llvm-project/mlir/lib/Parser/AttributeParser.cpp

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//===- AttributeParser.cpp - MLIR Attribute Parser Implementation ---------===//
//
// 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 the parser for the MLIR Types.
//
//===----------------------------------------------------------------------===//
#include "Parser.h"
#include "mlir/IR/AffineMap.h"
#include "mlir/IR/BuiltinTypes.h"
Separate the Registration from Loading dialects in the Context This changes the behavior of constructing MLIRContext to no longer load globally registered dialects on construction. Instead Dialects are only loaded explicitly on demand: - the Parser is lazily loading Dialects in the context as it encounters them during parsing. This is the only purpose for registering dialects and not load them in the context. - Passes are expected to declare the dialects they will create entity from (Operations, Attributes, or Types), and the PassManager is loading Dialects into the Context when starting a pipeline. This changes simplifies the configuration of the registration: a compiler only need to load the dialect for the IR it will emit, and the optimizer is self-contained and load the required Dialects. For example in the Toy tutorial, the compiler only needs to load the Toy dialect in the Context, all the others (linalg, affine, std, LLVM, ...) are automatically loaded depending on the optimization pipeline enabled. To adjust to this change, stop using the existing dialect registration: the global registry will be removed soon. 1) For passes, you need to override the method: virtual void getDependentDialects(DialectRegistry &registry) const {} and registery on the provided registry any dialect that this pass can produce. Passes defined in TableGen can provide this list in the dependentDialects list field. 2) For dialects, on construction you can register dependent dialects using the provided MLIRContext: `context.getOrLoadDialect<DialectName>()` This is useful if a dialect may canonicalize or have interfaces involving another dialect. 3) For loading IR, dialect that can be in the input file must be explicitly registered with the context. `MlirOptMain()` is taking an explicit registry for this purpose. See how the standalone-opt.cpp example is setup: mlir::DialectRegistry registry; registry.insert<mlir::standalone::StandaloneDialect>(); registry.insert<mlir::StandardOpsDialect>(); Only operations from these two dialects can be in the input file. To include all of the dialects in MLIR Core, you can populate the registry this way: mlir::registerAllDialects(registry); 4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in the context before emitting the IR: context.getOrLoadDialect<ToyDialect>() Differential Revision: https://reviews.llvm.org/D85622
2020-08-19 04:01:19 +08:00
#include "mlir/IR/Dialect.h"
#include "mlir/IR/IntegerSet.h"
#include "mlir/Parser/AsmParserState.h"
#include "llvm/ADT/StringExtras.h"
#include "llvm/Support/Endian.h"
using namespace mlir;
using namespace mlir::detail;
/// Parse an arbitrary attribute.
///
/// attribute-value ::= `unit`
/// | bool-literal
/// | integer-literal (`:` (index-type | integer-type))?
/// | float-literal (`:` float-type)?
/// | string-literal (`:` type)?
/// | type
/// | `[` (attribute-value (`,` attribute-value)*)? `]`
/// | `{` (attribute-entry (`,` attribute-entry)*)? `}`
/// | symbol-ref-id (`::` symbol-ref-id)*
/// | `dense` `<` attribute-value `>` `:`
/// (tensor-type | vector-type)
/// | `sparse` `<` attribute-value `,` attribute-value `>`
/// `:` (tensor-type | vector-type)
/// | `opaque` `<` dialect-namespace `,` hex-string-literal
/// `>` `:` (tensor-type | vector-type)
/// | extended-attribute
///
Attribute Parser::parseAttribute(Type type) {
switch (getToken().getKind()) {
// Parse an AffineMap or IntegerSet attribute.
case Token::kw_affine_map: {
consumeToken(Token::kw_affine_map);
AffineMap map;
if (parseToken(Token::less, "expected '<' in affine map") ||
parseAffineMapReference(map) ||
parseToken(Token::greater, "expected '>' in affine map"))
return Attribute();
return AffineMapAttr::get(map);
}
case Token::kw_affine_set: {
consumeToken(Token::kw_affine_set);
IntegerSet set;
if (parseToken(Token::less, "expected '<' in integer set") ||
parseIntegerSetReference(set) ||
parseToken(Token::greater, "expected '>' in integer set"))
return Attribute();
return IntegerSetAttr::get(set);
}
// Parse an array attribute.
case Token::l_square: {
SmallVector<Attribute, 4> elements;
auto parseElt = [&]() -> ParseResult {
elements.push_back(parseAttribute());
return elements.back() ? success() : failure();
};
if (parseCommaSeparatedList(Delimiter::Square, parseElt))
return nullptr;
return builder.getArrayAttr(elements);
}
// Parse a boolean attribute.
case Token::kw_false:
consumeToken(Token::kw_false);
return builder.getBoolAttr(false);
case Token::kw_true:
consumeToken(Token::kw_true);
return builder.getBoolAttr(true);
// Parse a dense elements attribute.
