Introduce a new operation property / trait (AutomaticAllocationScope)
for operations with regions that define a new scope for automatic allocations;
such allocations (typically realized on stack) are automatically freed when
control leaves such ops' regions. std.alloca's are freed at the closest
surrounding op that has this trait. All FunctionLike operations should normally
have this trait.
Differential Revision: https://reviews.llvm.org/D77787
Introduce the alloca op for stack memory allocation. When converting to the
LLVM dialect, this is lowered to an llvm.alloca. Refactor the std to
llvm conversion for alloc op to reuse with alloca. Drop useAlloca option
with alloc op lowering.
Differential Revision: https://reviews.llvm.org/D76602
Summary: This revision adds support for marking the last region as variadic in the ODS region list with the VariadicRegion directive.
Differential Revision: https://reviews.llvm.org/D77455
Summary: The attribute grammar includes an optional trailing colon type, so for attributes without a constant buildable type this will generally lead to unexpected and undesired behavior. Given that, it's better to just error out on these cases.
Differential Revision: https://reviews.llvm.org/D77293
Summary: This revision updates the SourceMgrDiagnosticHandler to not print the source location of a note if it is the same location as the previously printed diagnostic. This helps avoid redundancy, and potential confusion, when looking at the diagnostic output.
Differential Revision: https://reviews.llvm.org/D76787
It's common in many dialects to use tensors to themselves hold tensor shapes (for example, the shape is itself the result of some non-trivial calculation). Currently, such dialects have to use `tensor<?xi64>` or worse (like allowing either i32 or i64 tensors to represent shapes). `tensor<?xindex>` is the natural type to represent this, but is currently disallowed. This patch allows it.
Differential Revision: https://reviews.llvm.org/D76726
Summary:
The attribute parser fails to correctly parse unsigned 64 bit
attributes as the check `isNegative ? (int64_t)-val.getValue() >= 0
: (int64_t)val.getValue() < 0` will falsely detect an overflow for
unsigned values larger than 2^63-1.
This patch reworks the overflow logic to instead of doing arithmetic
on int64_t use APInt::isSignBitSet() and knowledge of the attribute
type.
Test-cases which verify the de-facto behavior of the parser and
triggered the previous faulty handing of unsigned 64 bit attrbutes are
also added.
Differential Revision: https://reviews.llvm.org/D76493
Summary:
While here, simplify the lexer a bit by eliminating the unneeded 'operator'
classification of certain sigils, they can just be treated as 'punctuation'.
Reviewers: rriddle!
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76647
Summary:
This allows the custom parser/printer hooks to do interesting things with
the SSA names. This patch:
- Adds a new 'getResultName' method to OpAsmParser that allows a parser
implementation to get information about its result names, along with
a getNumResults() method that allows op parser impls to know how many
results are expected.
- Adds a OpAsmPrinter::printOperand overload that takes an explicit stream.
- Adds a test.string_attr_pretty_name operation that uses these hooks to
do fancy things with the result name.
Reviewers: rriddle!
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76205
The current mechanism for identifying is a bit hacky and extremely adhoc, i.e. we explicit check 1-result, 0-operand, no side-effect, and always foldable and then assume that this is a constant. Adding a trait adds structure to this, and makes checking for a constant much more efficient as we can guarantee that all of these things have already been verified.
Differential Revision: https://reviews.llvm.org/D76020
Summary: In some situations the name of the attribute is not representable as a bare-identifier, this revision adds support for those cases by formatting the name as a string instead. This has the added benefit of removing the identifier regex from the verifier.
Differential Revision: https://reviews.llvm.org/D75973
This revision introduces the infrastructure for defining side-effects and attaching them to operations. This infrastructure allows for defining different types of side effects, that don't interact with each other, but use the same internal mechanisms. At the base of this is an interface that allows operations to specify the different effect instances that are exhibited by a specific operation instance. An effect instance is comprised of the following:
* Effect: The specific effect being applied.
For memory related effects this may be reading from memory, storing to memory, etc.
* Value: A specific value, either operand/result/region argument, the effect pertains to.
* Resource: This is a global entity that represents the domain within which the effect is being applied.
