This change allows to expose through an interface attributes wrapping
content as external resources, and the usage inside the ModuleToObject
show how we will be able to provide runtime libraries without relying on
the filesystem.
Disabling memrefs with a stride of 0 was intended to prevent internal
aliasing, but this does not address all cases : internal aliasing can
still occur when the stride is less than the shape.
On the other hand, a stride of 0 can be very useful in certain
scenarios. For example, in architectures that support multi-dimensional
DMA, we can use memref::copy with a stride of 0 to achieve a broadcast
effect.
This commit removes the restriction that strides in memrefs cannot be 0.
It is possible to have a subview with a fully static size and a type
that matches the source type, but a dynamic offset that may be
different. However, currently the memref dialect folds:
```mlir
func.func @subview_of_static_full_size(
%arg0: memref<16x4xf32, strided<[4, 1], offset: ?>>, %idx: index)
-> memref<16x4xf32, strided<[4, 1], offset: ?>>
{
%0 = memref.subview %arg0[%idx, 0][16, 4][1, 1]
: memref<16x4xf32, strided<[4, 1], offset: ?>>
to memref<16x4xf32, strided<[4, 1], offset: ?>>
return %0 : memref<16x4xf32, strided<[4, 1], offset: ?>>
}
```
To:
```mlir
func.func @subview_of_static_full_size(
%arg0: memref<16x4xf32, strided<[4, 1], offset: ?>>, %arg1: index)
-> memref<16x4xf32, strided<[4, 1], offset: ?>>
{
return %arg0 : memref<16x4xf32, strided<[4, 1], offset: ?>>
}
```
Which drops the dynamic offset from the `subview` op.
I have run into assertion failures quite often when calling this method
via `DenseElementsAttr::get`, and I think this would help, at the very
least, by printing out the bit width size mismatches, rather than a
plain assertion failure. I included all the other cases in the method
for completeness
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}.
When building MLIR using bazel on windows with MSVC2019, bool splats
were being created incorrectly:
```
dense<[true,true,true,true]> : tensor<4xi1>
-(parse with mlir-opt)-> dense<[true, false, false, false]> : tensor<4xi1>
```
Appears that a Windows bazel build produces a corrupt DenseIntOrFPElementsAttr.
Unable to repro using MSVC and cmake.
Issue first discovered here:
https://github.com/google/jax/issues/16394
Added test point for reproduction:
```
$ bazel test @llvm-project//mlir/unittests:ir_tests --test_arg=--gtest_filter=DenseSplatTest.BoolSplatSmall
```
Differential Revision: https://reviews.llvm.org/D155745
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 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 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 follows a previous patch that updated calls
`op.cast<T>()-> cast<T>(op)`. However some cases could not handle an
unprefixed `cast` call due to occurrences of variables named cast, or
occurring inside of class definitions which would resolve to the method.
All C++ files that did not work automatically with `cast<T>()` are
updated here to `llvm::cast` and similar with the intention that they
can be easily updated after the methods are removed through a
find-replace.
See https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
for the clang-tidy check that is used and then update printed
occurrences of the function to include `llvm::` before.
One can then run the following:
```
ninja -C $BUILD_DIR clang-tidy
run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
-export-fixes /tmp/cast/casts.yaml mlir/*\
-header-filter=mlir/ -fix
rm -rf $BUILD_DIR/tools/mlir/**/*.inc
```
Differential Revision: https://reviews.llvm.org/D150348
This patch removes the implementation of TypedAttr and ElementsAttr
from DenseArrayAttr and, in doing so, removes the need store a shaped
type. The attribute now stores a size (number of elements), an MLIR type
as a discriminator, and a raw byte array.
The intent of DenseArrayAttr was not to be a drop-in replacement for DenseElementsAttr. It was meant to be a simple container of integers or floats that map to C++ types. The ElementsAttr implementation on DenseArrayAttr had many holes in it, and fixing those holes would require evolving DenseArrayAttr in a way that is incompatible with its original purpose.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D137606
This patch mechanically replaces None with std::nullopt where the
compiler would warn if None were deprecated. The intent is to reduce
the amount of manual work required in migrating from Optional to
std::optional.
