This PR adds `f8E8M0FNU` type to MLIR.
`f8E8M0FNU` type is proposed in [OpenCompute MX
Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf).
It defines a 8-bit floating point number with bit layout S0E8M0. Unlike
IEEE-754 types, there are no infinity, denormals, zeros or negative
values.
```c
f8E8M0FNU
- Exponent bias: 127
- Maximum stored exponent value: 254 (binary 1111'1110)
- Maximum unbiased exponent value: 254 - 127 = 127
- Minimum stored exponent value: 0 (binary 0000'0000)
- Minimum unbiased exponent value: 0 − 127 = -127
- Doesn't have zero
- Doesn't have infinity
- NaN is encoded as binary 1111'1111
Additional details:
- Zeros cannot be represented
- Negative values cannot be represented
- Mantissa is always 1
```
Related PRs:
- [PR-107127](https://github.com/llvm/llvm-project/pull/107127)
[APFloat] Add APFloat support for E8M0 type
- [PR-105573](https://github.com/llvm/llvm-project/pull/105573) [MLIR]
Add f6E3M2FN type - was used as a template for this PR
- [PR-107999](https://github.com/llvm/llvm-project/pull/107999) [MLIR]
Add f6E2M3FN type
- [PR-108877](https://github.com/llvm/llvm-project/pull/108877) [MLIR]
Add f4E2M1FN type
This patch adds the capability to define dialect-specific location
attrs. This is useful in particular for defining location structure that
doesn't necessarily fit within the core MLIR location hierarchy, but
doesn't make sense to push upstream (i.e. a custom use case).
This patch adds an AttributeTrait, `IsLocation`, which is tagged onto
all the builtin location attrs, as well as the test location attribute.
This is necessary because previously LocationAttr::classof only returned
true if the attribute was one of the builtin location attributes, and
well, the point of this patch is to allow dialects to define their own
location attributes.
There was an alternate implementation I considered wherein LocationAttr
becomes an AttrInterface, but that was discarded because there are
likely to be *many* locations in a single program, and I was concerned
that forcing every MLIR user to pay the cost of the additional
lookup/dispatch was unacceptable. It also would have been a *much* more
invasive change. It would have allowed for more flexibility in terms of
pretty printing, but it's unclear how useful/necessary that flexibility
would be given how much customizability there already is for attribute
definitions.
This PR adds `f4E2M1FN` type to mlir.
`f4E2M1FN` type is proposed in [OpenCompute MX
Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf).
It defines a 4-bit floating point number with bit layout S1E2M1. Unlike
IEEE-754 types, there are no infinity or NaN values.
```c
f4E2M1FN
- Exponent bias: 1
- Maximum stored exponent value: 3 (binary 11)
- Maximum unbiased exponent value: 3 - 1 = 2
- Minimum stored exponent value: 1 (binary 01)
- Minimum unbiased exponent value: 1 − 1 = 0
- Has Positive and Negative zero
- Doesn't have infinity
- Doesn't have NaNs
Additional details:
- Zeros (+/-): S.00.0
- Max normal number: S.11.1 = ±2^(2) x (1 + 0.5) = ±6.0
- Min normal number: S.01.0 = ±2^(0) = ±1.0
- Min subnormal number: S.00.1 = ±2^(0) x 0.5 = ±0.5
```
Related PRs:
- [PR-95392](https://github.com/llvm/llvm-project/pull/95392) [APFloat]
Add APFloat support for FP4 data type
- [PR-105573](https://github.com/llvm/llvm-project/pull/105573) [MLIR]
Add f6E3M2FN type - was used as a template for this PR
- [PR-107999](https://github.com/llvm/llvm-project/pull/107999) [MLIR]
Add f6E2M3FN type
This PR adds `f6E2M3FN` type to mlir.
`f6E2M3FN` type is proposed in [OpenCompute MX
Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf).
It defines a 6-bit floating point number with bit layout S1E2M3. Unlike
IEEE-754 types, there are no infinity or NaN values.
