| Commit message (Collapse) | Author | Age | Files | Lines |
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properly value-typed.
Summary: These were temporary methods used to simplify the transition.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D72548
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instances. NFCI.
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SPIR-V has a few mechanisms to control op availability: version,
extension, and capabilities. These mechanisms are considered as
different availability classes.
This commit introduces basic definitions for modelling SPIR-V
availability classes. Specifically, an `Availability` class is
added to SPIRVBase.td, along with two subclasses: MinVersion
and MaxVersion for versioning. SPV_Op is extended to take a
list of `Availability`. Each `Availability` instance carries
information for generating op interfaces for the corresponding
availability class and also the concrete availability
requirements.
With the availability spec on ops, we can now auto-generate the
op interfaces of all SPIR-V availability classes and also
synthesize the op's implementations of these interfaces. The
interface generation is done via new TableGen backends
-gen-avail-interface-{decls|defs}. The op's implementation is
done via -gen-spirv-avail-impls.
Differential Revision: https://reviews.llvm.org/D71930
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ValuePtr was a temporary typedef during the transition to a value-typed Value.
PiperOrigin-RevId: 286945714
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PiperOrigin-RevId: 286906740
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Value being value-typed.
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
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in `mlir` namespace.
Aside from being cleaner, this also makes the codebase more consistent.
PiperOrigin-RevId: 286206974
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Some changes to the dialect generation script to allow specification
of different base class to derive from in ODS.
PiperOrigin-RevId: 285859230
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This cleans up the implementation of the various operation print methods. This is done via a combination of code cleanup, adding new streaming methods to the printer(e.g. operand ranges), etc.
PiperOrigin-RevId: 285285181
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Add some convenience build methods to SPIR-V ops and update the
lowering to use these methods where possible.
For SPIRV::CompositeExtractOp move the method to deduce type of
element based on base and indices into a convenience function. Some
additional functionality needed to handle differences between parsing
and verification methods.
PiperOrigin-RevId: 284794404
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Closes tensorflow/mlir#308
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/308 from denis0x0D:sandbox/composite_construct 9ef7180f77f9374bcd05afc4f9e6c1d2d72d02b7
PiperOrigin-RevId: 284613617
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The patterns to be folded away can be commonly generated
during lowering to SPIR-V.
PiperOrigin-RevId: 284604855
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The existing GPU to SPIR-V lowering created a spv.module for every
function with gpu.kernel attribute. A better approach is to lower the
module that the function lives in (which has the attribute
gpu.kernel_module) to a spv.module operation. This better captures the
host-device separation modeled by GPU dialect and simplifies the
lowering as well.
PiperOrigin-RevId: 284574688
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This allows for users to provide operand_range and result_range in builder.create<> calls, instead of requiring an explicit copy into a separate data structure like SmallVector/std::vector.
PiperOrigin-RevId: 284360710
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A CompositeInsertOp operation make a copy of a composite object,
while modifying one part of it.
Closes tensorflow/mlir#292
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/292 from denis0x0D:sandbox/composite_insert 2200962b9057bda53cd2f2866b461e2797196380
PiperOrigin-RevId: 284036551
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PiperOrigin-RevId: 283997917
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This CL also did the following cleanup:
- Moved the test for spv.SubgroupBallotKHR to its own file
- Wrapped generated canonicalization patterns in anonymous namespace
- Updated header comments in SPVOps.td
PiperOrigin-RevId: 283650091
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PiperOrigin-RevId: 283522284
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folding.
Closes tensorflow/mlir#281
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/281 from denis0x0D:sandbox/composite_ex_fold d02d73658bd1b9eaa515eb4e0aee34bc41d4252b
PiperOrigin-RevId: 282971563
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Getting constant zero or one is very common so it merits a special handy
method on spirv::ConstantOp itself.
PiperOrigin-RevId: 282832572
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Adding zero and multiplying one can be common when generating code
for index calculation.
