Now that a view op has graduated to the std dialect, we can update Linalg to use it and remove ops that have become obsolete. As a byproduct, the linalg buffer and associated ops can also disappear.
PiperOrigin-RevId: 279073591
This CL ports the lowering of linalg.view to the newly introduced std.view.
Differences in implementation relate to std.view having slightly different semantics:
1. a static or dynamic offset can be specified.
2. the size of the (contiguous) shape is passed instead of a range.
3. static size and stride information is extracted from the memref type rather than the range.
Besides these differences, lowering behaves the same.
A future CL will update Linalg to use this unified infrastructure.
PiperOrigin-RevId: 278948853
This is useful for making matching cases where a non-zero value is required more readable, such as the results of a constant comparison that are expected to be equal.
PiperOrigin-RevId: 278932874
Many operations with regions add an additional 'attributes' prefix when printing the attribute dictionary to differentiate it from the region body. This leads to duplicated logic for detecting when to actually print the attribute dictionary.
PiperOrigin-RevId: 278747681
This allows GlobalOp to either take a value attribute (for simple constants) or a region that can
contain IR instructions (that must be constant-foldable) to create a ConstantExpr initializer.
Example:
// A complex initializer is constructed with an initializer region.
llvm.mlir.global constant @int_gep() : !llvm<"i32*"> {
%0 = llvm.mlir.addressof @g2 : !llvm<"i32*">
%1 = llvm.mlir.constant(2 : i32) : !llvm.i32
%2 = llvm.getelementptr %0[%1] : (!llvm<"i32*">, !llvm.i32) -> !llvm<"i32*">
llvm.return %2 : !llvm<"i32*">
}
PiperOrigin-RevId: 278717836
This adds an importer from LLVM IR or bitcode to the LLVM dialect. The importer is registered with mlir-translate.
Known issues exposed by this patch but not yet fixed:
* Globals' initializers are attributes, which makes it impossible to represent a ConstantExpr. This will be fixed in a followup.
* icmp returns i32 rather than i1.
* select and a couple of other instructions aren't implemented.
* llvm.cond_br takes its successors in a weird order.
The testing here is known to be non-exhaustive.
I'd appreciate feedback on where this functionality should live. It looks like the translator *from MLIR to LLVM* lives in Target/, but the SPIR-V deserializer lives in Dialect/ which is why I've put this here too.
PiperOrigin-RevId: 278711683
A pattern rewriter hook, mergeBlock, is added that allows for merging the operations of one block into the end of another. This is used to support a canonicalization pattern for branch operations that folds the branch when the successor has a single predecessor(the branch block).
Example:
^bb0:
%c0_i32 = constant 0 : i32
br ^bb1(%c0_i32 : i32)
^bb1(%x : i32):
return %x : i32
becomes:
^bb0:
%c0_i32 = constant 0 : i32
return %c0_i32 : i32
PiperOrigin-RevId: 278677825
This simplifies the implementation quite a bit, and removes the need for explicit string munging. One change is made to some of the enum elements of SPV_DimAttr to ensure that they are proper identifiers; The string form is now prefixed with 'Dim'.
PiperOrigin-RevId: 278027132
This simplifies the implementation, and removes the need to do explicit string manipulation. A utility method 'parseDimensionList' is added to the DialectAsmParser to simplify defining types and attributes that contain shapes.
PiperOrigin-RevId: 278020604
This greatly simplifies the implementation and removes custom parser functionality. The necessary methods are added to the DialectAsmParser.
PiperOrigin-RevId: 278015983
Now that a proper parser is passed to these methods, there isn't a need to explicitly pass a source location. The source location can be recovered from the parser as necessary. This removes the need to explicitly decode an SMLoc in the case where we don't need to, which can be expensive.
This requires adding some basic nesting support to the parser for supporting nested parsers to allow for remapping source locations of the nested parsers to the top level parser for accurate diagnostics. This is due to the fact that the attribute and type parsers use different source buffers than the top level parser, as they may be represented in string form.