```c
f6E2M3FN
- Exponent bias: 1
- Maximum stored exponent value: 3 (binary 11)
- Maximum unbiased exponent value: 3 - 1 = 2
- Minimum stored exponent value: 1 (binary 01)
- Minimum unbiased exponent value: 1 − 1 = 0
- Has Positive and Negative zero
- Doesn't have infinity
- Doesn't have NaNs
Additional details:
- Zeros (+/-): S.00.000
- Max normal number: S.11.111 = ±2^(2) x (1 + 0.875) = ±7.5
- Min normal number: S.01.000 = ±2^(0) = ±1.0
- Max subnormal number: S.00.111 = ±2^(0) x 0.875 = ±0.875
- Min subnormal number: S.00.001 = ±2^(0) x 0.125 = ±0.125
```
Related PRs:
- [PR-94735](https://github.com/llvm/llvm-project/pull/94735) [APFloat]
Add APFloat support for FP6 data types
- [PR-105573](https://github.com/llvm/llvm-project/pull/105573) [MLIR]
Add f6E3M2FN type - was used as a template for this PR
'std::string detailData' is moved in the innermost loop of a 2-layer
loop, but is written to throughout the whole duration of the 2-layer
loop.
After move, std::string is in an unspecified state
(implementation-dependent).
Avoid using a moved value, as it incurs undefined behavior.
* Strip calls to raw_string_ostream::flush(), which is essentially a no-op
* Strip unneeded calls to raw_string_ostream::str(), to avoid excess indirection.
This PR adds `f6E3M2FN` type to mlir.
`f6E3M2FN` type is proposed in [OpenCompute MX
Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf).
It defines a 6-bit floating point number with bit layout S1E3M2. Unlike
IEEE-754 types, there are no infinity or NaN values.
```c
f6E3M2FN
- Exponent bias: 3
- Maximum stored exponent value: 7 (binary 111)
- Maximum unbiased exponent value: 7 - 3 = 4
- Minimum stored exponent value: 1 (binary 001)
- Minimum unbiased exponent value: 1 − 3 = −2
- Has Positive and Negative zero
- Doesn't have infinity
- Doesn't have NaNs
Additional details:
- Zeros (+/-): S.000.00
- Max normal number: S.111.11 = ±2^(4) x (1 + 0.75) = ±28
- Min normal number: S.001.00 = ±2^(-2) = ±0.25
- Max subnormal number: S.000.11 = ±2^(-2) x 0.75 = ±0.1875
- Min subnormal number: S.000.01 = ±2^(-2) x 0.25 = ±0.0625
```
Related PRs:
- [PR-94735](https://github.com/llvm/llvm-project/pull/94735) [APFloat]
Add APFloat support for FP6 data types
- [PR-97118](https://github.com/llvm/llvm-project/pull/97118) [MLIR] Add
f8E4M3 type - was used as a template for this PR
This changes the function `resetToken` to not update `lastToken`.
The member `lastToken` is the last token that was consumed by the
parser.
Resetting the lexer position to a different position does not cause any
token to be consumed, so `lastToken` should not be updated.
Setting it to `curToken` can cause the scopeLoc.end location of
`OperationDefinition `to be off-by-one, pointing to the
first token after the operation.
An example for an operation for which the scopeLoc.end location was
wrong before is:
```
%0 = torch.vtensor.literal(dense_resource<__elided__> : tensor<768xbf16>) : !torch.vtensor<[768],bf16>
```
Here the scope end loc always pointed to the next token
This also adds a test for the Locations of `OperationDefinitions`.
Without the change to `resetToken` the test failes, with the scope end
location for `llvm.mlir.undef` pointing to the `func.return` in the next
line
Found while working on parser for custom expression type for my dialect.
Builtin `AffineExpr` uses low-level parser API which is not available
for external users.
#102326 enables verification of type parameters that are type
constraints. The element type verification for `VectorType` (and maybe
other builtin types in the future) can now be auto-generated.
Also remove redundant error checking in the vector type parser: element
type and dimensions are already checked by the verifier (which is called
from `getChecked`).
Depends on #102326.
This PR adds `f8E3M4` type to mlir.
