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[TOSA] TOSA updates for LLVM hash 8885b5c #4087

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[TOSA] TOSA updates for LLVM hash 8885b5c #4087

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52 changes: 41 additions & 11 deletions lib/Conversion/TorchToTosa/TorchToTosa.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1848,22 +1848,52 @@ class ConvertAtenMatmulBaseOp : public OpConversionPattern<AtenOpT> {
SmallVector<int64_t> matmulOutputShape(
{matmulLhsShape[0], matmulLhsShape[1], matmulRhsShape[2]});
Type outputElemTy;
if (isa<mlir::FloatType>(lhsElemTy)) {
outputElemTy = lhsElemTy;
} else { // qint8 emits i32 matmul output

bool isInputElemTyQInt8 = false;
if (isa<mlir::quant::UniformQuantizedType>(lhsElemTy)) {
mlir::quant::UniformQuantizedType inputQTy =
dyn_cast<mlir::quant::UniformQuantizedType>(lhsElemTy);
if (inputQTy.getStorageTypeIntegralWidth() == 8)
isInputElemTyQInt8 = true;
}

if (isInputElemTyQInt8) {
// qint8 emits i32 matmul output
outputElemTy = rewriter.getIntegerType(32);
} else {
outputElemTy = lhsElemTy;
}

auto mmOutputTy = RankedTensorType::get(
makeShapeLLVMCompatible(matmulOutputShape), outputElemTy);
auto mmOpResult =
rewriter
.create<tosa::MatMulOp>(
op->getLoc(),
OpConversionPattern<AtenOpT>::getTypeConverter()->convertType(
mmOutputTy),
matmulLhs, matmulRhs)
.getResult();

Value mmOpResult;
if (!isInputElemTyQInt8) {
// LHS and RHS tensors' zero points must be zero for non-int8 types
Value lhsZp =
tosa::createZeroPointTensor(rewriter, op->getLoc(), lhsElemTy, 0)
.value();
Value rhsZp =
tosa::createZeroPointTensor(rewriter, op->getLoc(), rhsElemTy, 0)
.value();
mmOpResult =
rewriter
.create<tosa::MatMulOp>(
op->getLoc(),
OpConversionPattern<AtenOpT>::getTypeConverter()->convertType(
mmOutputTy),
matmulLhs, matmulRhs, lhsZp, rhsZp)
.getResult();
} else {
mmOpResult =
rewriter
.create<tosa::MatMulOp>(
op->getLoc(),
OpConversionPattern<AtenOpT>::getTypeConverter()->convertType(
mmOutputTy),
matmulLhs, matmulRhs)
.getResult();
}

// Perform the reshape to output shape. This is always required unless max
// input rank=3 and there was no broadcasting, in which case the tosa.matmul
Expand Down
74 changes: 59 additions & 15 deletions lib/Conversion/TorchToTosa/TosaLegalizeUtils.cpp
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Expand Up @@ -15,6 +15,21 @@
namespace mlir {
namespace tosa {

Value buildRescaleMultiplier(bool scale32, PatternRewriter &rewriter,
Operation *op, ArrayRef<int32_t> multipliers) {
if (scale32) {
return tosa::getConstTensor<int32_t>(
rewriter, op, multipliers,
{static_cast<int64_t>(multipliers.size())})
.value();
} else {
SmallVector<int16_t> vec(multipliers.begin(), multipliers.end());
return tosa::getConstTensor<int16_t>(rewriter, op, vec,
{static_cast<int64_t>(vec.size())})
.value();
}
}

// Create a TOSA rescale op from input framework tensor, zero points and
// rounding mode
Value buildRescale(PatternRewriter &rewriter, Operation *op,
Expand All @@ -28,14 +43,22 @@ Value buildRescale(PatternRewriter &rewriter, Operation *op,

computeMultiplierAndShift(scale, multiplier, shift, scale_width);

Value multiplier_val =
buildRescaleMultiplier(scale32, rewriter, op, {multiplier});
auto shift_val = tosa::getConstTensor<int8_t>(
rewriter, op, {static_cast<int8_t>(shift)}, {1})
.value();

bool input_unsigned = input_val.getType().isUnsignedInteger();
bool output_unsigned = output_type.isUnsignedInteger();

auto rescale_op = CreateOpAndInfer<tosa::RescaleOp>(
rewriter, op->getLoc(), output_type, input_val,
rewriter, op->getLoc(), output_type, input_val, multiplier_val, shift_val,
rewriter.getI32IntegerAttr(static_cast<int32_t>(input_zp)),
rewriter.getI32IntegerAttr(static_cast<int32_t>(output_zp)),
rewriter.getDenseI32ArrayAttr({multiplier}),
rewriter.getDenseI8ArrayAttr({static_cast<int8_t>(shift)}),
rewriter.getBoolAttr(scale32), rewriter.getBoolAttr(double_round),
rewriter.getBoolAttr(false));
rewriter.getBoolAttr(false), rewriter.getBoolAttr(input_unsigned),
rewriter.getBoolAttr(output_unsigned));

