[Mlir-commits] [mlir] 3745e70 - [Tosa] Rename variables to coding style guideline (#69509)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Wed Oct 18 15:05:51 PDT 2023
Author: Tai Ly
Date: 2023-10-18T15:05:46-07:00
New Revision: 3745e7080746b73377a479b6ceba2dbf25f245e2
URL: https://github.com/llvm/llvm-project/commit/3745e7080746b73377a479b6ceba2dbf25f245e2
DIFF: https://github.com/llvm/llvm-project/commit/3745e7080746b73377a479b6ceba2dbf25f245e2.diff
LOG: [Tosa] Rename variables to coding style guideline (#69509)
This patch fixes variable names in the style guide. Specifically, names
in the form xyz_abc are changed to the form xyzAbc
Signed-off-by: Tai Ly <tai.ly at arm.com>
Added:
Modified:
mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp
mlir/lib/Dialect/Tosa/Utils/QuantUtils.cpp
Removed:
################################################################################
diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
index 94cbb0afd274445..18bc7d6aa9ee6a8 100644
--- a/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
+++ b/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
@@ -54,24 +54,24 @@ LogicalResult reshapeLowerToHigher(PatternRewriter &rewriter, Location loc,
return rewriter.notifyMatchFailure(loc,
"cannot rewrite as its already correct");
- Value input1_copy = input1;
- Value input2_copy = input2;
- if (EqualizeRanks(rewriter, loc, input1_copy, input2_copy).failed()) {
+ Value input1Copy = input1;
+ Value input2Copy = input2;
+ if (EqualizeRanks(rewriter, loc, input1Copy, input2Copy).failed()) {
return rewriter.notifyMatchFailure(loc, "failed to reshape inputs");
}
// Verify the rank agrees with the output type if the output type is ranked.
if (outputType) {
if (outputType.getRank() !=
- llvm::cast<RankedTensorType>(input1_copy.getType()).getRank() ||
+ llvm::cast<RankedTensorType>(input1Copy.getType()).getRank() ||
outputType.getRank() !=
- llvm::cast<RankedTensorType>(input2_copy.getType()).getRank())
+ llvm::cast<RankedTensorType>(input2Copy.getType()).getRank())
return rewriter.notifyMatchFailure(
loc, "the reshaped type doesn't agrees with the ranked output type");
}
- input1 = input1_copy;
- input2 = input2_copy;
+ input1 = input1Copy;
+ input2 = input2Copy;
return success();
}
diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp
index d973ac9cae2e842..8a2254fc24effe2 100644
--- a/mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp
+++ b/mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp
@@ -39,43 +39,43 @@ using namespace mlir::tosa;
namespace {
static LogicalResult checkConstantOperandPad(Operation *op) {
- if (auto pad_op = dyn_cast<tosa::PadOp>(op)) {
+ if (auto padOp = dyn_cast<tosa::PadOp>(op)) {
DenseElementsAttr paddings;
- if (!matchPattern(pad_op.getPadding(), m_Constant(&paddings)))
+ if (!matchPattern(padOp.getPadding(), m_Constant(&paddings)))
return op->emitOpError("padding of pad is not constant");
- DenseElementsAttr pad_const;
- // Assume this op is zero-padding if pad_const is not presented.
- if (pad_op.getPadConst() &&
- !matchPattern(pad_op.getPadConst(), m_Constant(&pad_const)))
+ DenseElementsAttr padConst;
+ // Assume this op is zero-padding if padConst is not presented.