MLIR serves many different abstractions, which cover many different domains. Simple effects are may have very different context, for example writing to an in-memory buffer vs a database. This revision defines uses this infrastructure to define a set of initial MemoryEffects. The are effects that generally correspond to memory of some kind; Allocate, Free, Read, Write.
This set of memory effects will be used in follow revisions to generalize various parts of the compiler, and make others more powerful(e.g. DCE).
This infrastructure was originally proposed here:
https://groups.google.com/a/tensorflow.org/g/mlir/c/v2mNl4vFCUM
Differential Revision: https://reviews.llvm.org/D74439
Summary:
This revision removes all of the functionality related to successor operands on the core Operation class. This greatly simplifies a lot of handling of operands, as well as successors. For example, DialectConversion no longer needs a special "matchAndRewrite" for branching terminator operations.(Note, the existing method was also broken for operations with variadic successors!!)
This also enables terminator operations to define their own relationships with successor arguments, instead of the hardcoded "pass-through" behavior that exists today.
Differential Revision: https://reviews.llvm.org/D75318
This attribute details the segment sizes for operand groups within the operation. This revision add support for automatically populating this attribute in the declarative parser.
Differential Revision: https://reviews.llvm.org/D75315
A previous commit added support for integer signedness in C++
IntegerType. This change introduces ODS definitions for
integer types and integer (element) attributes w.r.t. signedness.
This commit also updates various existing definitions' descriptions
to mention signless where suitable to make it more clear.
Positive and non-negative integer attributes are removed to avoid
the explosion of subclasses. Instead, one should use more atmoic
constraints together with Confined to model that. For example,
`Confined<..., [IntPositive]>`.
Differential Revision: https://reviews.llvm.org/D75610
Summary:
This adds an rsqrt op to the standard dialect, and lowers
it as 1 / sqrt to the LLVM dialect.
Differential Revision: https://reviews.llvm.org/D75353
Summary: This allows for attaching the attribute to CmpF as a proper argument, and thus enables the removal of a bunch of c++ code.
Differential Revision: https://reviews.llvm.org/D75539
Summary: For example, DenseElementsAttr currently does not properly round-trip unsigned integer values.
Differential Revision: https://reviews.llvm.org/D75374
Summary: bfloat16 is stored internally as a double, so we can't direct use Type::getIntOrFloatBitWidth.
Differential Revision: https://reviews.llvm.org/D75133
Summary:
The RFC for this op is here: https://llvm.discourse.group/t/rfc-add-std-atomic-rmw-op/489
The std.atmomic_rmw op provides a way to support read-modify-write
sequences with data race freedom. It is intended to be used in the lowering
of an upcoming affine.atomic_rmw op which can be used for reductions.
A lowering to LLVM is provided with 2 paths:
- Simple patterns: llvm.atomicrmw
- Everything else: llvm.cmpxchg
Differential Revision: https://reviews.llvm.org/D74401
This revision add support for formatting successor variables in a similar way to operands, attributes, etc.
Differential Revision: https://reviews.llvm.org/D74789
This allows for injecting type constraints that are not direct 1-1 mappings, for example when one type is equal to the element type of another. This allows for moving over several more parsers to the declarative form.
Differential Revision: https://reviews.llvm.org/D74648
Thus far IntegerType has been signless: a value of IntegerType does
not have a sign intrinsically and it's up to the specific operation
to decide how to interpret those bits. For example, std.addi does
two's complement arithmetic, and std.divis/std.diviu treats the first
bit as a sign.
This design choice was made some time ago when we did't have lots
of dialects and dialects were more rigid. Today we have much more
extensible infrastructure and different dialect may want different
modelling over integer signedness. So while we can say we want
signless integers in the standard dialect, we cannot dictate for
others. Requiring each dialect to model the signedness semantics
with another set of custom types is duplicating the functionality
everywhere, considering the fundamental role integer types play.
This CL extends the IntegerType with a signedness semantics bit.
This gives each dialect an option to opt in signedness semantics
if that's what they want and helps code sharing. The parser is
modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as
signed and unsigned integer types, respectively, leaving the
original `i[1-9][0-9]*` to continue to mean no indication over
signedness semantics. All existing dialects are not affected (yet)
as this is a feature to opt in.