`f8E3M4` type follows IEEE 754 convention
```c
f8E3M4 (IEEE 754)
- Exponent bias: 3
- Maximum stored exponent value: 6 (binary 110)
- Maximum unbiased exponent value: 6 - 3 = 3
- Minimum stored exponent value: 1 (binary 001)
- Minimum unbiased exponent value: 1 − 3 = −2
- Precision specifies the total number of bits used for the significand (mantissa),
including implicit leading integer bit = 4 + 1 = 5
- Follows IEEE 754 conventions for representation of special values
- Has Positive and Negative zero
- Has Positive and Negative infinity
- Has NaNs
Additional details:
- Max exp (unbiased): 3
- Min exp (unbiased): -2
- Infinities (+/-): S.111.0000
- Zeros (+/-): S.000.0000
- NaNs: S.111.{0,1}⁴ except S.111.0000
- Max normal number: S.110.1111 = +/-2^(6-3) x (1 + 15/16) = +/-2^3 x 31 x 2^(-4) = +/-15.5
- Min normal number: S.001.0000 = +/-2^(1-3) x (1 + 0) = +/-2^(-2)
- Max subnormal number: S.000.1111 = +/-2^(-2) x 15/16 = +/-2^(-2) x 15 x 2^(-4) = +/-15 x 2^(-6)
- Min subnormal number: S.000.0001 = +/-2^(-2) x 1/16 = +/-2^(-2) x 2^(-4) = +/-2^(-6)
```
Related PRs:
- [PR-99698](https://github.com/llvm/llvm-project/pull/99698) [APFloat]
Add support for f8E3M4 IEEE 754 type
- [PR-97118](https://github.com/llvm/llvm-project/pull/97118) [MLIR] Add
f8E4M3 IEEE 754 type
An attribute parser needs to parse lists of possibly negative integers
separated by x in a way which is foiled by parseInteger handling hex
formats and parseIntegerInDimensionList does not allow negatives.
---------
Co-authored-by: Jacques Pienaar <jpienaar@google.com>
This PR adds `f8E4M3` type to mlir.
`f8E4M3` type follows IEEE 754 convention
```c
f8E4M3 (IEEE 754)
- Exponent bias: 7
- Maximum stored exponent value: 14 (binary 1110)
- Maximum unbiased exponent value: 14 - 7 = 7
- Minimum stored exponent value: 1 (binary 0001)
- Minimum unbiased exponent value: 1 − 7 = −6
- Precision specifies the total number of bits used for the significand (mantisa),
including implicit leading integer bit = 3 + 1 = 4
- Follows IEEE 754 conventions for representation of special values
- Has Positive and Negative zero
- Has Positive and Negative infinity
- Has NaNs
Additional details:
- Max exp (unbiased): 7
- Min exp (unbiased): -6
- Infinities (+/-): S.1111.000
- Zeros (+/-): S.0000.000
- NaNs: S.1111.{001, 010, 011, 100, 101, 110, 111}
- Max normal number: S.1110.111 = +/-2^(7) x (1 + 0.875) = +/-240
- Min normal number: S.0001.000 = +/-2^(-6)
- Max subnormal number: S.0000.111 = +/-2^(-6) x 0.875 = +/-2^(-9) x 7
- Min subnormal number: S.0000.001 = +/-2^(-6) x 0.125 = +/-2^(-9)
```
Related PRs:
- [PR-97179](https://github.com/llvm/llvm-project/pull/97179) [APFloat]
Add support for f8E4M3 IEEE 754 type
Parsing support for floating point types was missing a few features:
1. Parsing floating point attributes from integer literals was supported
only for types with bitwidth smaller or equal to 64.
2. Downstream users could not use `AsmParser::parseFloat` to parse float
types which are printed as integer literals.
This commit addresses both these points. It extends
`Parser::parseFloatFromIntegerLiteral` to support arbitrary bitwidth,
and exposes a new API to parse arbitrary floating point given an
fltSemantics as input. The usage of this new API is introduced in the
Test Dialect.
Store the last token parsed in the parser state so that the range parsed
can utilize its end rather than the start of the token after parsed.
This results in a tighter range (especially true in the case of
comments, see
```mlir
|%c4 = arith.constant 4 : index
// Foo
|
```
vs
```mlir
|%c4 = arith.constant 4 : index|
```
).
Discovered while working on a little textual post processing tool.
This patch replaces uses of StringRef::{starts,ends}with with
StringRef::{starts,ends}_with for consistency with
std::{string,string_view}::{starts,ends}_with in C++20.
I'm planning to deprecate and eventually remove
StringRef::{starts,ends}with.
system_endianness() just returns llvm::endianness::native, a
compile-time constant equivalent to std::native in C++20. This patch
deprecates system_endianness() while replacing all invocations of
system_endianness() with llvm::endianness::native.
