| Commit message (Collapse) | Author | Age | Files | Lines |
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Summary:
This allows for users to cache printer state, which can be costly to recompute. Each of the IR print methods gain a new overload taking this new state class.
Depends On D72293
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D72294
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Summary:
This was previously disabled as FunctionType TypeAttrs could not be roundtripped in the IR. This has been fixed, so we can now generically print FuncOp.
Depends On D72429
Reviewed By: jpienaar, mehdi_amini
Differential Revision: https://reviews.llvm.org/D72642
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Summary:
The visibility defines the structural reachability of the symbol within the IR. Symbols can define one of three visibilities:
* Public
The symbol \may be accessed from outside of the visible IR. We cannot assume that we can observe all of the uses of this symbol.
* Private
The symbol may only be referenced from within the operations in the current symbol table, via SymbolRefAttr.
* Nested
The symbol may be referenced by operations in symbol tables above the current symbol table, as long as each symbol table parent also defines a non-private symbol. This allows or referencing the symbol from outside of the defining symbol table, while retaining the ability for the compiler to see all uses.
These properties help to reason about the properties of a symbol, and will be used in a follow up to implement a dce pass on dead symbols.
A few examples of what this would look like in the IR are shown below:
module @public_module {
// This function can be accessed by 'live.user'
func @nested_function() attributes { sym_visibility = "nested" }
// This function cannot be accessed outside of 'public_module'
func @private_function() attributes { sym_visibility = "private" }
}
// This function can only be accessed from within this module.
func @private_function() attributes { sym_visibility = "private" }
// This function may be referenced externally.
func @public_function()
"live.user"() {uses = [@public_module::@nested_function,
@private_function,
@public_function]} : () -> ()
Depends On D72043
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D72044
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references.
Summary: This updates the use list algorithms to support querying from a specific symbol, allowing for the collection and detection of nested references. This works by walking the parent "symbol scopes" and applying the existing algorithm at each level.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D72042
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conflicts with function types.
Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`.
Reviewed By: nicolasvasilache, ftynse
Differential Revision: https://reviews.llvm.org/D72429
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Summary: Introduce m_Constant() which allows matching a constant operation without forcing the user also to capture the attribute value.
Differential Revision: https://reviews.llvm.org/D72397
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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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Summary: Some data values have a different storage width than the corresponding MLIR type, e.g. bfloat is currently stored as a double.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D72478
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OperationPrinter and into a new class SSANameState.
Summary:
This reduces the complexity of OperationPrinter and simplifies the code by quite a bit. The SSANameState is now held by ModuleState. This is in preparation for a future revision that molds ModuleState into something that can be used by users for caching the printer state, as well as for implementing printAsOperand style methods.
Depends On D72292
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D72293
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Introduce a set of function that promote a memref argument of a `gpu.func` to
workgroup memory using memory attribution. The promotion boils down to
additional loops performing the copy from the original argument to the
attributed memory in the beginning of the function, and back at the end of the
function using all available threads. The loop bounds are specified so as to
adapt to any size of the workgroup. These utilities are intended to compose
with other existing utilities (loop coalescing and tiling) in cases where the
distribution of work across threads is uneven, e.g. copying a 2D memref with
only the threads along the "x" dimension. Similarly, specialization of the
kernel to specific launch sizes should be implemented as a separate pass
combining constant propagation and canonicalization.
Introduce a simple attribute-driven pass to test the promotion transformation
since we don't have a heuristic at the moment.
Differential revision: https://reviews.llvm.org/D71904
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a new class AliasState.
Summary: This reduces the complexity of ModuleState and simplifies the code. A future revision will mold ModuleState into something that can be used by users for caching of printer state, as well as for implementing printAsOperand style methods.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D72292
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Summary:
This diff adds a new operation to linalg to allow reshaping of an
existing view into a new view in the same buffer at the same offset.
More specifically:
The `linalg.reshape` op produces a new view whose sizes are a reassociation
of the original `view`. Depending on whether or not the reassociated
MemRefType is contiguous, the resulting memref may require explicit alloc
and copies.
