriter.create<CmpFOp>(loc, CmpFPredicate::OGE, op.operand(), zero);
  rewriter.replaceOpWithNewOp<SelectOp>(op, cmpRes, positiveRes, negativeRes);
  return success();
}

void mlir::populateExpandTanhPattern(RewritePatternSet &patterns) {
  patterns.add(convertTanhOp);
}