return rescale_op.getResult();
}
Expand Down Expand Up @@ -70,6 +93,9 @@ Value buildRescaleOpConvOutput(PatternRewriter &rewriter, Operation *op,
bool scale32 = isScale32(output_qtype);
int32_t scale_width = scale32 ? 32 : 16;

bool input_unsigned = input_qtype.isUnsignedInteger();
bool output_unsigned = output_qtype.isUnsignedInteger();

if (auto weight_per_tensor_qtype =
dyn_cast<mlir::quant::UniformQuantizedType>(
weight_type.getElementType())) {
Expand All @@ -83,13 +109,19 @@ Value buildRescaleOpConvOutput(PatternRewriter &rewriter, Operation *op,

computeMultiplierAndShift(op_tensor_scale, multiplier, shift, scale_width);

Value multiplier_val =
buildRescaleMultiplier(scale32, rewriter, op, {multiplier});
auto shift_val = tosa::getConstTensor<int8_t>(
rewriter, op, {static_cast<int8_t>(shift)}, {1})
.value();

auto rescale_op = CreateOpAndInfer<tosa::RescaleOp>(
rewriter, op->getLoc(), output_type, conv_val,
rewriter.getI32IntegerAttr(0), rewriter.getI32IntegerAttr(output_zp),
rewriter.getDenseI32ArrayAttr({multiplier}),
rewriter.getDenseI8ArrayAttr({static_cast<int8_t>(shift)}),
rewriter.getBoolAttr(scale32), rewriter.getBoolAttr(true),
rewriter.getBoolAttr(false));
rewriter, op->getLoc(), output_type, conv_val, multiplier_val,
shift_val, rewriter.getI32IntegerAttr(0),
rewriter.getI32IntegerAttr(output_zp), rewriter.getBoolAttr(scale32),
rewriter.getBoolAttr(true), rewriter.getBoolAttr(false),
rewriter.getBoolAttr(input_unsigned),
rewriter.getBoolAttr(output_unsigned));

return rescale_op.getResult();

Expand Down Expand Up @@ -120,12 +152,20 @@ Value buildRescaleOpConvOutput(PatternRewriter &rewriter, Operation *op,
shift_arr.push_back(static_cast<int8_t>(shift));
}

Value multiplier_val =
buildRescaleMultiplier(scale32, rewriter, op, multiplier_arr);
auto shift_val =
tosa::getConstTensor<int8_t>(rewriter, op, shift_arr,
{static_cast<int64_t>(shift_arr.size())})
.value();

auto rescale_op = CreateOpAndInfer<tosa::RescaleOp>(
rewriter, op->getLoc(), output_type, conv_val,
rewriter.getI32IntegerAttr(0), rewriter.getI32IntegerAttr(output_zp),
rewriter.getDenseI32ArrayAttr(multiplier_arr),
rewriter.getDenseI8ArrayAttr(shift_arr), rewriter.getBoolAttr(scale32),
rewriter.getBoolAttr(true), rewriter.getBoolAttr(true));
rewriter, op->getLoc(), output_type, conv_val, multiplier_val,
shift_val, rewriter.getI32IntegerAttr(0),
rewriter.getI32IntegerAttr(output_zp), rewriter.getBoolAttr(scale32),
rewriter.getBoolAttr(true), rewriter.getBoolAttr(true),
rewriter.getBoolAttr(input_unsigned),
rewriter.getBoolAttr(output_unsigned));

return rescale_op.getResult();

Expand Down Expand Up @@ -408,6 +448,10 @@ template std::optional<Value>
getConstTensor<int8_t>(PatternRewriter &, Operation *, ArrayRef<int8_t> vec,
ArrayRef<int64_t> shape, std::optional<Type> dtype);

template std::optional<Value>
getConstTensor<int16_t>(PatternRewriter &, Operation *, ArrayRef<int16_t> vec,
ArrayRef<int64_t> shape, std::optional<Type> dtype);

template std::optional<Value>
getConstTensor<int32_t>(PatternRewriter &, Operation *, ArrayRef<int32_t> vec,
ArrayRef<int64_t> shape, std::optional<Type> dtype);
Expand Down
2 changes: 0 additions & 2 deletions projects/pt1/e2e_testing/xfail_sets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3472,7 +3472,6 @@
"AtenMatmulQint8VM_basic",
"AtenMatmulQint8VV_basic",
"AtenMatmulQint8_basic",
"AtenMmIntTypes_basic",
"AtenMmQMixedSigni8_basic",
"AtenMmQint8_basic",
"AtenMmQuint8_basic",
Expand All @@ -3496,7 +3495,6 @@
"BincountMinlengthModule_basic",
"BincountModule_basic",
"BincountStaticSizeModule_basic",
"BmmIntModule_basic",
"BoolFloatConstantModule_basic",
"BoolFloatFalseModule_basic",
"BoolFloatTrueModule_basic",
Expand Down
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