While we are at it, this patch replaces
llvm::support::endianness::{big,little} with
llvm::endianness::{big,little} in those statements that happen to call
system_endianness(). It does not go out of its way to replace other
occurrences of llvm::support::endianness::{big,little}.
This is a follow-up to 8c2bff1ab9 which lazy-initialized the
diagnostic and removed the need to dynamically abandon() an
InFlightDiagnostic. This further simplifies the code to not needed to
return a reference to an InFlightDiagnostic and instead eagerly emit
errors.
Also use `emitError` as name instead of `getDiag` which seems more
explicit and in-line with the common usage.
Printing cyclic attributes and types currently has no first-class
support within the AsmPrinter and AsmParser. The workaround for this
issue used in all mutable attributes and types upstream has been to
create a `thread_local static SetVector` keeping track of currently
parsed and printed attributes.
This solution is not ideal readability wise due to the use of globals
and keeping track of state. Worst of all, this pattern had to be
reimplemented for every mutable attribute and type.
This patch therefore adds support for this pattern in `AsmPrinter` and
`AsmParser` replacing the use of this pattern. By calling
`tryStartCyclingPrint/Parse`, the mutable attribute or type are
registered in an internal stack. All subsequent calls to the function
with the same attribute or type will lead to returning failure. This way
the nesting can be detected and a short form printed or parsed instead.
Through the resetter returned by the call, the cyclic printing or
parsing region automatically ends on return.
This wires in attribute and type aliases into the MLIR LSP server. This
will allow goto definition and find references on attribute and type
references, which should make debugging locations and other metadata
easier.
Depends on D158781
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D158782
This adds fields to AsmParserState to track attribute and type alias
definitions and uses and teachers the parser to inform the
AsmParserState about them. This will be used to add LSP support for goto
definition and find references for aliases.
Attribute aliases are tolerant to use before def, because certain
location aliases may be deferred.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D158781
In cases where memory is of less of a concern (e.g. small attributes where all instances have to be distinct by definition), using `DistinctAttr` with a unit attribute is a useful and conscious way of generating deterministic unique IDs.
The syntax as is however, makes them less useful to use, as it 1) always prints `<unit>` at the back and 2) always aliases them leading to not very useful `#distinct = distinct[n]<unit>` lines in the printer output.
This patch fixes that by special casing `UnitAttr` to simply elide the `unit` attribute in the back and not printing it as alias in that case.
Differential Revision: https://reviews.llvm.org/D155162
A distinct attribute associates a referenced attribute with a unique
identifier. Every call to its create function allocates a new
distinct attribute instance. The address of the attribute instance
temporarily serves as its unique identifier. Similar to the names
of SSA values, the final unique identifiers are generated during
pretty printing.
Examples:
#distinct = distinct[0]<42.0 : f32>
#distinct1 = distinct[1]<42.0 : f32>
#distinct2 = distinct[2]<array<i32: 10, 42>>
This mechanism is meant to generate attributes with a unique
identifier, which can be used to mark groups of operations
that share a common properties such as if they are aliasing.
The design of the distinct attribute ensures minimal memory
footprint per distinct attribute since it only contains a reference
to another attribute. All distinct attributes are stored outside of
the storage uniquer in a thread local store that is part of the
context. It uses one bump pointer allocator per thread to ensure
distinct attributes can be created in-parallel.
Reviewed By: rriddle, Dinistro, zero9178
Differential Revision: https://reviews.llvm.org/D153360
The methods added by D154177 don't require the `symbolSet` parameter to be mutable nor to have the `SmallVectorImpl` type, so this commit changes them to accept `ArrayRef` instead: both for generality, and to make the non-mutation an explicit part of the API.
Reviewed By: aartbik, Peiming
Differential Revision: https://reviews.llvm.org/D154751
Similar to AffineMap and IntegerSet parsing, this change makes the more fine-grained AffineExpr available for general parsing, using a preset symbol set to recognize variables.
Motivation:
The AffineExpr parser will be used by the new sparse tensor encoding surface syntax. Originally, we planned to duplicate the affine parser completely, but that would be a terrible waste of a good thing. With this minor API change, we prepare the way for the sparse tensor dialect (and others) to reuse the AffineExpr parser outside the context of a more restricted AffineMap parser.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D154177
This revision fixes a typo, where printIntegerSet() was used where it should have been parseIntegerSet().It also removes a dangling getDimsAndSymbolSSAIds() declaration that is never used.