This is part of an effort to migrate from llvm::Optional to
std::optional:
https://discourse.llvm.org/t/deprecating-llvm-optional-x-hasvalue-getvalue-getvalueor/63716
The KeyTy of attribute/type storage classes provide enough information for
automatically implementing the necessary sub element interface methods. This
removes the need for derived classes to do it themselves, which is both much
nicer and easier to handle certain invariants (e.g. null handling). In cases where
explicitly handling for parameter types is necessary, they can provide an implementation
of `AttrTypeSubElementHandler` to opt-in to support.
This tickles a few things alias wise, which annoyingly messes with tests that hard
code specific affine map numbers.
Differential Revision: https://reviews.llvm.org/D137374
Negative strides are useful for creating reverse-view of array. We don't have specific example for negative offset yet but will add it for consistency.
Differential Revision: https://reviews.llvm.org/D134147
Splat of bool is encoded as a byte with all-ones in it [1]. Without this
change, this piece of code:
auto xs = builder.getI32TensorAttr({42, 42, 42, 42});
auto xs2 = xs.mapValues(builder.getI1Type(), [](const llvm::APInt &x) {
return x.isZero() ? llvm::APInt::getZero(1) : llvm::APInt::getAllOnes(1);
});
xs2.dump();
Prints:
dense<[true, false, false, false]> : tensor<4xi1>
Because only the first bit is set. This applies to both
DenseIntElementsAttr::mapValues() and DenseFPElementsAttr::mapValues().
[1]: e877b42e2c/mlir/lib/IR/BuiltinAttributes.cpp (L984)
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D132767
This patch ensures that index integer attributes can only be
constructed with APInts whose widths are equal to the index
internal storage bitwidth (64).
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D133059
The previous implementation would still crash if the element type was
not iterable. This patch changes SparseElementsAttr to properly
implement `try_value_begin_impl` according to ElementsAttr and changes
DenseElementsAttr to implement `tryGetValues` as the basis for querying
element values.
Depends on D132904
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D132958
This patch changes `value_begin_impl` to a faillable
`try_value_begin_impl` so that specific cases can fail iteration if the
type doesn't match the internal storage.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D132904
This patch turns `DenseArrayBaseAttr` into a fully-functional attribute by
adding a generic parser and printer, supporting bool or integer and floating
point element types with bitwidths divisible by 8. It has been renamed
to `DenseArrayAttr`. The patch maintains the specialized subclasses,
e.g. `DenseI32ArrayAttr`, which remain the preferred API for accessing
elements in C++.
This allows `DenseArrayAttr` to hold signed and unsigned integer elements:
```
array<si8: -128, 127>
array<ui8: 255>
```
"Exotic" floating point elements:
```
array<bf16: 1.2, 3.4>
```
And integers of other bitwidths:
```
array<i24: 8388607>
```
Reviewed By: rriddle, lattner
Differential Revision: https://reviews.llvm.org/D132758
Introduce a new attribute to represent the strided memref layout. Strided
layouts are omnipresent in code generation flows and are the only kind of
layouts produced and supported by a half of operation in the memref dialect
(view-related, shape-related). However, they are internally represented as
affine maps that require a somewhat fragile extraction of the strides from the
linear form that also comes with an overhead. Furthermore, textual
representation of strided layouts as affine maps is difficult to read: compare
`affine_map<(d0, d1, d2)[s0, s1] -> (d0*32 + d1*s0 + s1 + d2)>` with
`strides: [32, ?, 1], offset: ?`. While a rudimentary support for parsing a
syntactically sugared version of the strided layout has existed in the codebase
for a long time, it does not go as far as this commit to make the strided
layout a first-class attribute in the IR.