case Token::kw_dense:
return parseDenseElementsAttr(type);
// Parse a dictionary attribute.
case Token::l_brace: {
NamedAttrList elements;
if (parseAttributeDict(elements))
return nullptr;
return elements.getDictionary(getContext());
}
// Parse an extended attribute, i.e. alias or dialect attribute.
case Token::hash_identifier:
return parseExtendedAttr(type);
// Parse floating point and integer attributes.
case Token::floatliteral:
return parseFloatAttr(type, /*isNegative=*/false);
case Token::integer:
return parseDecOrHexAttr(type, /*isNegative=*/false);
case Token::minus: {
consumeToken(Token::minus);
if (getToken().is(Token::integer))
return parseDecOrHexAttr(type, /*isNegative=*/true);
if (getToken().is(Token::floatliteral))
return parseFloatAttr(type, /*isNegative=*/true);
return (emitError("expected constant integer or floating point value"),
nullptr);
}
// Parse a location attribute.
case Token::kw_loc: {
consumeToken(Token::kw_loc);
LocationAttr locAttr;
if (parseToken(Token::l_paren, "expected '(' in inline location") ||
parseLocationInstance(locAttr) ||
parseToken(Token::r_paren, "expected ')' in inline location"))
return Attribute();
return locAttr;
}
// Parse an opaque elements attribute.
case Token::kw_opaque:
return parseOpaqueElementsAttr(type);
// Parse a sparse elements attribute.
case Token::kw_sparse:
return parseSparseElementsAttr(type);
// Parse a string attribute.
case Token::string: {
auto val = getToken().getStringValue();
consumeToken(Token::string);
// Parse the optional trailing colon type if one wasn't explicitly provided.
if (!type && consumeIf(Token::colon) && !(type = parseType()))
return Attribute();
return type ? StringAttr::get(val, type)
: StringAttr::get(getContext(), val);
}
// Parse a symbol reference attribute.
case Token::at_identifier: {
// When populating the parser state, this is a list of locations for all of
// the nested references.
SmallVector<llvm::SMRange> referenceLocations;
if (state.asmState)
referenceLocations.push_back(getToken().getLocRange());
// Parse the top-level reference.
std::string nameStr = getToken().getSymbolReference();
consumeToken(Token::at_identifier);
// Parse any nested references.
std::vector<FlatSymbolRefAttr> nestedRefs;
while (getToken().is(Token::colon)) {
// Check for the '::' prefix.
const char *curPointer = getToken().getLoc().getPointer();
consumeToken(Token::colon);
if (!consumeIf(Token::colon)) {
state.lex.resetPointer(curPointer);
consumeToken();
break;
}
// Parse the reference itself.
auto curLoc = getToken().getLoc();
if (getToken().isNot(Token::at_identifier)) {
emitError(curLoc, "expected nested symbol reference identifier");
return Attribute();
}
// If we are populating the assembly state, add the location for this
// reference.
if (state.asmState)
referenceLocations.push_back(getToken().getLocRange());
std::string nameStr = getToken().getSymbolReference();
consumeToken(Token::at_identifier);
nestedRefs.push_back(SymbolRefAttr::get(getContext(), nameStr));
}
SymbolRefAttr symbolRefAttr =
SymbolRefAttr::get(getContext(), nameStr, nestedRefs);
// If we are populating the assembly state, record this symbol reference.
if (state.asmState)
state.asmState->addUses(symbolRefAttr, referenceLocations);
return symbolRefAttr;
}
// Parse a 'unit' attribute.
case Token::kw_unit:
consumeToken(Token::kw_unit);
return builder.getUnitAttr();
default:
// Parse a type attribute.
if (Type type = parseType())
return TypeAttr::get(type);
return nullptr;
}
}
/// Parse an optional attribute with the provided type.
OptionalParseResult Parser::parseOptionalAttribute(Attribute &attribute,
Type type) {
switch (getToken().getKind()) {
case Token::at_identifier:
case Token::floatliteral:
case Token::integer:
case Token::hash_identifier:
case Token::kw_affine_map:
case Token::kw_affine_set:
case Token::kw_dense:
case Token::kw_false:
case Token::kw_loc:
case Token::kw_opaque:
case Token::kw_sparse:
case Token::kw_true:
case Token::kw_unit:
case Token::l_brace:
case Token::l_square:
case Token::minus:
case Token::string:
attribute = parseAttribute(type);
return success(attribute != nullptr);
default:
// Parse an optional type attribute.