A reassociation is defined as a continous grouping of dimensions and is
represented with a affine map array attribute. In the future, non-continous
groupings may be allowed (i.e. permutations, reindexings etc).
For now, it is assumed that either:
1. a reassociation produces and consumes contiguous MemRefType or,
2. the reshape op will be folded into its consumers (by changing the shape
of the computations).
All other cases are undefined behavior and a reshape op may not lower to
LLVM if it cannot be proven statically that it does not require alloc+copy.
A reshape may either collapse or expand dimensions, depending on the
relationship between source and target memref ranks. The verification rule
is that the reassociation maps are applied to the memref with the larger
rank to obtain the memref with the smaller rank. In the case of a dimension
expansion, the reassociation maps can be interpreted as inverse maps.
Examples:
```mlir
// Dimension collapse (i, j) -> i' and k -> k'
%1 = linalg.reshape %0 [(i, j, k) -> (i, j),
(i, j, k) -> (k)] :
memref<?x?x?xf32, stride_spec> into memref<?x?xf32, stride_spec_2>
```
```mlir
// Dimension expansion i -> (i', j') and (k) -> (k')
%1 = linalg.reshape %0 [(i, j, k) -> (i, j),
(i, j, k) -> (k)] :
memref<?x?xf32, stride_spec> into memref<?x?x?xf32, stride_spec_2>
```
The relevant invalid and roundtripping tests are added.
Reviewers: AlexEichenberger, ftynse, rriddle, asaadaldien, yangjunpro
Subscribers: kiszk, merge_guards_bot, mehdi_amini, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72168
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Summary: This diff reimplements getStridesAndOffset in a significantly simpler way by operating on the AffineExpr and calling into simplifyAffineExpr instead of rolling its own saturating arithmetic.
As a consequence it becomes quite simple to extend the behavior of getStridesAndOffset to encompass more cases by manipulating the AffineExpr more directly.
The divisions are still filtered out and continue to yield fully dynamic strides.
Simplifying the divisions is left for a later time if compelling use cases arise.
Relevant tests are added.
Reviewers: ftynse
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72098
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Summary: This fixes the return value of helper methods on the base range class.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D72127
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memory.
Summary:
This changes the implementation of OpResult to have some of the results be represented inline in Value, via a pointer int pair of Operation*+result number, and the rest being trailing objects on the main operation. The full details of the new representation is detailed in the proposal here:
https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
The only difference between here and the above proposal is that we only steal 2-bits for the Value kind instead of 3. This means that we can only fit 2-results inline instead of 6. This allows for other users to steal the final bit for PointerUnion/etc. If necessary, we can always steal this bit back in the future to save more space if 3-6 results are common enough.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D72020
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* replaceAllUsesWith may be supplied with a null value.
* some compilers fail to implicitly convert single result operations to
OpaqueValue, so add an explicit OpOperand::set(Value) method.
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for (const auto &x : llvm::zip(..., ...))
->
for (auto x : llvm::zip(..., ...))
The return type of zip() is a wrapper that wraps a tuple of references.
> warning: loop variable 'p' is always a copy because the range of type 'detail::zippy<detail::zip_shortest, ArrayRef<long> &, ArrayRef<long> &>' does not return a reference [-Wrange-loop-analysis]
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Fixes: warning: comparison of integers of different signs: 'const unsigned int' and '(anonymous namespace)::OperationPrinter::(anonymous enum at F:\llvm-project\mlir\lib\IR\AsmPrinter.cpp:1444:3)' [-Wsign-compare]
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of the operation.
Summary: A new class is added, IRMultiObjectWithUseList, that allows for representing an IR use list that holds multiple sub values(used in this case for OpResults). This class provides all of the same functionality as the base IRObjectWithUseList, but for specific sub-values. This saves a word per operation result and is a necessary step in optimizing the layout of operation results. For now the use list is placed on the operation itself, so zero-result operations grow by a word. When the work for optimizing layout is finished, this can be moved back to being a trailing object based on memory/runtime benchmarking.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D71955
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Summary: The successor operand counts are directly tied to block operands anyways, and this simplifies the trailing objects of Operation(i.e. one less computation to perform).