This CL also sorted canonicalize.mlir to alphabetical order.
PiperOrigin-RevId: 282828055
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To simplify the lowering into SPIR-V, while still respecting the ABI
requirements of SPIR-V/Vulkan, split the process into two
1) While lowering a function to SPIR-V (when the function is an entry
point function), allow specifying attributes on arguments and
function itself that describe the ABI of the function.
2) Add a pass that materializes the ABI described in the function.
Two attributes are needed.
1) Attribute on arguments of the entry point function that describe
the descriptor_set, binding, storage class, etc, of the
spv.globalVariable this argument will be replaced by
2) Attribute on function that specifies workgroup size, etc. (for now
only workgroup size).
Add the pass -spirv-lower-abi-attrs to materialize the ABI described
by the attributes.
This change makes the SPIRVBasicTypeConverter class unnecessary and is
removed, further simplifying the SPIR-V lowering path.
PiperOrigin-RevId: 282387587
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This CL added necessary files and settings for using DRR to
write SPIR-V canonicalization patterns and also converted the
patterns for spv.Bitcast and spv.LogicalNot.
PiperOrigin-RevId: 282132786
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Add a canonicalizer for `spirv::LogicalNotOp`.
Converts:
* spv.LogicalNot(spv.IEqual(...)) -> spv.INotEqual(...)
* spv.LogicalNot(spv.INotEqual(...)) -> spv.IEqual(...)
* spv.LogicalNot(spv.LogicalEqual(...)) -> spv.LogicalNotEqual(...)
* spv.LogicalNot(spv.LogicalNotEqual(...)) -> spv.LogicalEqual(...)
Also moved the test for spv.IMul to arithemtic tests.
Closes tensorflow/mlir#256
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/256 from denis0x0D:sandbox/canon_logical_not 76ab5787b2c777f948c8978db061d99e76453d44
PiperOrigin-RevId: 282012356
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Iterates each element to build the array. This includes a little refactor to
combine bool/int/float into a function, since they are similar. The only
difference is calling different function in the end.
PiperOrigin-RevId: 281210288
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Convert chained `spirv::BitcastOp` operations into
one `spirv::BitcastOp` operation.
Closes tensorflow/mlir#238
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/238 from denis0x0D:sandbox/canon_bitcast 4352ed4f81b959ec92f849c599e733b62a99c010
PiperOrigin-RevId: 281129234
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This CL added op definitions for a few bit operations:
* OpBitFieldInsert
* OpBitFieldSExtract
* OpBitFieldUExtract
Closes tensorflow/mlir#233
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/233 from denis0x0D:sandbox/bit_field_ops e7fd85b00d72d483d7992dc42b9cc4d673903455
PiperOrigin-RevId: 280691816
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During deserialization, the loop header block will be moved into the
spv.loop's region. If the loop header block has block arguments,
we need to make sure it is correctly carried over to the block where
the new spv.loop resides.
During serialization, we need to make sure block arguments from the
spv.loop's entry block are not silently dropped.
PiperOrigin-RevId: 280021777
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This change allows for adding additional nested references to a SymbolRefAttr to allow for further resolving a symbol if that symbol also defines a SymbolTable. If a referenced symbol also defines a symbol table, a nested reference can be used to refer to a symbol within that table. Nested references are printed after the main reference in the following form:
symbol-ref-attribute ::= symbol-ref-id (`::` symbol-ref-id)*
Example:
module @reference {
func @nested_reference()
}
my_reference_op @reference::@nested_reference
Given that SymbolRefAttr is now more general, the existing functionality centered around a single reference is moved to a derived class FlatSymbolRefAttr. Followup commits will add support to lookups, rauw, etc. for scoped references.
PiperOrigin-RevId: 279860501
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This CL added op definitions for a few bit operations:
* OpShiftLeftLogical
* OpShiftRightArithmetic
* OpShiftRightLogical
* OpBitCount
* OpBitReverse
* OpNot
Also moved the definition of spv.BitwiseAnd to follow the
lexicographical order.