More discussions can be found at:
https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ
Differential Revision: https://reviews.llvm.org/D72533
Summary: DenseElementsAttr is used to store tensor data, which in some cases can become extremely large(100s of mb). In these cases it is much more efficient to format the data as a string of hex values instead.
Differential Revision: https://reviews.llvm.org/D74922
Summary:
This trait takes three arguments: lhs, rhs, transformer. It verifies that the type of 'rhs' matches the type of 'lhs' when the given 'transformer' is applied to 'lhs'. This allows for adding constraints like: "the type of 'a' must match the element type of 'b'". A followup revision will add support in the declarative parser for using these equality constraints to port more c++ parsers to the declarative form.
Differential Revision: https://reviews.llvm.org/D74647
Defines a tablegen class RankedIntElementsAttr. This is an integer
version of RankedFloatElementsAttr.
Differential Revision: https://reviews.llvm.org/D73764
Summary: In some edge cases the default APFloat printer will generate something that we can't parse back in. In these cases, fallback to using hex instead.
Differential Revision: https://reviews.llvm.org/D74181
Summary: This pass deletes all symbols that are found to be unreachable. This is done by computing the set of operations that are known to be live, propagating that liveness to other symbols, and then deleting all symbols that are not within this live set.
Differential Revision: https://reviews.llvm.org/D72482
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
Summary: bfloat16 doesn't have a valid APFloat format, so we have to use double semantics when storing it. This change makes sure that hexadecimal values can be round-tripped properly given this fact.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D72667
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
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
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
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
Rename the 'shlis' operation in the standard dialect to 'shift_left'. Add tests
for this operation (these have been missing so far) and add a lowering to the
'shl' operation in the LLVM dialect.
Add also 'shift_right_signed' (lowered to LLVM's 'ashr') and 'shift_right_unsigned'
(lowered to 'lshr').
The original plan was to name these operations 'shift.left', 'shift.right.signed'
and 'shift.right.unsigned'. This works if the operations are prefixed with 'std.'
in MLIR assembly. Unfortunately during import the short form is ambigous with
operations from a hypothetical 'shift' dialect. The best solution seems to omit
dots in standard operations for now.
Closestensorflow/mlir#226
PiperOrigin-RevId: 286803388
This is the block argument equivalent of the existing `getAsmResultNames` hook.
Closestensorflow/mlir#329
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/329 from plaidml:flaub-region-arg-names fc7876f2d1335024e441083cd25263fd6247eb7d
PiperOrigin-RevId: 286523299
Introduce affine.prefetch: op to prefetch using a multi-dimensional
subscript on a memref; similar to affine.load but has no effect on
semantics, but only on performance.
Provide lowering through std.prefetch, llvm.prefetch and map to llvm's
prefetch instrinsic. All attributes reflected through the lowering -
locality hint, rw, and instr/data cache.
affine.prefetch %0[%i, %j + 5], false, 3, true : memref<400x400xi32>
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Closestensorflow/mlir#225
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/225 from bondhugula:prefetch 4c3b4e93bc64d9a5719504e6d6e1657818a2ead0
PiperOrigin-RevId: 286212997
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>
Closestensorflow/mlir#202
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/202 from bondhugula:affine b13fcb2f1c00a39ca5434613a02408e085a80e77
PiperOrigin-RevId: 284866710
This CL adds support for building matchers recursively.
The following matchers are provided:
1. `m_any()` can match any value
2. `m_val(Value *)` binds to a value and must match it
3. `RecursivePatternMatcher<OpType, Matchers...>` n-arity pattern that matches `OpType` and whose operands must be matched exactly by `Matchers...`.
This allows building expression templates for patterns, declaratively, in a very natural fashion.
For example pattern `p9` defined as follows:
```
auto mul_of_muladd = m_Op<MulFOp>(m_Op<MulFOp>(), m_Op<AddFOp>());
auto mul_of_anyadd = m_Op<MulFOp>(m_any(), m_Op<AddFOp>());
auto p9 = m_Op<MulFOp>(m_Op<MulFOp>(
mul_of_muladd, m_Op<MulFOp>()),
m_Op<MulFOp>(mul_of_anyadd, mul_of_anyadd));
```
Successfully matches `%6` in:
```
%0 = addf %a, %b: f32
%1 = addf %a, %c: f32 // matched
%2 = addf %c, %b: f32
%3 = mulf %a, %2: f32 // matched
%4 = mulf %3, %1: f32 // matched
%5 = mulf %4, %4: f32 // matched
%6 = mulf %5, %5: f32 // matched
```
Note that 0-ary matchers can be used as leaves in place of n-ary matchers. This alleviates from passing explicit `m_any()` leaves.
