1f971e23f0
The Func has a large number of legacy dependencies carried over from the old Standard dialect, which was pervasive and contained a large number of varied operations. With the split of the standard dialect and its demise, a lot of lingering dead dependencies have survived to the Func dialect. This commit removes a large majority of then, greatly reducing the dependence surface area of the Func dialect.
59 lines
2.6 KiB
C++
59 lines
2.6 KiB
C++
//===- ExpandTanh.cpp - Code to perform expanding tanh op -----------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// This file implements expansion of tanh op.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Dialect/Arithmetic/IR/Arithmetic.h"
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#include "mlir/Dialect/Math/IR/Math.h"
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#include "mlir/Dialect/Math/Transforms/Passes.h"
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#include "mlir/IR/Builders.h"
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#include "mlir/Transforms/DialectConversion.h"
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using namespace mlir;
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/// Expands tanh op into
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/// 1) 1-exp^{-2x} / 1+exp^{-2x}, if x => 0
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/// 2) exp^{2x}-1 / exp^{2x}+1 , if x < 0
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static LogicalResult convertTanhOp(math::TanhOp op, PatternRewriter &rewriter) {
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auto floatType = op.getOperand().getType();
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Location loc = op.getLoc();
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auto floatOne = rewriter.getFloatAttr(floatType, 1.0);
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auto floatTwo = rewriter.getFloatAttr(floatType, 2.0);
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Value one = rewriter.create<arith::ConstantOp>(loc, floatOne);
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Value two = rewriter.create<arith::ConstantOp>(loc, floatTwo);
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Value doubledX = rewriter.create<arith::MulFOp>(loc, op.getOperand(), two);
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// Case 1: tanh(x) = 1-exp^{-2x} / 1+exp^{-2x}
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Value negDoubledX = rewriter.create<arith::NegFOp>(loc, doubledX);
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Value exp2x = rewriter.create<math::ExpOp>(loc, negDoubledX);
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Value dividend = rewriter.create<arith::SubFOp>(loc, one, exp2x);
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Value divisor = rewriter.create<arith::AddFOp>(loc, one, exp2x);
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Value positiveRes = rewriter.create<arith::DivFOp>(loc, dividend, divisor);
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// Case 2: tanh(x) = exp^{2x}-1 / exp^{2x}+1
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exp2x = rewriter.create<math::ExpOp>(loc, doubledX);
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dividend = rewriter.create<arith::SubFOp>(loc, exp2x, one);
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divisor = rewriter.create<arith::AddFOp>(loc, exp2x, one);
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Value negativeRes = rewriter.create<arith::DivFOp>(loc, dividend, divisor);
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// tanh(x) = x >= 0 ? positiveRes : negativeRes
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auto floatZero = rewriter.getFloatAttr(floatType, 0.0);
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Value zero = rewriter.create<arith::ConstantOp>(loc, floatZero);
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Value cmpRes = rewriter.create<arith::CmpFOp>(loc, arith::CmpFPredicate::OGE,
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op.getOperand(), zero);
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rewriter.replaceOpWithNewOp<arith::SelectOp>(op, cmpRes, positiveRes,
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negativeRes);
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return success();
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}
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void mlir::populateExpandTanhPattern(RewritePatternSet &patterns) {
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patterns.add(convertTanhOp);
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}
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