PiperOrigin-RevId: 278014858
These classes are functionally similar to the OpAsmParser/Printer classes and provide hooks for parsing attributes/tokens/types/etc. This change merely sets up the base infrastructure and updates the parser hooks, followups will add hooks as needed to simplify existing handrolled dialect parsers.
This has various different benefits:
*) Attribute/Type parsing is much simpler to define.
*) Dialect attributes/types that contain other attributes/types can now use aliases.
*) It provides a 'spec' with which we may use in the future to auto-generate parsers/printers.
*) Error messages emitted by attribute/type parsers can provide character exact locations rather than "beginning of the string"
PiperOrigin-RevId: 278005322
BitEnumAttr is a mechanism for modelling attributes whose value is
a bitfield. It should not be scoped to the SPIR-V dialect and can
be used by other dialects too.
This CL is mostly shuffling code around and adding tests and docs.
Functionality changes are:
* Fixed to use `getZExtValue()` instead of `getSExtValue()` when
getting the value from the underlying IntegerAttr for a case.
* Changed to auto-detect whether there is a case whose value is
all bits unset (i.e., zero). If so handle it specially in all
helper methods.
PiperOrigin-RevId: 277964926
The current lowering of loops to GPU only supports lowering of loop
nests where the loops mapped to workgroups and workitems are perfectly
nested. Here a new lowering is added to handle lowering of imperfectly
nested loop body with the following properties
1) The loops partitioned to workgroups are perfectly nested.
2) The loop body of the inner most loop partitioned to workgroups can
contain one or more loop nests that are to be partitioned across
workitems. Each individual loops nests partitioned to workitems should
also be perfectly nested.
3) The number of workgroups and workitems are not deduced from the
loop bounds but are passed in by the caller of the lowering as values.
4) For statements within the perfectly nested loop nest partitioned
across workgroups that are not loops, it is valid to have all threads
execute that statement. This is NOT verified.
PiperOrigin-RevId: 277958868
This CL adds a simple pattern for specifying producer-consumer fusion on Linalg operations.
Implementing such an extension reveals some interesting properties.
Since Linalg operates on a buffer abstraction, the output buffers are specified as in/out parameters to the ops. As a consequence, there are no SSA use-def chains and one cannot specify complex dag input patterns with the current infrastructure.
Instead this CL uses constraints based on the existing linalg dependence analysis to focus the pattern and refine patterns based on the type of op that last wrote in a buffer.
This is a very local property and is less powerful than the generic dag specification based on SSA use-def chains.
This will be generalized in the future.
PiperOrigin-RevId: 277931503
Upstream LLVM gained support for #ifndef with https://reviews.llvm.org/D61888
This is changed mechanically via the following command:
find . -name "*.td" -exec sed -i -e ':a' -e 'N' -e '$!ba' -e 's/#ifdef \([A-Z_]*\)\n#else/#ifndef \1/g' {} \;
PiperOrigin-RevId: 277789427
MLIR const-correctness policy is to avoid having `const` on IR objects.
LinalgDependenceGraph is not an IR object but an auxiliary data structure.
Furthermore, it is not updated once constructed unlike IR objects. Add const
qualifiers to get* and find* methods of LinalgDependenceGraph since they are
not modifying the graph. This allows transformation functions that require the
dependence graph to take it by const-reference, clearly indicating that they
are not modifying it (and that the graph may have to be recomputed after the
transformation).
PiperOrigin-RevId: 277731608
This CL added op definitions for a few cast operations:
* OpConvertFToU
* OpConvertFToS
* OpConvertSToF
* OpConvertUToF
* OpUConvert
* OpSConvert
* OpFConvert
Also moved the definition of spv.Bitcast to the new file.
Closestensorflow/mlir#208 and tensorflow/mlir#174
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/208 from denis0x0D:sandbox/cast_ops 79bc9b37398aafddee6cf6beb301807988fe67f9
PiperOrigin-RevId: 277587891
Rewrite patterns may make modifications to the CFG, including dropping edges between blocks. This change adds a simple unreachable block elimination run at the end of each iteration to ensure that the CFG remains valid.