This introduces the attribute and updates the tests that using the pre-existing
sugared form to use the new attribute instead. Most memref created
programmatically, e.g., in passes, still use the affine form with further
extraction of strides and will be updated separately.
Update and clean-up the memref type documentation that has gotten stale and has
been referring to the details of affine map composition that are long gone.
See https://discourse.llvm.org/t/rfc-materialize-strided-memref-layout-as-an-attribute/64211.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D132864
The element type enum is not needed to differentiate dense array kinds
because the element type of the shaped type can be used instead.
Reviewed By: mehdi_amini, rriddle
Differential Revision: https://reviews.llvm.org/D132535
This patch cleans up the definition of `DenseArrayAttrBase` by relying
more on ODS-generated methods. It also exposes an API for using the raw
data of a dense array, similar to `DenseIntOrFPElementsAttr::getRaw`.
Reviewed By: lattner, mehdi_amini
Differential Revision: https://reviews.llvm.org/D131450
This patch adds a DenseI1ArrayAttr to support arrays of i1. Importantly,
the implementation is as a simple `ArrayRef<bool>` instead of using bit
compression, which was problematic in DenseElementsAttr.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D130957
Previously, DenseArrayAttr used VectorType for its shaped type.
VectorType is problematic for arrays because it doesn't support zero
dimensions, meaning that an empty array would have `vector<i32>` as its
type. ElementsAttr would think that an empty dense array is size 1, not
0. This patch switches over to TensorType, which does support zero
dimensions.
Fixes#56860
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D130921
This attribute is technical debt from the early stages of MLIR, before
ElementsAttr was an interface and when it was more difficult for
dialects to define their own types of attributes. At present it isn't
used at all in tree (aside from being convenient for eliding other
ElementsAttr), and has had little to no evolution in the past three years.
Differential Revision: https://reviews.llvm.org/D129917
This attributes is intended cover the current set of use cases that abuse
DenseElementsAttr, e.g. when the data is large. Using resources for large
data is one of the major reasons why they were added; e.g. they can be
deallocated mid-compilation, they support a wide variety of data origins
(e.g, heap allocated, mmap'd, etc.), they can support mutation, etc.
I considered at length not having a builtin variant of this, and instead
having multiple versions of this attribute for dialects that are interested,
but they all boiled down to the exact same attribute definition. Given the
generality of this attribute, it feels more aligned to keep it next to DenseArrayAttr
(given that DenseArrayAttr covers the "small" case, and DenseResourcesElementsAttr
covers the "large" case). The underlying infra used to build this attribute is
general, and having a builtin attribute doesn't preclude users from defining
their own when it makes sense (they can even share a blob manager with the
builtin dialect to avoid data duplication).
Differential Revision: https://reviews.llvm.org/D130022
This patch removes the `type` field from `Attribute` along with the
`Attribute::getType` accessor.
Going forward, this means that attributes in MLIR will no longer have
types as a first-class concept. This patch lays the groundwork to
incrementally remove or refactor code that relies on generic attributes
being typed. The immediate impact will be on attributes that rely on
`Attribute` containing a type, such as `IntegerAttr`,
`DenseElementsAttr`, and `ml_program::ExternAttr`, which will now need
to define a type parameter on their storage classes. This will save
memory as all other attribute kinds will no longer contain a type.
Moreover, it will not be possible to generically query the type of an
attribute directly. This patch provides an attribute interface
`TypedAttr` that implements only one method, `getType`, which can be
used to generically query the types of attributes that implement the
interface. This interface can be used to retain the concept of a "typed
attribute". The ODS-generated accessor for a `type` parameter
automatically implements this method.
Next steps will be to refactor the assembly formats of certain operations
that rely on `parseAttribute(type)` and `printAttributeWithoutType` to
remove special handling of type elision until `type` can be removed from
the dialect parsing hook entirely; and incrementally remove uses of
`TypedAttr`.