In the future, we may add extra patterns to specify that operands may be matched in any order.
PiperOrigin-RevId: 284469446
I found that when running crash reproducers, the elided elementsattr's
would prevent parsing the IR repro. I found myself manually going and
replacing the "..." with some valid IR.
With this change, we now print elided attrs as `opaque<"", "0xDEADBEEF">`
to clearly delineate them as being elided while still being parseable.
PiperOrigin-RevId: 283781806
As described in the documentation, ViewOp is expected to take an optional
dynamic offset followed by a list of dynamic sizes. However, the ViewOp parser
did not include a check for the offset being a single value and accepeted a
list of values instead.
Furthermore, several tests have been exercising the wrong syntax of a ViewOp,
passing multiple values to the dyanmic stride list, which was not caught by the
parser. The trailing values could have been erronously interpreted as dynamic
sizes. This is likely due to resyntaxing of the ViewOp, with the previous
syntax taking the list of sizes before the offset. Update the tests to use the
syntax with the offset preceding the sizes.
Worse, the conversion of ViewOp to the LLVM dialect assumed the wrong order of
operands with offset in the trailing position, and erronously relied on the
permissive parsing that interpreted trailing dynamic offset values as leading
dynamic sizes. Fix the lowering to use the correct order of operands.
PiperOrigin-RevId: 283532506
Certain operations can have multiple variadic operands and their size
relationship is not always known statically. For such cases, we need
a per-op-instance specification to divide the operands into logical
groups or segments. This can be modeled by attributes.
This CL introduces C++ trait AttrSizedOperandSegments for operands and
AttrSizedResultSegments for results. The C++ trait just guarantees
such size attribute has the correct type (1D vector) and values
(non-negative), etc. It serves as the basis for ODS sugaring that
with ODS argument declarations we can further verify the number of
elements match the number of ODS-declared operands and we can generate
handy getter methods.
PiperOrigin-RevId: 282467075
Memref_cast supports cast from static shape to dynamic shape
memrefs. The same should be true for strides as well, i.e a memref
with static strides can be casted to a memref with dynamic strides.
PiperOrigin-RevId: 282381862
Due to legacy reasons, a newline character followed by two spaces was always
inserted before the attributes of the function Op in pretty form. This breaks
formatting when functions are nested in some other operations. Don't print the
newline and just put the attributes on the same line, which is also more
consistent with module Op. Line breaking aware of indentation can be introduced
separately into the parser if deemed useful.
PiperOrigin-RevId: 281721793
The current SubViewOp specification allows for either all offsets,
shape and stride to be dynamic or all of them to be static. There are
opportunities for more fine-grained canonicalization based on which of
these are static. For example, if the sizes are static, the result
memref is of static shape. The specification of SubViewOp is modified
to allow on or more of offsets, shapes and strides to be statically
specified. The verification is updated to ensure that the result type
of the subview op is consistent with which of these are static and
which are dynamic.
PiperOrigin-RevId: 281560457
This interface provides more fine-grained hooks into the AsmPrinter than the dialect interface, allowing for operations to define the asm name to use for results directly on the operations themselves. The hook is also expanded to enable defining named result "groups". Get a special name to use when printing the results of this operation.
The given callback is invoked with a specific result value that starts a
result "pack", and the name to give this result pack. To signal that a
result pack should use the default naming scheme, a None can be passed
in instead of the name.
For example, if you have an operation that has four results and you want
to split these into three distinct groups you could do the following:
setNameFn(getResult(0), "first_result");
setNameFn(getResult(1), "middle_results");
setNameFn(getResult(3), ""); // use the default numbering.
This would print the operation as follows:
%first_result, %middle_results:2, %0 = "my.op" ...
PiperOrigin-RevId: 281546873
This CL moves VectorOps to Tablegen and cleans up the implementation.