+ if (padOp.getPadConst() &&
+ !matchPattern(padOp.getPadConst(), m_Constant(&padConst)))
return op->emitOpError("pad_const of pad is not constant");
}
return success();
}
static LogicalResult checkConstantOperandTranspose(Operation *op) {
- if (auto transpose_op = dyn_cast<tosa::TransposeOp>(op)) {
+ if (auto transposeOp = dyn_cast<tosa::TransposeOp>(op)) {
DenseElementsAttr perms;
- if (!matchPattern(transpose_op.getPerms(), m_Constant(&perms)))
+ if (!matchPattern(transposeOp.getPerms(), m_Constant(&perms)))
return op->emitOpError("perms of transpose is not constant");
}
return success();
}
static LogicalResult checkConstantOperandFullyConnected(Operation *op) {
- if (auto fc_op = dyn_cast<tosa::FullyConnectedOp>(op)) {
+ if (auto fcOp = dyn_cast<tosa::FullyConnectedOp>(op)) {
DenseElementsAttr weight;
- if (!matchPattern(fc_op.getWeight(), m_Constant(&weight)))
+ if (!matchPattern(fcOp.getWeight(), m_Constant(&weight)))
return op->emitOpError("weight of fully_connected is not constant");
DenseElementsAttr bias;
- if (!matchPattern(fc_op.getBias(), m_Constant(&bias)))
+ if (!matchPattern(fcOp.getBias(), m_Constant(&bias)))
return op->emitOpError("bias of fully_connected is not constant");
}
return success();
}
-struct tosa_level_t {
+struct TosaLevel {
int32_t MAX_RANK = 0;
int32_t MAX_KERNEL = 0;
int32_t MAX_STRIDE = 0;
@@ -83,14 +83,14 @@ struct tosa_level_t {
// @todo: MAX_LOG2_SIZE value and checks
- bool operator==(const tosa_level_t &rhs) {
+ bool operator==(const TosaLevel &rhs) {
return MAX_RANK == rhs.MAX_RANK && MAX_KERNEL == rhs.MAX_KERNEL &&
MAX_STRIDE == rhs.MAX_STRIDE && MAX_SCALE == rhs.MAX_SCALE;
}
};
-static constexpr tosa_level_t TOSA_LEVEL_EIGHTK = {6, 8192, 8192, 256};
-static constexpr tosa_level_t TOSA_LEVEL_NONE = {0, 0, 0, 0};
+static constexpr TosaLevel TOSA_LEVEL_EIGHTK = {6, 8192, 8192, 256};
+static constexpr TosaLevel TOSA_LEVEL_NONE = {0, 0, 0, 0};
//===----------------------------------------------------------------------===//
// TOSA Validation Pass.
@@ -108,7 +108,7 @@ struct TosaValidation : public tosa::impl::TosaValidationBase<TosaValidation> {
void runOnOperation() final;
LogicalResult applyConstantOperandCheck(Operation *op) {
- for (auto &checker : const_checkers) {
+ for (auto &checker : constCheckers) {
if (failed(checker(op)))
return failure();
}
@@ -122,43 +122,42 @@ struct TosaValidation : public tosa::impl::TosaValidationBase<TosaValidation> {
private:
void populateConstantOperandChecks() {
- const_checkers.emplace_back(checkConstantOperandPad);
- const_checkers.emplace_back(checkConstantOperandTranspose);
- const_checkers.emplace_back(checkConstantOperandFullyConnected);
+ constCheckers.emplace_back(checkConstantOperandPad);
+ constCheckers.emplace_back(checkConstantOperandTranspose);
+ constCheckers.emplace_back(checkConstantOperandFullyConnected);
}
bool levelCheckKernel(Operation *op, int32_t v,
- const std::string &check_desc) {
- if (v > tosa_level.MAX_KERNEL) {
- op->emitOpError() << "failed level check: " << check_desc;
+ const std::string &checkDesc) {
+ if (v > tosaLevel.MAX_KERNEL) {
+ op->emitOpError() << "failed level check: " << checkDesc;
return false;
}
return true;
}
bool levelCheckStride(Operation *op, int32_t v,
- const std::string &check_desc) {
- if (v > tosa_level.MAX_STRIDE) {
- op->emitOpError() << "failed level check: " << check_desc;
+ const std::string &checkDesc) {
+ if (v > tosaLevel.MAX_STRIDE) {
+ op->emitOpError() << "failed level check: " << checkDesc;
return false;
}
return true;
}
- bool levelCheckScale(Operation *op, int32_t v,
- const std::string &check_desc) {
- if (v > tosa_level.MAX_SCALE) {
- op->emitOpError() << "failed level check: " << check_desc;
+ bool levelCheckScale(Operation *op, int32_t v, const std::string &checkDesc) {
+ if (v > tosaLevel.MAX_SCALE) {
+ op->emitOpError() << "failed level check: " << checkDesc;
return false;
}
return true;
}
bool levelCheckRank(Operation *op, const Value &v,