Type type;
OptionalParseResult result = parseOptionalType(type);
if (result.hasValue() && succeeded(*result))
attribute = TypeAttr::get(type);
return result;
}
}
OptionalParseResult Parser::parseOptionalAttribute(ArrayAttr &attribute,
Type type) {
return parseOptionalAttributeWithToken(Token::l_square, attribute, type);
[mlir][PDL] Add a PDL Interpreter Dialect The PDL Interpreter dialect provides a lower level abstraction compared to the PDL dialect, and is targeted towards low level optimization and interpreter code generation. The dialect operations encapsulates low-level pattern match and rewrite "primitives", such as navigating the IR (Operation::getOperand), creating new operations (OpBuilder::create), etc. Many of the operations within this dialect also fuse branching control flow with some form of a predicate comparison operation. This type of fusion reduces the amount of work that an interpreter must do when executing. An example of this representation is shown below: ```mlir // The following high level PDL pattern: pdl.pattern : benefit(1) { %resultType = pdl.type %inputOperand = pdl.input %root, %results = pdl.operation "foo.op"(%inputOperand) -> %resultType pdl.rewrite %root { pdl.replace %root with (%inputOperand) } } // May be represented in the interpreter dialect as follows: module { func @matcher(%arg0: !pdl.operation) { pdl_interp.check_operation_name of %arg0 is "foo.op" -> ^bb2, ^bb1 ^bb1: pdl_interp.return ^bb2: pdl_interp.check_operand_count of %arg0 is 1 -> ^bb3, ^bb1 ^bb3: pdl_interp.check_result_count of %arg0 is 1 -> ^bb4, ^bb1 ^bb4: %0 = pdl_interp.get_operand 0 of %arg0 pdl_interp.is_not_null %0 : !pdl.value -> ^bb5, ^bb1 ^bb5: %1 = pdl_interp.get_result 0 of %arg0 pdl_interp.is_not_null %1 : !pdl.value -> ^bb6, ^bb1 ^bb6: pdl_interp.record_match @rewriters::@rewriter(%0, %arg0 : !pdl.value, !pdl.operation) : benefit(1), loc([%arg0]), root("foo.op") -> ^bb1 } module @rewriters { func @rewriter(%arg0: !pdl.value, %arg1: !pdl.operation) { pdl_interp.replace %arg1 with(%arg0) pdl_interp.return } } } ``` Differential Revision: https://reviews.llvm.org/D84579
2020-08-26 20:12:07 +08:00
}
OptionalParseResult Parser::parseOptionalAttribute(StringAttr &attribute,
Type type) {
return parseOptionalAttributeWithToken(Token::string, attribute, type);
}
/// Attribute dictionary.
///
/// attribute-dict ::= `{` `}`
/// | `{` attribute-entry (`,` attribute-entry)* `}`
/// attribute-entry ::= (bare-id | string-literal) `=` attribute-value
///
ParseResult Parser::parseAttributeDict(NamedAttrList &attributes) {
llvm::SmallDenseSet<StringAttr> seenKeys;
auto parseElt = [&]() -> ParseResult {
// The name of an attribute can either be a bare identifier, or a string.
Optional<StringAttr> nameId;
if (getToken().is(Token::string))
nameId = builder.getStringAttr(getToken().getStringValue());
else if (getToken().isAny(Token::bare_identifier, Token::inttype) ||
getToken().isKeyword())
nameId = builder.getStringAttr(getTokenSpelling());
else
return emitError("expected attribute name");
if (!seenKeys.insert(*nameId).second)
return emitError("duplicate key '")
<< nameId->getValue() << "' in dictionary attribute";
consumeToken();
Separate the Registration from Loading dialects in the Context This changes the behavior of constructing MLIRContext to no longer load globally registered dialects on construction. Instead Dialects are only loaded explicitly on demand: - the Parser is lazily loading Dialects in the context as it encounters them during parsing. This is the only purpose for registering dialects and not load them in the context. - Passes are expected to declare the dialects they will create entity from (Operations, Attributes, or Types), and the PassManager is loading Dialects into the Context when starting a pipeline. This changes simplifies the configuration of the registration: a compiler only need to load the dialect for the IR it will emit, and the optimizer is self-contained and load the required Dialects. For example in the Toy tutorial, the compiler only needs to load the Toy dialect in the Context, all the others (linalg, affine, std, LLVM, ...) are automatically loaded depending on the optimization pipeline enabled. To adjust to this change, stop using the existing dialect registration: the global registry will be removed soon. 1) For passes, you need to override the method: virtual void getDependentDialects(DialectRegistry &registry) const {} and registery on the provided registry any dialect that this pass can produce. Passes defined in TableGen can provide this list in the dependentDialects list field. 2) For dialects, on construction you can register dependent dialects using the provided MLIRContext: `context.getOrLoadDialect<DialectName>()` This is useful if a dialect may canonicalize or have interfaces involving another dialect. 3) For loading IR, dialect that can be in the input file must be explicitly registered with the context. `MlirOptMain()` is taking an explicit registry for this purpose. See how the standalone-opt.cpp example is setup: mlir::DialectRegistry registry; registry.insert<mlir::standalone::StandaloneDialect>(); registry.insert<mlir::StandardOpsDialect>(); Only operations from these two dialects can be in the input file. To include all of the dialects in MLIR Core, you can populate the registry this way: mlir::registerAllDialects(registry); 4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in the context before emitting the IR: context.getOrLoadDialect<ToyDialect>() Differential Revision: https://reviews.llvm.org/D85622
2020-08-19 04:01:19 +08:00
// Lazy load a dialect in the context if there is a possible namespace.