This is almost NFC but 2 changes occur:
1. an interface change occurs in the padding value specification in vector_transfer_read:
the value becomes non-optional. As a shortcut we currently use %f0 for all paddings.
This should become an OpInterface for vectorization in the future.
2. the return type of vector.type_cast is trivial and simplified to `memref<vector<...>>`
Relevant roundtrip and invalid tests that used to sit in core are moved to the vector dialect.
The op documentation is moved to the .td file.
PiperOrigin-RevId: 280430869
Expand local scope printing to skip printing aliases as aliases are printed out at the top of a module and may not be part of the output generated by local scope print.
PiperOrigin-RevId: 280278617
This is a quite complex operation that users are likely to attempt to write
themselves and get wrong (citation: users=me).
Ideally, we could pull this into FunctionLike, but for now, the
FunctionType rewriting makes it FuncOp specific. We would need some hook
for rewriting the function type (which for LLVM's func op, would need to
rewrite the underlying LLVM type).
PiperOrigin-RevId: 280234164
The current implementation silently fails if the '@' identifier isn't present, making it similar to the 'optional' parse methods. This change renames the current implementation to 'Optional' and adds a new 'parseSymbolName' that emits an error.
PiperOrigin-RevId: 280214610
It is often helpful to inspect the operation that the error/warning/remark/etc. originated from, especially in the context of debugging or in the case of a verifier failure. This change adds an option 'mlir-print-op-on-diagnostic' that attaches the operation as a note to any diagnostic that is emitted on it via Operation::emit(Error|Warning|Remark). In the case of an error, the operation is printed in the generic form.
PiperOrigin-RevId: 280021438
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
This operation is a companion operation to the std.view operation added as proposed in "Updates to the MLIR MemRefType" RFC.
PiperOrigin-RevId: 279766410
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 constraint can be used to limit a SymbolRefAttr to point
to a specific kind of op in the closest parent with a symbol table.
PiperOrigin-RevId: 278001364
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 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
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
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
'_' 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
1. Rename test ops referencing operand to index from 0 consistent with how we index elsewhere.
2. Don't limit type checking that functions for all shaped types to only tensors.
3. Don't limit (element) type checking functions and add tests for scalars.
4. Remove SSA values that don't do anything.
PiperOrigin-RevId: 273917608
Currently SameOperandsAndResultShape trait allows operands to have tensor<*xf32> and tensor<2xf32> but doesn't allow tensor<?xf32> and tensor<10xf32>.
Also, use the updated shape compatibility helper function in TensorCastOp::areCastCompatible method.
PiperOrigin-RevId: 273658336
This enhances the symbol table utility methods to handle the case where an unknown operation may define a symbol table. When walking symbols, we now collect all symbol uses before allowing the user to iterate. This prevents the user from assuming that all symbols are actually known before performing a transformation.
PiperOrigin-RevId: 273651963
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
MLIR uses symbol references to model references to many global entities, such as functions/variables/etc. Before this change, there is no way to actually reason about the uses of such entities. This change provides a walker for symbol references(via SymbolTable::walkSymbolUses), as well as 'use_empty' support(via SymbolTable::symbol_use_empty). It also resolves some deficiencies in the LangRef definition of SymbolRefAttr, namely the restrictions on where a SymbolRefAttr can be stored, ArrayAttr and DictionaryAttr, and the relationship with operations containing the SymbolTable trait.
PiperOrigin-RevId: 273549331
Some modules may have extremely large ElementsAttrs, which makes debugging involving IR dumping extremely slow and painful. This change adds a flag that will elide ElementsAttrs with a "large"(as defined by the user) number of elements by printing "..." instead of the element data.
PiperOrigin-RevId: 273413100
See RFC: https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/xE2IzfhE3Wg.
Opaque location stores two pointers, one of them points to some data structure that is external to MLIR, and the other one is unique for each type and represents type id of that data structure. OpaqueLoc also stores an optional location that can be used if the first one is not suitable.
OpaqueLoc is managed similar to FileLineColLoc. It is passed around by MLIR transformations and can be used in compound locations like CallSiteLoc.