PiperOrigin-RevId: 277545805
Linalg ops provide a good anchor for pattern matching/rewriting transformations.
This CL adds a simple example of how multi-level tiling may be specified by attaching a simple StringAttr to ops as they are transformed so we can easily specify partial lowering to control transformation application.
This is a first stab at taking advantage of higher-level information contained in Linalg ops and will evolve in the future.
PiperOrigin-RevId: 277497958
This CL fixed gen_spirv_dialect.py to support nested delimiters when
chunking existing ODS entries in .td files and to allow ops without
correspondence in the spec. This is needed to pull in the definition
of OpUnreachable.
PiperOrigin-RevId: 277486465
When we removed a pattern, we removed it from worklist but not from
worklistMap. Then, when we tried to add a new pattern on the same Operation
again, the pattern wasn't added since it already existed in the
worklistMap (but not in the worklist).
Closestensorflow/mlir#211
PiperOrigin-RevId: 277319669
This removes a bunch of special tailored DFS code in favor of the common
LLVM utility. Besides, we avoid recursion with system stack given that
llvm::depth_first_ext is iterator based and maintains its own stack.
PiperOrigin-RevId: 277272961
The SelectOp always has the same result type as its true/false
value. Add a builder method that uses the operand type to get the
result type.
PiperOrigin-RevId: 277217978
This CL adds another control flow instruction in SPIR-V: OpPhi.
It is modelled as block arguments to be idiomatic with MLIR.
See the rationale.md doc for "Block Arguments vs PHI nodes".
Serialization and deserialization is updated to convert between
block arguments and SPIR-V OpPhi instructions.
PiperOrigin-RevId: 277161545
For ops that recursively re-enter the parser to parse an operation (such as
ops with a "wraps" pretty form), this ensures that the wrapped op will parse
its location, which can then be used for the locations of the wrapping op
and any other implicit ops.
PiperOrigin-RevId: 277152636
This will be used to specify declarative Linalg transformations in a followup CL. In particular, the PatternRewrite mechanism does not allow folding and has its own way of tracking erasure.
PiperOrigin-RevId: 277149158
In some cases, it may be desirable to mark entire regions of operations as legal. This provides an additional granularity of context to the concept of "legal". The `ConversionTarget` supports marking operations, that were previously added as `Legal` or `Dynamic`, as `recursively` legal. Recursive legality means that if an operation instance is legal, either statically or dynamically, all of the operations nested within are also considered legal. An operation can be marked via `markOpRecursivelyLegal<>`:
```c++
ConversionTarget &target = ...;
/// The operation must first be marked as `Legal` or `Dynamic`.
target.addLegalOp<MyOp>(...);
target.addDynamicallyLegalOp<MySecondOp>(...);
/// Mark the operation as always recursively legal.
target.markOpRecursivelyLegal<MyOp>();
/// Mark optionally with a callback to allow selective marking.
target.markOpRecursivelyLegal<MyOp, MySecondOp>([](Operation *op) { ... });
/// Mark optionally with a callback to allow selective marking.
target.markOpRecursivelyLegal<MyOp>([](MyOp op) { ... });
```
PiperOrigin-RevId: 277086382
This allows for parsing things like:
%name_1, %name_2:5, %name_3:2 = "my.op" ...
This is useful for operations that have groups of variadic result values. The
total number of results is expected to match the number of results defined by
the operation.
PiperOrigin-RevId: 276703280
Combine chained `spirv::AccessChainOp` operations into one
`spirv::AccessChainOp` operation.
Closestensorflow/mlir#198
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/198 from denis0x0D:sandbox/canon_access_chain 0cb87955a85511071143d62637ff939d0dabc2bd
PiperOrigin-RevId: 276609345
This allows for them to be used on other non-function, or even other function-like, operations. The algorithms are already generic, so this is simply changing the derived pass type. The majority of this change is just ensuring that the nesting of these passes remains the same, as the pass manager won't auto-nest them anymore.