auto splitName = nameId->strref().split('.');
if (!splitName.second.empty())
getContext()->getOrLoadDialect(splitName.first);
// Try to parse the '=' for the attribute value.
if (!consumeIf(Token::equal)) {
// If there is no '=', we treat this as a unit attribute.
attributes.push_back({*nameId, builder.getUnitAttr()});
return success();
}
auto attr = parseAttribute();
if (!attr)
return failure();
attributes.push_back({*nameId, attr});
return success();
};
if (parseCommaSeparatedList(Delimiter::Braces, parseElt,
" in attribute dictionary"))
return failure();
return success();
}
/// Parse a float attribute.
Attribute Parser::parseFloatAttr(Type type, bool isNegative) {
auto val = getToken().getFloatingPointValue();
if (!val.hasValue())
return (emitError("floating point value too large for attribute"), nullptr);
consumeToken(Token::floatliteral);
if (!type) {
// Default to F64 when no type is specified.
if (!consumeIf(Token::colon))
type = builder.getF64Type();
else if (!(type = parseType()))
return nullptr;
}
if (!type.isa<FloatType>())
return (emitError("floating point value not valid for specified type"),
nullptr);
return FloatAttr::get(type, isNegative ? -val.getValue() : val.getValue());
}
/// Construct an APint from a parsed value, a known attribute type and
/// sign.
static Optional<APInt> buildAttributeAPInt(Type type, bool isNegative,
StringRef spelling) {
// Parse the integer value into an APInt that is big enough to hold the value.
APInt result;
bool isHex = spelling.size() > 1 && spelling[1] == 'x';
if (spelling.getAsInteger(isHex ? 0 : 10, result))
return llvm::None;
// Extend or truncate the bitwidth to the right size.
unsigned width = type.isIndex() ? IndexType::kInternalStorageBitWidth
: type.getIntOrFloatBitWidth();
if (width > result.getBitWidth()) {
result = result.zext(width);
} else if (width < result.getBitWidth()) {
// The parser can return an unnecessarily wide result with leading zeros.
// This isn't a problem, but truncating off bits is bad.
if (result.countLeadingZeros() < result.getBitWidth() - width)
return llvm::None;
result = result.trunc(width);
}
if (width == 0) {
// 0 bit integers cannot be negative and manipulation of their sign bit will
// assert, so short-cut validation here.
if (isNegative)
return llvm::None;
} else if (isNegative) {
// The value is negative, we have an overflow if the sign bit is not set
// in the negated apInt.
result.negate();
if (!result.isSignBitSet())
return llvm::None;
} else if ((type.isSignedInteger() || type.isIndex()) &&
result.isSignBitSet()) {
// The value is a positive signed integer or index,
// we have an overflow if the sign bit is set.
return llvm::None;
}
return result;
}
/// Parse a decimal or a hexadecimal literal, which can be either an integer
/// or a float attribute.
Attribute Parser::parseDecOrHexAttr(Type type, bool isNegative) {
Token tok = getToken();
StringRef spelling = tok.getSpelling();
llvm::SMLoc loc = tok.getLoc();
consumeToken(Token::integer);
if (!type) {
// Default to i64 if not type is specified.
if (!consumeIf(Token::colon))
type = builder.getIntegerType(64);
else if (!(type = parseType()))
return nullptr;
}
if (auto floatType = type.dyn_cast<FloatType>()) {
Optional<APFloat> result;
if (failed(parseFloatFromIntegerLiteral(result, tok, isNegative,
floatType.getFloatSemantics(),
floatType.getWidth())))
return Attribute();
return FloatAttr::get(floatType, *result);
}
if (!type.isa<IntegerType, IndexType>())
return emitError(loc, "integer literal not valid for specified type"),
nullptr;
if (isNegative && type.isUnsignedInteger()) {
emitError(loc,
"negative integer literal not valid for unsigned integer type");
return nullptr;
}
Optional<APInt> apInt = buildAttributeAPInt(type, isNegative, spelling);
if (!apInt)
return emitError(loc, "integer constant out of range for attribute"),
nullptr;
return builder.getIntegerAttr(type, *apInt);
}
//===----------------------------------------------------------------------===//
// TensorLiteralParser
//===----------------------------------------------------------------------===//
/// Parse elements values stored within a hex string. On success, the values are
/// stored into 'result'.