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D71949
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ValuePtr was a temporary typedef during the transition to a value-typed Value.
PiperOrigin-RevId: 286945714
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This means that in-place, or root, updates need to use explicit calls to `startRootUpdate`, `finalizeRootUpdate`, and `cancelRootUpdate`. The major benefit of this change is that it enables in-place updates in DialectConversion, which simplifies the FuncOp pattern for example. The major downside to this is that the cases that *may* modify an operation in-place will need an explicit cancel on the failure branches(assuming that they started an update before attempting the transformation).
PiperOrigin-RevId: 286933674
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internal pointer storage.
This will enable future commits to reimplement the internal implementation of OpResult without needing to change all of the existing users. This is part of a chain of commits optimizing the size of operation results.
PiperOrigin-RevId: 286930047
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PiperOrigin-RevId: 286924059
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pointer storage.
This will enable future commits to reimplement the internal implementation of OpResult without needing to change all of the existing users. This is part of a chain of commits optimizing the size of operation results.
PiperOrigin-RevId: 286919966
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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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This is the block argument equivalent of the existing `getAsmResultNames` hook.
Closes tensorflow/mlir#329
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/329 from plaidml:flaub-region-arg-names fc7876f2d1335024e441083cd25263fd6247eb7d
PiperOrigin-RevId: 286523299
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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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This keeps the IR valid and consistent as it is expected that each block should have a valid parent region/operation. Previously, converted blocks were kept floating without a valid parent region.
PiperOrigin-RevId: 285821687
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PiperOrigin-RevId: 285574334
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This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter.
PiperOrigin-RevId: 285448440
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It is sometimes useful to create operations separately from the builder before insertion as it may be easier to erase them in isolation if necessary. One example use case for this is folding, as we will only want to insert newly generated constant operations on success. This has the added benefit of fixing some silent PatternRewriter failures related to cloning, as the OpBuilder 'clone' methods don't call createOperation.
PiperOrigin-RevId: 285086242
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Add one more simplification for floordiv and mod affine expressions.
Examples:
(2*d0 + 1) floordiv 2 is simplified to d0
(8*d0 + 4*d1 + d2) floordiv 4 simplified to 4*d0 + d1 + d2 floordiv 4.
etc.
Similarly, (4*d1 + 1) mod 2 is simplified to 1,
(2*d0 + 8*d1) mod 8 simplified to 2*d0 mod 8.
Change getLargestKnownDivisor to return int64_t to be consistent and
to avoid casting at call sites (since the return value is used in expressions
of int64_t/index type).
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Closes tensorflow/mlir#202
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/202 from bondhugula:affine b13fcb2f1c00a39ca5434613a02408e085a80e77
PiperOrigin-RevId: 284866710
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indexed_accessor_range.
This has several benefits:
* The implementation is much cleaner and more efficient.
* The ranges now have support for many useful operations: operator[], slice, drop_front, size, etc.
* Value ranges can now directly query a range for their types via 'getTypes()': e.g:
void foo(Operation::operand_range operands) {
auto operandTypes = operands.getTypes();
}
PiperOrigin-RevId: 284834912
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This reorganizes the vector transformations to be more easily testable as patterns and more easily composable into fused passes in the future.
PiperOrigin-RevId: 284817474
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Each of the support classes for Block are now moved into a new header BlockSupport.h. The successor iterator class is also reimplemented as an indexed_accessor_range. This makes the class more efficient, and expands on its available functionality.
PiperOrigin-RevId: 284646792
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simplify defining index-able ranges.