PiperOrigin-RevId: 276573038
MLIRIR includes generated header for interfaces, including these headers require
an extra dependency to ensure these headers are generated before we attempt to
build MLIREDSCInterface.
PiperOrigin-RevId: 276518255
This simplifies defining expected-* directives when there are multiple that apply to the next or previous line. @below applies the directive to the next non-designator line, i.e. the next line that does not contain an expected-* designator. @above applies to the previous non designator line.
Examples:
// Expect an error on the next line that does not contain a designator.
// expected-remark@below {{remark on function below}}
// expected-remark@below {{another remark on function below}}
func @bar(%a : f32)
// Expect an error on the previous line that does not contain a designator.
func @baz(%a : f32)
// expected-remark@above {{remark on function above}}
// expected-remark@above {{another remark on function above}}
PiperOrigin-RevId: 276369085
The ExecutionEngine was updated recently to only take the LLVM dialect as
input. Memrefs are no longer expected in the signature of the entry point
function by the executor so there is no need to allocate and free them. The
code in MemRefUtils is therefore dead and furthermore out of sync with the
recent evolution of memref type to support strides. Drop it.
PiperOrigin-RevId: 276272302
Previously DRR assumes attributes to appear after operands. This was the
previous requirements on ODS, but that has changed some time ago. Fix
DRR to also support interleaved operands and attributes.
PiperOrigin-RevId: 275983485
We will use block arguments as the way to model SPIR-V OpPhi in
the SPIR-V dialect.
This CL also adds a few useful helper methods to both ops to
get the block arguments.
Also added tests for branch weight (de)serialization.
PiperOrigin-RevId: 275960797
nvvm.shfl.sync.bfly optionally returns a predicate whether source lane was active. Support for this was added to clang in https://reviews.llvm.org/D68892.
Add an optional 'pred' unit attribute to the instruction to return this predicate. Specify this attribute in the partial warp reduction so we don't need to manually compute the predicate.
PiperOrigin-RevId: 275616564
Refactor the implementation to be much cleaner by adding a `make_second_range` utility to walk the `second` value of a range of pairs.
PiperOrigin-RevId: 275598985
This allows dialect-specific attributes to be attached to func results. (or more specifically, FunctionLike ops).
For example:
```
func @f() -> (i32 {my_dialect.some_attr = 3})
```
This attaches my_dialect.some_attr with value 3 to the first result of func @f.
Another more complex example:
```
func @g() -> (i32, f32 {my_dialect.some_attr = "foo", other_dialect.some_other_attr = [1,2,3]}, i1)
```
Here, the second result has two attributes attached.
PiperOrigin-RevId: 275564165
This allows mixing linalg operations with vector transfer operations (with additional modifications to affine ops) and is a step towards solving tensorflow/mlir#189.
PiperOrigin-RevId: 275543361
A VectorTypeCastOp can only be used to lower between statically sized contiguous memrefs of scalar and matching vector type. The sizes and strides are thus fully static and easy to determine.
A relevant test is added.
This is a step towards solving tensorflow/mlir#189.
PiperOrigin-RevId: 275538981
This CL adds support for loop.for operations in EDSC and adds a test.
This will be used in a followup commit to implement lowering of vector_transfer ops so that it works more generally and is not subject to affine constraints.
PiperOrigin-RevId: 275349796
This CL creates a new Linalg promotion pass that operates on SubViewOp and decouples it from Linalg tiling. This is mostly moving code around.
PiperOrigin-RevId: 275329213
Add a canonicalization pattern for spv.selection operation.
Convert spv.selection operation to spv.Select based on
simple pattern.
Closestensorflow/mlir#183
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/183 from denis0x0D:sandbox/canon_select 43d04d923272dd60b9da39f70bdbc51a5168db62
PiperOrigin-RevId: 275312748
'_' is used frequently enough as the separator of words in symbols.
We should allow it in dialect symbols when considering pretty printing.
Also updated LangRef.md regarding pretty form.