static ParseResult parseElementAttrHexValues(Parser &parser, Token tok,
std::string &result) {
if (Optional<std::string> value = tok.getHexStringValue()) {
result = std::move(*value);
return success();
}
return parser.emitError(
tok.getLoc(), "expected string containing hex digits starting with `0x`");
}
namespace {
/// This class implements a parser for TensorLiterals. A tensor literal is
/// either a single element (e.g, 5) or a multi-dimensional list of elements
/// (e.g., [[5, 5]]).
class TensorLiteralParser {
public:
TensorLiteralParser(Parser &p) : p(p) {}
/// Parse the elements of a tensor literal. If 'allowHex' is true, the parser
/// may also parse a tensor literal that is store as a hex string.
ParseResult parse(bool allowHex);
/// Build a dense attribute instance with the parsed elements and the given
/// shaped type.
DenseElementsAttr getAttr(llvm::SMLoc loc, ShapedType type);
ArrayRef<int64_t> getShape() const { return shape; }
private:
/// Get the parsed elements for an integer attribute.
ParseResult getIntAttrElements(llvm::SMLoc loc, Type eltTy,
std::vector<APInt> &intValues);
/// Get the parsed elements for a float attribute.
ParseResult getFloatAttrElements(llvm::SMLoc loc, FloatType eltTy,
std::vector<APFloat> &floatValues);
/// Build a Dense String attribute for the given type.
DenseElementsAttr getStringAttr(llvm::SMLoc loc, ShapedType type, Type eltTy);
/// Build a Dense attribute with hex data for the given type.
DenseElementsAttr getHexAttr(llvm::SMLoc loc, ShapedType type);
/// Parse a single element, returning failure if it isn't a valid element
/// literal. For example:
/// parseElement(1) -> Success, 1
/// parseElement([1]) -> Failure
ParseResult parseElement();
/// Parse a list of either lists or elements, returning the dimensions of the
/// parsed sub-tensors in dims. For example:
/// parseList([1, 2, 3]) -> Success, [3]
/// parseList([[1, 2], [3, 4]]) -> Success, [2, 2]
/// parseList([[1, 2], 3]) -> Failure
/// parseList([[1, [2, 3]], [4, [5]]]) -> Failure
ParseResult parseList(SmallVectorImpl<int64_t> &dims);
/// Parse a literal that was printed as a hex string.
ParseResult parseHexElements();
Parser &p;
/// The shape inferred from the parsed elements.
SmallVector<int64_t, 4> shape;
/// Storage used when parsing elements, this is a pair of <is_negated, token>.
std::vector<std::pair<bool, Token>> storage;
/// Storage used when parsing elements that were stored as hex values.
Optional<Token> hexStorage;
};
} // namespace
/// Parse the elements of a tensor literal. If 'allowHex' is true, the parser
/// may also parse a tensor literal that is store as a hex string.
ParseResult TensorLiteralParser::parse(bool allowHex) {
// If hex is allowed, check for a string literal.
if (allowHex && p.getToken().is(Token::string)) {
hexStorage = p.getToken();
p.consumeToken(Token::string);
return success();
}
// Otherwise, parse a list or an individual element.
if (p.getToken().is(Token::l_square))
return parseList(shape);
return parseElement();
}
/// Build a dense attribute instance with the parsed elements and the given
/// shaped type.
DenseElementsAttr TensorLiteralParser::getAttr(llvm::SMLoc loc,
ShapedType type) {
Type eltType = type.getElementType();
// Check to see if we parse the literal from a hex string.
if (hexStorage.hasValue() &&
(eltType.isIntOrIndexOrFloat() || eltType.isa<ComplexType>()))
return getHexAttr(loc, type);
// Check that the parsed storage size has the same number of elements to the
// type, or is a known splat.
if (!shape.empty() && getShape() != type.getShape()) {
p.emitError(loc) << "inferred shape of elements literal ([" << getShape()
<< "]) does not match type ([" << type.getShape() << "])";
return nullptr;
}
// Handle the case where no elements were parsed.
if (!hexStorage.hasValue() && storage.empty() && type.getNumElements()) {
p.emitError(loc) << "parsed zero elements, but type (" << type
<< ") expected at least 1";
return nullptr;
}
// Handle complex types in the specific element type cases below.
bool isComplex = false;
if (ComplexType complexTy = eltType.dyn_cast<ComplexType>()) {
eltType = complexTy.getElementType();
isComplex = true;
}
// Handle integer and index types.
if (eltType.isIntOrIndex()) {
std::vector<APInt> intValues;
if (failed(getIntAttrElements(loc, eltType, intValues)))
return nullptr;
if (isComplex) {
// If this is a complex, treat the parsed values as complex values.
