This commit refactors the expected form of native constraint and rewrite
functions, and greatly reduces the necessary user complexity required when
defining a native function. Namely, this commit adds in automatic processing
of the necessary PDLValue glue code, and allows for users to define
constraint/rewrite functions using the C++ types that they actually want to
use.
As an example, lets see a simple example rewrite defined today:
```
static void rewriteFn(PatternRewriter &rewriter, PDLResultList &results,
ArrayRef<PDLValue> args) {
ValueRange operandValues = args[0].cast<ValueRange>();
TypeRange typeValues = args[1].cast<TypeRange>();
...
// Create an operation at some point and pass it back to PDL.
Operation *op = rewriter.create<SomeOp>(...);
results.push_back(op);
}
```
After this commit, that same rewrite could be defined as:
```
static Operation *rewriteFn(PatternRewriter &rewriter ValueRange operandValues,
TypeRange typeValues) {
...
// Create an operation at some point and pass it back to PDL.
return rewriter.create<SomeOp>(...);
}
```
Differential Revision: https://reviews.llvm.org/D122086
This commit restructures how TypeID is implemented to ideally avoid
the current problems related to shared libraries. This is done by changing
the "implicit" fallback path to use the name of the type, instead of using
a static template variable (which breaks shared libraries). The major downside to this
is that it adds some additional initialization costs for the implicit path. Given the
use of type names for uniqueness in the fallback, we also no longer allow types
defined in anonymous namespaces to have an implicit TypeID. To simplify defining
an ID for these classes, a new `MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID` macro
was added to allow for explicitly defining a TypeID directly on an internal class.
To help identify when types are using the fallback, `-debug-only=typeid` can be
used to log which types are using implicit ids.
This change generally only requires changes to the test passes, which are all defined
in anonymous namespaces, and thus can't use the fallback any longer.
Differential Revision: https://reviews.llvm.org/D122775
This provides a way to create an operation without manipulating
OperationState directly. This is useful for creating unregistered ops.
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D120787
This support has never really worked well, and is incredibly clunky to
use (it effectively creates two argument APIs), and clunky to generate (it isn't
clear how we should actually expose this from PDL frontends). Treating these
as just attribute arguments is much much cleaner in every aspect of the stack.
If we need to optimize lots of constant parameters, it would be better to
investigate internal representation optimizations (e.g. batch attribute creation),
that do not affect the user (we want a clean external API).
Differential Revision: https://reviews.llvm.org/D121569
This diff adds an integration test to multi-root PDL matching. It consists of two subtests:
1) A 1-layer perceptron with split forward / backward operations.
2) A 2-layer perceptron with fused forward / backward operations.
These tests use a collection of hand-written patterns and TensorFlow operations to be matched. The first test has a DAG / SSA dominant resulting match; the second does not and is therefore stored in a graph region.
This diff also includes two bug fixes:
1) Mark the pdl_interp dialect as a dependent in the TestPDLByteCodePass. This is needed, because we create ops from that dialect as a part of the PDL-to-PDLInterp lowering.
2) Fix of the starting index in the liveness range for the ForEach operations (bug exposed by the integration test).
Reviewed By: Mogball
Differential Revision: https://reviews.llvm.org/D116082
* Constraints/Rewrites registered before a pattern was added were dropped
* Constraints/Rewrites may be registered multiple times (if different pattern sets depend on them)
* ModuleOp no longer has a terminator, so we shouldn't be removing the terminator from it
Differential Revision: https://reviews.llvm.org/D114816
SymbolRefAttr is fundamentally a base string plus a sequence
of nested references. Instead of storing the string data as
a copies StringRef, store it as an already-uniqued StringAttr.
This makes a lot of things simpler and more efficient because:
1) references to the symbol are already stored as StringAttr's:
there is no need to copy the string data into MLIRContext
multiple times.
2) This allows pointer comparisons instead of string
comparisons (or redundant uniquing) within SymbolTable.cpp.
3) This allows SymbolTable to hold a DenseMap instead of a
StringMap (which again copies the string data and slows
lookup).
This is a moderately invasive patch, so I kept a lot of
compatibility APIs around. It would be nice to explore changing
getName() to return a StringAttr for example (right now you have
to use getNameAttr()), and eliminate things like the StringRef
version of getSymbol.
Differential Revision: https://reviews.llvm.org/D108899
This doesn't change APIs, this just cleans up the many in-tree uses of these
names to use the new preferred names. We'll keep the old names around for a
couple weeks to help transitions.
Differential Revision: https://reviews.llvm.org/D99127
Supporting ranges in the byte code requires additional complexity, given that a range can't be easily representable as an opaque void *, as is possible with the existing bytecode value types (Attribute, Type, Value, etc.). To enable representing a range with void *, an auxillary storage is used for the actual range itself, with the pointer being passed around in the normal byte code memory. For type ranges, a TypeRange is stored. For value ranges, a ValueRange is stored. The above problem represents a majority of the complexity involved in this revision, the rest is adapting/adding byte code operations to support the changes made to the PDL interpreter in the parent revision.
After this revision, PDL will have initial end-to-end support for variadic operands/results.
Differential Revision: https://reviews.llvm.org/D95723
This has a numerous amount of benefits, given the overly clunky nature of CreateNativeOp:
* Users can now call into arbitrary rewrite functions from inside of PDL, allowing for more natural interleaving of PDL/C++ and enabling for more of the pattern to be in PDL.
* Removes the need for an additional set of C++ functions/registry/etc. The new ApplyNativeRewriteOp will use the same PDLRewriteFunction as the existing RewriteOp. This reduces the API surface area exposed to users.
This revision also introduces a new PDLResultList class. This class is used to provide results of native rewrite functions back to PDL. We introduce a new class instead of using a SmallVector to simplify the work necessary for variadics, given that ranges will require some changes to the structure of PDLValue.
Differential Revision: https://reviews.llvm.org/D95720
PDL patterns are now supported via a new `PDLPatternModule` class. This class contains a ModuleOp with the pdl::PatternOp operations representing the patterns, as well as a collection of registered C++ functions for native constraints/creations/rewrites/etc. that may be invoked via the pdl patterns. Instances of this class are added to an OwningRewritePatternList in the same fashion as C++ RewritePatterns, i.e. via the `insert` method.
The PDL bytecode is an in-memory representation of the PDL interpreter dialect that can be efficiently interpreted/executed. The representation of the bytecode boils down to a code array(for opcodes/memory locations/etc) and a memory buffer(for storing attributes/operations/values/any other data necessary). The bytecode operations are effectively a 1-1 mapping to the PDLInterp dialect operations, with a few exceptions in cases where the in-memory representation of the bytecode can be more efficient than the MLIR representation. For example, a generic `AreEqual` bytecode op can be used to represent AreEqualOp, CheckAttributeOp, and CheckTypeOp.
The execution of the bytecode is split into two phases: matching and rewriting. When matching, all of the matched patterns are collected to avoid the overhead of re-running parts of the matcher. These matched patterns are then considered alongside the native C++ patterns, which rewrite immediately in-place via `RewritePattern::matchAndRewrite`, for the given root operation. When a PDL pattern is matched and has the highest benefit, it is passed back to the bytecode to execute its rewriter.
Differential Revision: https://reviews.llvm.org/D89107