Many ranges want similar functionality from a range type(e.g. slice/drop_front/operator[]/etc.), so these classes provide a generic implementation that may be used by many different types of ranges. This removes some code duplication, and also empowers many of the existing range types in MLIR(e.g. result type ranges, operand ranges, ElementsAttr ranges, etc.). This change only updates RegionRange and ValueRange, more ranges will be updated in followup commits.
PiperOrigin-RevId: 284615679
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Follows ValueRange in representing a generic abstraction over the different
ways to represent a range of Regions. This wrapper is not as ValueRange and only
considers the current cases of interest: MutableArrayRef<Region> and
ArrayRef<std::unique_ptr<Region>> as occurs during op construction vs op region
querying.
Note: ArrayRef<std::unique_ptr<Region>> allows for unset regions, so this range
returns a pointer to a Region instead of a Region.
PiperOrigin-RevId: 284563229
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Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Closes tensorflow/mlir#305
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/305 from bondhugula:value_range 21d1fae73f549e3c8e72b60876eff1b864cea39c
PiperOrigin-RevId: 284541027
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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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This class represents a generic abstraction over the different ways to represent a range of Values: ArrayRef<Value *>, operand_range, result_range. This class will allow for removing the many instances of explicit SmallVector<Value *, N> construction. It has the same memory cost as ArrayRef, and only suffers cost from indexing(if+elsing the different underlying representations).
This change only updates a few of the existing usages, with more to be changed in followups; e.g. 'build' API.
PiperOrigin-RevId: 284307996
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Closes tensorflow/mlir#290
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/290 from kiszk:spelling_tweaks_201912 9d9afd16a723dd65754a04698b3976f150a6054a
PiperOrigin-RevId: 284169681
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This patch closes issue tensorflow/mlir#271.
It adds an optional permutation map to declarative tiling transformations.
The map is expressed as a list of integers.
Closes tensorflow/mlir#288
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/288 from tetuante:issue271 2df2938d6a1f01b3bc404ded08dea2dd1e10b588
PiperOrigin-RevId: 284064151
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Closes tensorflow/mlir#261
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/261 from nmostafa:nmostafa/unranked 96b6e918f6ed64496f7573b2db33c0b02658ca45
PiperOrigin-RevId: 284037040
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It is often desirable to know where within the program that a diagnostic was emitted, without reverting to assert/unreachable which crash the program. This change adds a flag `mlir-print-stacktrace-on-diagnostic` that attaches the current stack trace as a note to every diagnostic that gets emitted.
PiperOrigin-RevId: 283996373
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Note for broken code, the following transformations occurred:
ModuleManager::insert(Block::iterator, Operation*) - > SymbolTable::insert(Operation*, Block::iterator)
ModuleManager::lookupSymbol -> SymbolTable::lookup
ModuleManager::getModule() -> SymbolTable::getOp()
ModuleManager::getContext() -> SymbolTable::getOp()->getContext()
ModuleManager::* -> SymbolTable::*
PiperOrigin-RevId: 283944635
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This change adds support for non-congruent indices in the operation ordering within a basic block. This effect of this is that insertions are less likely to cause an invalidation of the ordering within a block. This has a big effect on modules that have very large basic blocks.
PiperOrigin-RevId: 283858136
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an optional location.
In some situations a diagnostic may optionally be emitted by the presence of a location, e.g. attribute and type verification. These situations currently require extra 'if(loc) emitError(...); return failure()' wrappers that make verification clunky. These new overloads take an optional location and a list of arguments to the diagnostic, and return a LogicalResult. We take the arguments directly and return LogicalResult instead of returning InFlightDiagnostic because we cannot create a valid diagnostic with a null location. This creates an awkward situation where a user may try to treat the, potentially null, diagnostic as a valid one and encounter crashes when attaching notes/etc. Below is an example of how these methods simplify some existing usages:
Before:
if (loc)
emitError(*loc, "this is my diagnostic with argument: ") << 5;
return failure();
After:
return emitOptionalError(loc, "this is my diagnostic with argument: ", 5);
PiperOrigin-RevId: 283853599
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