auto complexData = llvm::makeArrayRef(
reinterpret_cast<std::complex<APInt> *>(intValues.data()),
intValues.size() / 2);
return DenseElementsAttr::get(type, complexData);
}
return DenseElementsAttr::get(type, intValues);
}
// Handle floating point types.
if (FloatType floatTy = eltType.dyn_cast<FloatType>()) {
std::vector<APFloat> floatValues;
if (failed(getFloatAttrElements(loc, floatTy, floatValues)))
return nullptr;
if (isComplex) {
// If this is a complex, treat the parsed values as complex values.
auto complexData = llvm::makeArrayRef(
reinterpret_cast<std::complex<APFloat> *>(floatValues.data()),
floatValues.size() / 2);
return DenseElementsAttr::get(type, complexData);
}
return DenseElementsAttr::get(type, floatValues);
}
// Other types are assumed to be string representations.
return getStringAttr(loc, type, type.getElementType());
}
/// Build a Dense Integer attribute for the given type.
ParseResult
TensorLiteralParser::getIntAttrElements(llvm::SMLoc loc, Type eltTy,
std::vector<APInt> &intValues) {
intValues.reserve(storage.size());
bool isUintType = eltTy.isUnsignedInteger();
for (const auto &signAndToken : storage) {
bool isNegative = signAndToken.first;
const Token &token = signAndToken.second;
auto tokenLoc = token.getLoc();
if (isNegative && isUintType) {
return p.emitError(tokenLoc)
<< "expected unsigned integer elements, but parsed negative value";
}
// Check to see if floating point values were parsed.
if (token.is(Token::floatliteral)) {
return p.emitError(tokenLoc)
<< "expected integer elements, but parsed floating-point";
}
assert(token.isAny(Token::integer, Token::kw_true, Token::kw_false) &&
"unexpected token type");
if (token.isAny(Token::kw_true, Token::kw_false)) {
if (!eltTy.isInteger(1)) {
return p.emitError(tokenLoc)
<< "expected i1 type for 'true' or 'false' values";
}
APInt apInt(1, token.is(Token::kw_true), /*isSigned=*/false);
intValues.push_back(apInt);
continue;
}
// Create APInt values for each element with the correct bitwidth.
Optional<APInt> apInt =
buildAttributeAPInt(eltTy, isNegative, token.getSpelling());
if (!apInt)
return p.emitError(tokenLoc, "integer constant out of range for type");
intValues.push_back(*apInt);
}
return success();
}
/// Build a Dense Float attribute for the given type.
ParseResult
TensorLiteralParser::getFloatAttrElements(llvm::SMLoc loc, FloatType eltTy,
std::vector<APFloat> &floatValues) {
floatValues.reserve(storage.size());
for (const auto &signAndToken : storage) {
bool isNegative = signAndToken.first;
const Token &token = signAndToken.second;
// Handle hexadecimal float literals.
if (token.is(Token::integer) && token.getSpelling().startswith("0x")) {
Optional<APFloat> result;
if (failed(p.parseFloatFromIntegerLiteral(result, token, isNegative,
eltTy.getFloatSemantics(),
eltTy.getWidth())))
return failure();
floatValues.push_back(*result);
continue;
}
// Check to see if any decimal integers or booleans were parsed.
if (!token.is(Token::floatliteral))
return p.emitError()
<< "expected floating-point elements, but parsed integer";
// Build the float values from tokens.
auto val = token.getFloatingPointValue();
if (!val.hasValue())
return p.emitError("floating point value too large for attribute");
APFloat apVal(isNegative ? -*val : *val);
if (!eltTy.isF64()) {
bool unused;
apVal.convert(eltTy.getFloatSemantics(), APFloat::rmNearestTiesToEven,
&unused);
}
floatValues.push_back(apVal);
}
return success();
}
/// Build a Dense String attribute for the given type.
DenseElementsAttr TensorLiteralParser::getStringAttr(llvm::SMLoc loc,
ShapedType type,
Type eltTy) {
if (hexStorage.hasValue()) {
auto stringValue = hexStorage.getValue().getStringValue();
return DenseStringElementsAttr::get(type, {stringValue});
}
std::vector<std::string> stringValues;
std::vector<StringRef> stringRefValues;
stringValues.reserve(storage.size());
stringRefValues.reserve(storage.size());
for (auto val : storage) {
stringValues.push_back(val.second.getStringValue());
stringRefValues.emplace_back(stringValues.back());
}
return DenseStringElementsAttr::get(type, stringRefValues);
}
/// Build a Dense attribute with hex data for the given type.