Differential Revision: https://reviews.llvm.org/D154179
At the moment, only the trailing dimensions in the vector type can be
scalable, i.e. this is supported:
vector<2x[4]xf32>
and this is not allowed:
vector<[2]x4xf32>
This patch extends the vector type so that arbitrary dimensions can be
scalable. To this end, an array of bool values is added to every vector
type to denote whether the corresponding dimensions are scalable or not.
For example, for this vector:
vector<[2]x[3]x4xf32>
the following array would be created:
{true, true, false}.
Additionally, the current syntax:
vector<[2x3]x4xf32>
is replaced with:
vector<[2]x[3]x4xf32>
This is primarily to simplify parsing (this way, the parser can easily
process one dimension at a time rather than e.g. tracking whether
"scalable block" has been entered/left).
NOTE: The `isScalableDim` parameter of `VectorType` (introduced in this
patch) makes `numScalableDims` redundant. For the time being,
`numScalableDims` is preserved to facilitate the transition between the
two parameters. `numScalableDims` will be removed in one of the
subsequent patches.
This change is a part of a larger effort to enable scalable
vectorisation in Linalg. See this RFC for more context:
* https://discourse.llvm.org/t/rfc-scalable-vectorisation-in-linalg/
Differential Revision: https://reviews.llvm.org/D153372
The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.
Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.
Context:
- https://mlir.llvm.org/deprecation/ at "Use the free function variants
for dyn_cast/cast/isa/…"
- Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443
Implementation:
This patch updates all remaining uses of the deprecated functionality in
mlir/. This was done with clang-tidy as described below and further
modifications to GPUBase.td and OpenMPOpsInterfaces.td.
Steps are described per line, as comments are removed by git:
0. Retrieve the change from the following to build clang-tidy with an
additional check:
main...tpopp:llvm-project:tidy-cast-check
1. Build clang-tidy
2. Run clang-tidy over your entire codebase while disabling all checks
and enabling the one relevant one. Run on all header files also.
3. Delete .inc files that were also modified, so the next build rebuilds
them to a pure state.
```
ninja -C $BUILD_DIR clang-tidy
run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
-header-filter=mlir/ mlir/* -fix
rm -rf $BUILD_DIR/tools/mlir/**/*.inc
```
Differential Revision: https://reviews.llvm.org/D151542
The bytecode reader didn't handle properly the case where resource names
conflicted and were renamed, leading to orphan handles in the IR as well
as overwriting the exiting resources.
Differential Revision: https://reviews.llvm.org/D151408
The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.
Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.
Caveats include:
- This clang-tidy script probably has more problems.
- This only touches C++ code, so nothing that is being generated.
Context:
- https://mlir.llvm.org/deprecation/ at "Use the free function variants
for dyn_cast/cast/isa/…"
- Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443
Implementation:
This first patch was created with the following steps. The intention is
to only do automated changes at first, so I waste less time if it's
reverted, and so the first mass change is more clear as an example to
other teams that will need to follow similar steps.
Steps are described per line, as comments are removed by git:
0. Retrieve the change from the following to build clang-tidy with an
additional check:
https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
1. Build clang-tidy
2. Run clang-tidy over your entire codebase while disabling all checks
and enabling the one relevant one. Run on all header files also.
3. Delete .inc files that were also modified, so the next build rebuilds
them to a pure state.
4. Some changes have been deleted for the following reasons:
- Some files had a variable also named cast
- Some files had not included a header file that defines the cast
functions
- Some files are definitions of the classes that have the casting
methods, so the code still refers to the method instead of the
function without adding a prefix or removing the method declaration
at the same time.
```
ninja -C $BUILD_DIR clang-tidy
run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
-header-filter=mlir/ mlir/* -fix
rm -rf $BUILD_DIR/tools/mlir/**/*.inc
git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\
mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\
mlir/lib/**/IR/\
mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\
mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\
mlir/test/lib/Dialect/Test/TestTypes.cpp\
mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\
mlir/test/lib/Dialect/Test/TestAttributes.cpp\
mlir/unittests/TableGen/EnumsGenTest.cpp\
mlir/test/python/lib/PythonTestCAPI.cpp\
mlir/include/mlir/IR/
```
Differential Revision: https://reviews.llvm.org/D150123
This new features enabled to dedicate custom storage inline within operations.