Reviewed By: lattner, rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D130092
The current support was essentially the amount necessary
to support replacing SymbolRefAttrs, but suffers from various
deficiencies (both ergonomic and functional):
* Replace crashes if unsupported
This makes it really hard to use safely, given that you don't know
if you are going to crash or not when using it.
* Types aren't supported
This seems like a simple missed addition when the attribute replacement
support was originally added.
* The ergonomics are weird
It currently uses an index based replacement, which makes the implementations
quite clunky.
This commit refactors support to be a bit more ergonomic, and also
adds support for types in the process. This was also a great oppurtunity
to greatly simplify how replacement is done in the symbol table.
Fixes#56355
Differential Revision: https://reviews.llvm.org/D130589
This attribute is similar to DenseElementsAttr but does not support
splat. As such it has a much simpler API and does not need any smart
iterator: it exposes direct ArrayRef access.
A new syntax is introduced so that the generic printing/parsing looks
like:
[:i64 1, -2, 3]
This attribute beings like an ArrayAttr but has a `:` token after the
opening square brace to introduce the element type (supported are I8,
I16, I32, I64, F32, F64) and the comma separated list for the data.
This is particularly convenient for attributes intended to be small,
like those referring to shapes.
For example a `transpose` operation with a `dims` attribute could be
defined as such:
let arguments = (ins AnyTensor:$input, DenseI64ArrayAttr:$dims);
let assemblyFormat = "$input `dims` `=` $dims attr-dict : type($input)";
And printed this way (the element type is elided in this case):
transpose %input dims = [0, 2, 1] : tensor<2x3x4xf32>
The C++ API for dims would just directly return an ArrayRef<int64>
RFC: https://discourse.llvm.org/t/rfc-introduce-a-new-dense-array-attribute/63279
Recommit with a custom DenseArrayBaseAttrStorage class to ensure
over-alignment of the storage to the largest type.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D123774
This attribute is similar to DenseElementsAttr but does not support
splat. As such it has a much simpler API and does not need any smart
iterator: it exposes direct ArrayRef access.
A new syntax is introduced so that the generic printing/parsing looks
like:
[:i64 1, -2, 3]
This attribute beings like an ArrayAttr but has a `:` token after the
opening square brace to introduce the element type (supported are I8,
I16, I32, I64, F32, F64) and the comma separated list for the data.
This is particularly convenient for attributes intended to be small,
like those referring to shapes.
For example a `transpose` operation with a `dims` attribute could be
defined as such:
let arguments = (ins AnyTensor:$input, DenseI64ArrayAttr:$dims);
let assemblyFormat = "$input `dims` `=` $dims attr-dict : type($input)";
And printed this way (the element type is elided in this case):
transpose %input dims = [0, 2, 1] : tensor<2x3x4xf32>
The C++ API for dims would just directly return an ArrayRef<int64>
RFC: https://discourse.llvm.org/t/rfc-introduce-a-new-dense-array-attribute/63279
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D123774
When convertEndianOfCharForBEmachine is called with elementBitWidth
smaller than CHAR_BIT, the default case is invoked, but this does
nothing at all and leaves the output array unchanged.
Fix DenseIntOrFPElementsAttr::convertEndianOfArrayRefForBEmachine
by not calling convertEndianOfCharForBEmachine in this case, and
instead simply copying the input to the output (for sub-byte types,
endian conversion is in fact a no-op).
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D125676
Instead of requiring the client to compute the "isSplat" bit,
compute it internally. This makes the logic more consistent
and defines away a lot of "elements.size()==1" in the clients.
This addresses Issue #55185
Differential Revision: https://reviews.llvm.org/D125447
A large DenseElementsAttr of i1could trigger a bug in printer/parser roundtrip.
Ex. A DenseElementsAttr of i1 with 200 elements will print as Hex format of length 400 before the fix. However, when parsing the printed text, an error will be triggered. After fix, the printed length will be 50.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D122925