DenseElementsAttr TensorLiteralParser::getHexAttr(llvm::SMLoc loc,
ShapedType type) {
Type elementType = type.getElementType();
if (!elementType.isIntOrIndexOrFloat() && !elementType.isa<ComplexType>()) {
p.emitError(loc)
<< "expected floating-point, integer, or complex element type, got "
<< elementType;
return nullptr;
}
std::string data;
if (parseElementAttrHexValues(p, hexStorage.getValue(), data))
return nullptr;
ArrayRef<char> rawData(data.data(), data.size());
bool detectedSplat = false;
if (!DenseElementsAttr::isValidRawBuffer(type, rawData, detectedSplat)) {
p.emitError(loc) << "elements hex data size is invalid for provided type: "
<< type;
return nullptr;
}
if (llvm::support::endian::system_endianness() ==
llvm::support::endianness::big) {
// Convert endianess in big-endian(BE) machines. `rawData` is
// little-endian(LE) because HEX in raw data of dense element attribute
// is always LE format. It is converted into BE here to be used in BE
// machines.
SmallVector<char, 64> outDataVec(rawData.size());
MutableArrayRef<char> convRawData(outDataVec);
DenseIntOrFPElementsAttr::convertEndianOfArrayRefForBEmachine(
rawData, convRawData, type);
return DenseElementsAttr::getFromRawBuffer(type, convRawData,
detectedSplat);
}
return DenseElementsAttr::getFromRawBuffer(type, rawData, detectedSplat);
}
ParseResult TensorLiteralParser::parseElement() {
switch (p.getToken().getKind()) {
// Parse a boolean element.
case Token::kw_true:
case Token::kw_false:
case Token::floatliteral:
case Token::integer:
storage.emplace_back(/*isNegative=*/false, p.getToken());
p.consumeToken();
break;
// Parse a signed integer or a negative floating-point element.
case Token::minus:
p.consumeToken(Token::minus);
if (!p.getToken().isAny(Token::floatliteral, Token::integer))
return p.emitError("expected integer or floating point literal");
storage.emplace_back(/*isNegative=*/true, p.getToken());
p.consumeToken();
break;
case Token::string:
storage.emplace_back(/*isNegative=*/false, p.getToken());
p.consumeToken();
break;
// Parse a complex element of the form '(' element ',' element ')'.
case Token::l_paren:
p.consumeToken(Token::l_paren);
if (parseElement() ||
p.parseToken(Token::comma, "expected ',' between complex elements") ||
parseElement() ||
p.parseToken(Token::r_paren, "expected ')' after complex elements"))
return failure();
break;
default:
return p.emitError("expected element literal of primitive type");
}
return success();
}
/// Parse a list of either lists or elements, returning the dimensions of the
/// parsed sub-tensors in dims. For example:
/// parseList([1, 2, 3]) -> Success, [3]
/// parseList([[1, 2], [3, 4]]) -> Success, [2, 2]
/// parseList([[1, 2], 3]) -> Failure
/// parseList([[1, [2, 3]], [4, [5]]]) -> Failure
ParseResult TensorLiteralParser::parseList(SmallVectorImpl<int64_t> &dims) {
auto checkDims = [&](const SmallVectorImpl<int64_t> &prevDims,
const SmallVectorImpl<int64_t> &newDims) -> ParseResult {
if (prevDims == newDims)
return success();
return p.emitError("tensor literal is invalid; ranks are not consistent "
"between elements");
};
bool first = true;
SmallVector<int64_t, 4> newDims;
unsigned size = 0;
auto parseOneElement = [&]() -> ParseResult {
SmallVector<int64_t, 4> thisDims;
if (p.getToken().getKind() == Token::l_square) {
if (parseList(thisDims))
return failure();
} else if (parseElement()) {
return failure();
}
++size;
if (!first)
return checkDims(newDims, thisDims);
newDims = thisDims;
first = false;
return success();
};
if (p.parseCommaSeparatedList(Parser::Delimiter::Square, parseOneElement))
return failure();
// Return the sublists' dimensions with 'size' prepended.
dims.clear();
dims.push_back(size);
dims.append(newDims.begin(), newDims.end());
return success();
}
//===----------------------------------------------------------------------===//
// ElementsAttr Parser
//===----------------------------------------------------------------------===//
/// Parse a dense elements attribute.
Attribute Parser::parseDenseElementsAttr(Type attrType) {
auto attribLoc = getToken().getLoc();
consumeToken(Token::kw_dense);
if (parseToken(Token::less, "expected '<' after 'dense'"))
return nullptr;
// Parse the literal data if necessary.
TensorLiteralParser literalParser(*this);
if (!consumeIf(Token::greater)) {
if (literalParser.parse(/*allowHex=*/true) ||
parseToken(Token::greater, "expected '>'"))
return nullptr;
}
// If the type is specified `parseElementsLiteralType` will not parse a type.