PiperOrigin-RevId: 275312494
Previously when we bind a symbol to an op in DRR, it means to capture
the op's result(s) and later references will be expanded to result(s).
This means for ops without result, we are replacing the symbol with
nothing. This CL treats non-result op capturing and referencing as a
special case to mean the op itself.
PiperOrigin-RevId: 275269702
It's usually hard to understand what went wrong if mlir-tblgen
crashes on some input. This CL adds a few useful LLVM_DEBUG
statements so that we can use mlir-tblegn -debug to figure
out the culprit for a crash.
PiperOrigin-RevId: 275253532
We just need to implement a few interface hooks to DialectInlinerInterface
and CallOpInterface to gain the benefits of an inliner. :)
Right now only supports some trivial cases:
* Inlining single block with spv.Return/spv.ReturnValue
* Inlining multi block with spv.Return
* Inlining spv.selection/spv.loop without return ops
More advanced cases will require block argument and Phi support.
PiperOrigin-RevId: 275151132
This Chapter now introduces and makes use of the Interface concept
in MLIR to demonstrate ShapeInference.
END_PUBLIC
Closestensorflow/mlir#191
PiperOrigin-RevId: 275085151
Makes the spv.module generated by the GPU to SPIR-V conversion SPIR-V
spec compliant (validated using spirv-val from Vulkan tools).
1) Separate out the VulkanLayoutUtils from
DecorateSPIRVCompositeTypeLayoutPass to make it reusable within the
Type converter in SPIR-V lowering infrastructure. This is used to
compute the layout of the !spv.struct used in global variable type
description.
2) Set the capabilities of the spv.module to Shader (needed for use of
Logical Memory Model, and the extensions to
SPV_KHR_storage_buffer_storage_class for use of Storage Buffer)
PiperOrigin-RevId: 275081486
In addition to specifying the type of accumulation through the 'op' attribute, the accumulation can now also be specified as arbitrary code region.
Adds a gpu.yield op to specify the result of the accumulation.
Also support more types (integers) and accumulations (mul).
PiperOrigin-RevId: 275065447
The current SignatureConversion framework (part of DialectConversion)
allows remapping input arguments to a function from 1->0, 1->1 or
1->many arguments during conversion. Another case is where the
argument itself is dropped, but it's use are remapped to another
Value*.
An example of this is: The Vulkan/SPIR-V spec requires entry functions
to be of type void(void). The GPU -> SPIR-V conversion implemented
this without having the DialectConversion framework track the
remapping that lead to some undefined behavior. The changes here
addresses that.
PiperOrigin-RevId: 275059656
b843cc5d5a introduced a new op LICM transformation and a LoopLike interface,
but missed the CMake aspects of it. This should fix the build.
PiperOrigin-RevId: 275038533
The SpecId decoration is the handle for providing external specialization.
Similar to descriptor set and binding on global variables, we directly
bake it into assembly parsing and printing.
PiperOrigin-RevId: 274893879
This CL adds a missing lowering for splat of multi-dimensional vectors.
Additional support is also added to the runtime utils library to allow printing memrefs with such vectors.
PiperOrigin-RevId: 274794723
Python bindings currently currently provide a makeScalarType function that
constructs one of the predefined types. It was implemented in the bindings
directly to circumvent the absence of standalone type parsing function. Now
that mlir::parseType has been made available, rely on the core parsing
procedure to construct types from strings in the bindings.
This changes includes a library reshuffling that splits out "CoreAPIs"
implementing the binding helper APIs into a separate library and makes that
dependent on the Parser library.
PiperOrigin-RevId: 274794516
The value defined in a loop was not being used and the function producing it
re-evaluated instead. Use the value to avoid both the warning and the
re-evaluation.
PiperOrigin-RevId: 274794459
When dealing with regions, or other patterns that need to generate temporary operations, it is useful to be able to replace other operations than the root op being matched. Before this PR, these operations would still be considered for legalization meaning that the conversion would either fail, erroneously need to mark these ops as legal, or add unnecessary patterns.
PiperOrigin-RevId: 274598513
Andy Davis