This storage can be used as an alternative to attributes to store data that is
specific to an operation. Attribute can also be stored inside the properties
storage if desired, but any kind of data can be present as well. This offers
a way to store and mutate data without uniquing in the Context like Attribute.
See the OpPropertiesTest.cpp for an example where a struct with a
std::vector<> is attached to an operation and mutated in-place:
struct TestProperties {
int a = -1;
float b = -1.;
std::vector<int64_t> array = {-33};
};
More complex scheme (including reference-counting) are also possible.
The only constraint to enable storing a C++ object as "properties" on an
operation is to implement three functions:
- convert from the candidate object to an Attribute
- convert from the Attribute to the candidate object
- hash the object
Optional the parsing and printing can also be customized with 2 extra
functions.
A new options is introduced to ODS to allow dialects to specify:
let usePropertiesForAttributes = 1;
When set to true, the inherent attributes for all the ops in this dialect
will be using properties instead of being stored alongside discardable
attributes.
The TestDialect showcases this feature.
Another change is that we introduce new APIs on the Operation class
to access separately the inherent attributes from the discardable ones.
We envision deprecating and removing the `getAttr()`, `getAttrsDictionary()`,
and other similar method which don't make the distinction explicit, leading
to an entirely separate namespace for discardable attributes.
Recommit d572cd1b06 after fixing python bindings build.
Differential Revision: https://reviews.llvm.org/D141742
This new features enabled to dedicate custom storage inline within operations.
This storage can be used as an alternative to attributes to store data that is
specific to an operation. Attribute can also be stored inside the properties
storage if desired, but any kind of data can be present as well. This offers
a way to store and mutate data without uniquing in the Context like Attribute.
See the OpPropertiesTest.cpp for an example where a struct with a
std::vector<> is attached to an operation and mutated in-place:
struct TestProperties {
int a = -1;
float b = -1.;
std::vector<int64_t> array = {-33};
};
More complex scheme (including reference-counting) are also possible.
The only constraint to enable storing a C++ object as "properties" on an
operation is to implement three functions:
- convert from the candidate object to an Attribute
- convert from the Attribute to the candidate object
- hash the object
Optional the parsing and printing can also be customized with 2 extra
functions.
A new options is introduced to ODS to allow dialects to specify:
let usePropertiesForAttributes = 1;
When set to true, the inherent attributes for all the ops in this dialect
will be using properties instead of being stored alongside discardable
attributes.
The TestDialect showcases this feature.
Another change is that we introduce new APIs on the Operation class
to access separately the inherent attributes from the discardable ones.
We envision deprecating and removing the `getAttr()`, `getAttrsDictionary()`,
and other similar method which don't make the distinction explicit, leading
to an entirely separate namespace for discardable attributes.
Differential Revision: https://reviews.llvm.org/D141742
X. Sun et al. (https://dl.acm.org/doi/10.5555/3454287.3454728) published
a paper showing that an FP format with 4 bits of exponent, 3 bits of
significand and an exponent bias of 11 would work quite well for ML
applications.
Google hardware supports a variant of this format where 0x80 is used to
represent NaN, as in the Float8E4M3FNUZ format. Just like the
Float8E4M3FNUZ format, this format does not support -0 and values which
would map to it will become +0.
This format is proposed for inclusion in OpenXLA's StableHLO dialect: https://github.com/openxla/stablehlo/pull/1308
As part of inclusion in that dialect, APFloat needs to know how to
handle this format.
Differential Revision: https://reviews.llvm.org/D146441
`parseAttribute` and `parseType` require null-terminated strings as
input, but this isn't great considering the argument type is
`StringRef`. This changes them to copy to a null-terminated buffer by
default, with a `isKnownNullTerminated` flag added to disable the
copying.
closes#58964
Reviewed By: rriddle, kuhar, lattner
Differential Revision: https://reviews.llvm.org/D145182
Currently these functions report errors directly to stderr, this updates
them to use diagnostics instead. This also makes partially-consumed
strings an error if the `numRead` parameter isn't provided (the
docstrings already claimed this happened, but it didn't.)
While here I also tried to reduce the number of overloads by switching
to using default parameters.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D144804