// Use the attribute location as the location for error reporting in that
// case.
auto loc = attrType ? attribLoc : getToken().getLoc();
auto type = parseElementsLiteralType(attrType);
if (!type)
return nullptr;
return literalParser.getAttr(loc, type);
}
/// Parse an opaque elements attribute.
Attribute Parser::parseOpaqueElementsAttr(Type attrType) {
consumeToken(Token::kw_opaque);
if (parseToken(Token::less, "expected '<' after 'opaque'"))
return nullptr;
if (getToken().isNot(Token::string))
return (emitError("expected dialect namespace"), nullptr);
std::string name = getToken().getStringValue();
consumeToken(Token::string);
if (parseToken(Token::comma, "expected ','"))
return nullptr;
Token hexTok = getToken();
if (parseToken(Token::string, "elements hex string should start with '0x'") ||
parseToken(Token::greater, "expected '>'"))
return nullptr;
auto type = parseElementsLiteralType(attrType);
if (!type)
return nullptr;
std::string data;
if (parseElementAttrHexValues(*this, hexTok, data))
return nullptr;
return OpaqueElementsAttr::get(builder.getStringAttr(name), type, data);
}
/// Shaped type for elements attribute.
///
/// elements-literal-type ::= vector-type | ranked-tensor-type
///
/// This method also checks the type has static shape.
ShapedType Parser::parseElementsLiteralType(Type type) {
// If the user didn't provide a type, parse the colon type for the literal.
if (!type) {
if (parseToken(Token::colon, "expected ':'"))
return nullptr;
if (!(type = parseType()))
return nullptr;
}
if (!type.isa<RankedTensorType, VectorType>()) {
emitError("elements literal must be a ranked tensor or vector type");
return nullptr;
}
auto sType = type.cast<ShapedType>();
if (!sType.hasStaticShape())
return (emitError("elements literal type must have static shape"), nullptr);
return sType;
}
/// Parse a sparse elements attribute.
Attribute Parser::parseSparseElementsAttr(Type attrType) {
llvm::SMLoc loc = getToken().getLoc();
consumeToken(Token::kw_sparse);
if (parseToken(Token::less, "Expected '<' after 'sparse'"))
return nullptr;
// Check for the case where all elements are sparse. The indices are
// represented by a 2-dimensional shape where the second dimension is the rank
// of the type.
Type indiceEltType = builder.getIntegerType(64);
if (consumeIf(Token::greater)) {
ShapedType type = parseElementsLiteralType(attrType);
if (!type)
return nullptr;
// Construct the sparse elements attr using zero element indice/value
// attributes.
ShapedType indicesType =
RankedTensorType::get({0, type.getRank()}, indiceEltType);
ShapedType valuesType = RankedTensorType::get({0}, type.getElementType());
return getChecked<SparseElementsAttr>(
loc, type, DenseElementsAttr::get(indicesType, ArrayRef<Attribute>()),
DenseElementsAttr::get(valuesType, ArrayRef<Attribute>()));
}
/// Parse the indices. We don't allow hex values here as we may need to use
/// the inferred shape.
auto indicesLoc = getToken().getLoc();
TensorLiteralParser indiceParser(*this);
if (indiceParser.parse(/*allowHex=*/false))
return nullptr;
if (parseToken(Token::comma, "expected ','"))
return nullptr;
/// Parse the values.
auto valuesLoc = getToken().getLoc();
TensorLiteralParser valuesParser(*this);
if (valuesParser.parse(/*allowHex=*/true))
return nullptr;
if (parseToken(Token::greater, "expected '>'"))
return nullptr;
auto type = parseElementsLiteralType(attrType);
if (!type)
return nullptr;
// If the indices are a splat, i.e. the literal parser parsed an element and
// not a list, we set the shape explicitly. The indices are represented by a
// 2-dimensional shape where the second dimension is the rank of the type.
// Given that the parsed indices is a splat, we know that we only have one
// indice and thus one for the first dimension.
ShapedType indicesType;
if (indiceParser.getShape().empty()) {
indicesType = RankedTensorType::get({1, type.getRank()}, indiceEltType);
} else {
// Otherwise, set the shape to the one parsed by the literal parser.
indicesType = RankedTensorType::get(indiceParser.getShape(), indiceEltType);
}
auto indices = indiceParser.getAttr(indicesLoc, indicesType);
// If the values are a splat, set the shape explicitly based on the number of
// indices. The number of indices is encoded in the first dimension of the
// indice shape type.
auto valuesEltType = type.getElementType();
ShapedType valuesType =
valuesParser.getShape().empty()
? RankedTensorType::get({indicesType.getDimSize(0)}, valuesEltType)
: RankedTensorType::get(valuesParser.getShape(), valuesEltType);
auto values = valuesParser.getAttr(valuesLoc, valuesType);
// Build the sparse elements attribute by the indices and values.
return getChecked<SparseElementsAttr>(loc, type, indices, values);
}