Closes tensorflow/mlir#215
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/215 from denis0x0D:sandbox/bit_ops d9b0852b689ac6c4879a9740b1740a2357f44d24
PiperOrigin-RevId: 279350470
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attribute dictionaries with regions.
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
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name of the print method.
PiperOrigin-RevId: 278696668
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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.
Closes tensorflow/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
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This provides an easy way to check if a range has a single element.
PiperOrigin-RevId: 277544647
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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
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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
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Combine chained `spirv::AccessChainOp` operations into one
`spirv::AccessChainOp` operation.
Closes tensorflow/mlir#198
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/198 from denis0x0D:sandbox/canon_access_chain 0cb87955a85511071143d62637ff939d0dabc2bd
PiperOrigin-RevId: 276609345
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Closes tensorflow/mlir#177
PiperOrigin-RevId: 275692653
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PiperOrigin-RevId: 275631166
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These don't add any value, and some are even more restrictive than the respective static 'get' method.
PiperOrigin-RevId: 275391240
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Add a canonicalization pattern for spv.selection operation.
Convert spv.selection operation to spv.Select based on
simple pattern.
Closes tensorflow/mlir#183
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/183 from denis0x0D:sandbox/canon_select 43d04d923272dd60b9da39f70bdbc51a5168db62
PiperOrigin-RevId: 275312748
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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
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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
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The restriction that symbols can only have identifier names is arbitrary, and artificially limits the names that a symbol may have. This change adds support for parsing and printing symbols that don't fit in the 'bare-identifier' grammar by printing the reference in quotes, e.g. @"0_my_reference" can now be used as a symbol name.
PiperOrigin-RevId: 273644768
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Use `getParentOfType<FunctionOp>()` instead of `cast<FuncOp>(getParentOp())`
to avoid crash when return ops are used inside spv.selection/spv.loop.
PiperOrigin-RevId: 273006041
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Adding support for OpUndef instruction. Updating the dialect
generation script to fix a few bugs in the instruction spec
generation.
PiperOrigin-RevId: 272975685
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Add builder functions for spv._address_of, spv.EntryPoint,
spv.ExecutionMode and spv.Load to make it easier to create these
operations.
Fix a minor bug in printing of spv.EntryPoint
Add a utility function to get the attribute name associated with a
decoration.
PiperOrigin-RevId: 272952846
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Similar to spv.loop, spv.selection is another op for modelling
SPIR-V structured control flow. It covers both OpBranchConditional
and OpSwitch with OpSelectionMerge.
Instead of having a `spv.SelectionMerge` op to directly model
selection merge instruction for indicating the merge target,
we use regions to delimit the boundary of the selection: the
merge target is the next op following the `spv.selection` op.
This way it's easier to discover all blocks belonging to
the selection and it plays nicer with the MLIR system.
PiperOrigin-RevId: 272475006
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Add operations corresponding to OpLogicalAnd, OpLogicalNot,
OpLogicalEqual, OpLogicalNotEqual and OpLogicalOr instructions in
SPIR-V dialect. This needs changes to class hierarchy in SPIR-V
TableGen files to split SPIRVLogicalOp into SPIRVLogicalUnaryOp and
SPIRVLogicalBinaryOp. All derived classes of SPIRVLogicalOp are
updated accordingly.
Update the spirv dialect generation script to
1) Allow specifying base class to use for instruction spec generation
and file name to generate the specification in separately.
2) Use the existing descriptions for operations.
3) Update define_inst.sh to also invoke define_opcode.sh to also
define the corresponding SPIR-V instruction opcode enum.
PiperOrigin-RevId: 272014876
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Support the OpBitcast instruction of SPIR-V using the spv.Bitcast
operation. The semantics implemented in the dialect differ from the
SPIR-V spec in that the dialect does not allow conversion to/from
pointer types from/to non-pointer types.
PiperOrigin-RevId: 271255957
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