- const std::string &check_desc) {
+ const std::string &checkDesc) {
if (ShapedType type = dyn_cast<ShapedType>(v.getType())) {
- if (type.getRank() > tosa_level.MAX_RANK) {
- op->emitOpError() << "failed level check: " << check_desc;
+ if (type.getRank() > tosaLevel.MAX_RANK) {
+ op->emitOpError() << "failed level check: " << checkDesc;
return false;
}
}
@@ -182,8 +181,8 @@ struct TosaValidation : public tosa::impl::TosaValidationBase<TosaValidation> {
}
bool levelCheckRanks(Operation *op) {
-#define CHECK_RANKS_FOR(tosa_op) \
- if (!levelCheckRanksFor<tosa_op##Op>(op)) \
+#define CHECK_RANKS_FOR(tosaOp) \
+ if (!levelCheckRanksFor<tosaOp##Op>(op)) \
return false;
// tensor operators:
@@ -257,18 +256,18 @@ struct TosaValidation : public tosa::impl::TosaValidationBase<TosaValidation> {
// Pool Op: level check kernel/stride/pad values
template <typename T>
bool levelCheckPool(Operation *op) {
- if (auto pool_op = dyn_cast<T>(op)) {
- for (auto k : pool_op.getKernel()) {
+ if (auto poolOp = dyn_cast<T>(op)) {
+ for (auto k : poolOp.getKernel()) {
if (!levelCheckKernel(op, k, "kernel <= MAX_KERNEL")) {
return false;
}
}
- for (auto s : pool_op.getStride()) {
+ for (auto s : poolOp.getStride()) {
if (!levelCheckStride(op, s, "stride <= MAX_STRIDE")) {
return false;
}
}
- for (auto p : pool_op.getPad()) {
+ for (auto p : poolOp.getPad()) {
if (!levelCheckKernel(op, p, "pad <= MAX_KERNEL")) {
return false;
}
@@ -280,27 +279,27 @@ struct TosaValidation : public tosa::impl::TosaValidationBase<TosaValidation> {
// Conv Op: level check dilation/stride/pad values
template <typename T>
bool levelCheckConv(Operation *op) {
- if (auto conv_op = dyn_cast<T>(op)) {
+ if (auto convOp = dyn_cast<T>(op)) {
- for (auto k : conv_op.getDilation()) {
+ for (auto k : convOp.getDilation()) {
if (!levelCheckKernel(op, k, "dilation <= MAX_KERNEL")) {
return false;
}
}
- for (auto p : conv_op.getPad()) {
+ for (auto p : convOp.getPad()) {
if (!levelCheckKernel(op, p, "pad <= MAX_KERNEL")) {
return false;
}
}
- for (auto s : conv_op.getStride()) {
+ for (auto s : convOp.getStride()) {
if (!levelCheckStride(op, s, "stride <= MAX_STRIDE")) {
return false;
}
}
- auto dilation = conv_op.getDilation();
- if (ShapedType weight_type =
+ auto dilation = convOp.getDilation();
+ if (ShapedType weightType =
dyn_cast<ShapedType>(op->getOperand(1).getType())) {
- auto shape = weight_type.getShape();
+ auto shape = weightType.getShape();
if (isa<tosa::Conv2DOp>(op)) {
assert(shape.size() == 4);
assert(dilation.size() == 2);
@@ -354,9 +353,9 @@ struct TosaValidation : public tosa::impl::TosaValidationBase<TosaValidation> {
// TransposeConv2d op: level check kH/kW, outpad, and stride
bool levelCheckTransposeConv2d(Operation *op) {
if (auto transpose = dyn_cast<tosa::TransposeConv2DOp>(op)) {
- if (ShapedType filter_type =
+ if (ShapedType filterType =
transpose.getFilter().getType().dyn_cast<ShapedType>()) {
- auto shape = filter_type.getShape();
+ auto shape = filterType.getShape();
assert(shape.size() == 4);
// level check kernel sizes for kH and KW
if (!levelCheckKernel(op, shape[1], "KH <= MAX_KERNEL") ||
@@ -382,13 +381,13 @@ struct TosaValidation : public tosa::impl::TosaValidationBase<TosaValidation> {
bool levelCheckResize(Operation *op) {
if (auto resize = dyn_cast<tosa::ResizeOp>(op)) {
auto scale = resize.getScale();
- int16_t scale_y_n = scale[0];
- int16_t scale_y_d = scale[1];
- int16_t scale_x_n = scale[2];
- int16_t scale_x_d = scale[3];
- if (!levelCheckScale(op, scale_y_n / scale_y_d,
+ int16_t scaleYN = scale[0];
+ int16_t scaleYD = scale[1];
+ int16_t scaleXN = scale[2];
+ int16_t scaleXD = scale[3];
+ if (!levelCheckScale(op, scaleYN / scaleYD,
"scale_y_n/scale_y_d <= MAX_SCALE") ||
- !levelCheckScale(op, scale_x_n / scale_x_d,
+ !levelCheckScale(op, scaleXN / scaleXD,
"scale_x_n/scale_x_d <= MAX_SCALE")) {
return false;
}
@@ -399,22 +398,22 @@ struct TosaValidation : public tosa::impl::TosaValidationBase<TosaValidation> {
// configure profile and level values from pass options profileName and
// levelName
void configLevelAndProfile() {
- tosa_level = TOSA_LEVEL_NONE;
+ tosaLevel = TOSA_LEVEL_NONE;
if (level == TosaLevelEnum::EightK) {
- tosa_level = TOSA_LEVEL_EIGHTK;
+ tosaLevel = TOSA_LEVEL_EIGHTK;
}
}
bool CheckVariable(Operation *op);
bool CheckVariableReadOrWrite(Operation *op);
- SmallVector<std::function<LogicalResult(Operation *)>> const_checkers;
- tosa_level_t tosa_level;
- DenseMap<StringAttr, mlir::Type> variables_map;
+ SmallVector<std::function<LogicalResult(Operation *)>> constCheckers;
+ TosaLevel tosaLevel;
+ DenseMap<StringAttr, mlir::Type> variablesMap;
};
LogicalResult TosaValidation::applyLevelCheck(Operation *op) {
- if (tosa_level == TOSA_LEVEL_NONE) {
+ if (tosaLevel == TOSA_LEVEL_NONE) {
// no need to do level checks
return success();
}
@@ -439,24 +438,24 @@ LogicalResult TosaValidation::applyLevelCheck(Operation *op) {
}
inline bool CompatibleTypes(const mlir::Type &type,
- const mlir::Type &declared_type) {
+ const mlir::Type &declaredType) {
// for now, simply use type equality comparison
- return type == declared_type;
+ return type == declaredType;
}
bool TosaValidation::CheckVariable(Operation *op) {
if (isa<mlir::tosa::VariableOp>(op)) {
- auto name_attr = cast<mlir::StringAttr>(op->getAttr("name"));
+ auto nameAttr = cast<mlir::StringAttr>(op->getAttr("name"));
- if (variables_map.count(name_attr)) {
+ if (variablesMap.count(nameAttr)) {
op->emitOpError() << "name has already been declared";
return false;
}
- auto type_attr = cast<mlir::TypeAttr>(op->getAttr("type"));
- mlir::Type type = type_attr.getValue();
+ auto typeAttr = cast<mlir::TypeAttr>(op->getAttr("type"));
+ mlir::Type type = typeAttr.getValue();
- variables_map[name_attr] = type;
+ variablesMap[nameAttr] = type;
}
return true;
@@ -465,18 +464,18 @@ bool TosaValidation::CheckVariable(Operation *op) {
bool TosaValidation::CheckVariableReadOrWrite(Operation *op) {
if (isa<mlir::tosa::VariableReadOp>(op) ||
isa<mlir::tosa::VariableWriteOp>(op)) {
- auto name_attr = cast<mlir::StringAttr>(op->getAttr("name"));
+ auto nameAttr = cast<mlir::StringAttr>(op->getAttr("name"));
- if (!variables_map.count(name_attr)) {
+ if (!variablesMap.count(nameAttr)) {
op->emitOpError() << "name has not been declared";
return false;
}
- auto var_type = variables_map[name_attr];
+ auto varType = variablesMap[nameAttr];
for (auto v : op->getOperands()) {
auto type = v.getType();
- if (!CompatibleTypes(type, var_type)) {
+ if (!CompatibleTypes(type, varType)) {
op->emitOpError() << "operand type does not equal variable type";
return false;
}
@@ -484,7 +483,7 @@ bool TosaValidation::CheckVariableReadOrWrite(Operation *op) {
for (auto v : op->getResults()) {
auto type = v.getType();
- if (!CompatibleTypes(type, var_type)) {
+ if (!CompatibleTypes(type, varType)) {
op->emitOpError() << "result type does not equal variable type";
return false;
}
diff --git a/mlir/lib/Dialect/Tosa/Utils/QuantUtils.cpp b/mlir/lib/Dialect/Tosa/Utils/QuantUtils.cpp
index eb81446caacaba5..5c546f59cde4132 100644
--- a/mlir/lib/Dialect/Tosa/Utils/QuantUtils.cpp
+++ b/mlir/lib/Dialect/Tosa/Utils/QuantUtils.cpp
@@ -107,10 +107,10 @@ void mlir::tosa::computeMultiplierAndShift(double scale, int32_t &multiplier,
}
}
-#define GET_UQTYPE(input_type) \
- (llvm::dyn_cast<quant::UniformQuantizedType>((input_type).getElementType()))
-#define GET_QTYPE(input_type) \
- (llvm::dyn_cast<quant::QuantizedType>((input_type).getElementType()))
+#define GET_UQTYPE(inputType) \
+ (llvm::dyn_cast<quant::UniformQuantizedType>((inputType).getElementType()))
+#define GET_QTYPE(inputType) \
+ (llvm::dyn_cast<quant::QuantizedType>((inputType).getElementType()))
/// Method to build ConvOpQuantizationAttr, called from
/// ConvOpQuantInfoBuilder/TransConvOpQuantInfoBuilder:
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