PiperOrigin-RevId: 273266510
This allows confirming that a scalar argument has the same element type as a shaped one. It's easy to validate a type is shaped on its own if that's desirable, so this shouldn't make that use case harder. This matches the behavior of other traits that operate on element type (e.g. AllElementTypesMatch). Also this makes the code simpler because now we just use getElementTypeOrSelf.
Verified that all uses in core already check the type is shaped in another way.
PiperOrigin-RevId: 273068507
1. Rename a few ops to make it clear they operate on *element* types.
2. Remove unused and generic operand and result ODS names (e.g. $res, $arg, $input). These are just clutter and don't make the op definitions any clearer.
3. Give test cases with duplicate names clearer names.
4. Add missing test case for no operands in SameOperandAndResultElementType.
PiperOrigin-RevId: 273067933
This CL implements the last remaining bit of the [strided memref proposal](https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/MaL8m2nXuio).
The syntax is a bit more explicit than what was originally proposed and resembles:
`memref<?x?xf32, offset: 0 strides: [?, 1]>`
Nonnegative strides and offsets are currently supported. Future extensions will include negative strides.
This also gives a concrete example of syntactic sugar for the ([RFC] Proposed Changes to MemRef and Tensor MLIR Types)[https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/-wKHANzDNTg].
The underlying implementation still uses AffineMap layout.
PiperOrigin-RevId: 272717437
Modules are now Ops and, as such, can be nested. They do not produce an SSA
value so there is no possibility to refer to them in the IR. Introduce support
for symbol names attached to the module Op so that it can be referred to using
SymbolRefAttrs. The name is optional, for example the implicit top-level module
does not have a name.
PiperOrigin-RevId: 272671600
As specified in the MLIR language reference and rationale documents, `memref`
types should not be allowed to have `index` as element types. As observed in
https://groups.google.com/a/tensorflow.org/forum/#!msg/mlir/P49hVWqTMNc/nW89a4i_AgAJ
this restriction was lifted when canonicalization unit tests for affine
operations were introduced, without sufficient motivation to lift the
restriction itself. The test in question can be trivially rewritten (return
the value from a function instead of storing it to prevent DCE from removing
the producer operation) and the restriction put back in place.
If `memref<...x index>` is relevant for some use cases, the relaxation of the
type system can be implemented separately with appropriate modifications to the
documentation.
PiperOrigin-RevId: 272607043
- also remove stale terminology/references in docs
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Closestensorflow/mlir#148
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/148 from bondhugula:cleanup e846b641a3c2936e874138aff480a23cdbf66591
PiperOrigin-RevId: 271618279
- introduce splat op in standard dialect (currently for int/float/index input
type, output type can be vector or statically shaped tensor)
- implement LLVM lowering (when result type is 1-d vector)
- add constant folding hook for it
- while on Ops.cpp, fix some stale names
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Closestensorflow/mlir#141
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/141 from bondhugula:splat 48976a6aa0a75be6d91187db6418de989e03eb51
PiperOrigin-RevId: 270965304
The existing logic to parse spirv::StructTypes is very brittle. This
change simplifies the parsing logic a lot. The simplification also
allows for memberdecorations to be separated by commas instead of
spaces (which was an artifact of the existing parsing logic). The
change also needs a modification to mlir::parseType to return the
number of chars parsed. Adding a new parseType method to do so.
Also allow specification of spirv::StructType with no members.
PiperOrigin-RevId: 270739672
This adds sign- and zero-extension and truncation of integer types to the
standard dialects. This allows to perform integer type conversions without
having to go to the LLVM dialect and introduce custom type casts (between
standard and LLVM integer types).
Closestensorflow/mlir#134
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/134 from ombre5733:sext-zext-trunc-in-std c7657bc84c0ca66b304e53ec03797e09152e4d31
PiperOrigin-RevId: 270479722
This CL adds a new FloatElementsAttr definition to ODS for float
elements attributes of a certain type.
Tests are added to show both verification and how to use it in patterns.
PiperOrigin-RevId: 270455487
This modifies DominanceInfo::properlyDominates(Value *value, Operation *op) to return false if the value is defined by a parent operation of 'op'. This prevents using values defined by the parent operation from within any child regions.
PiperOrigin-RevId: 269934920
This is useful in several cases, for example a user may want to sugar the syntax of a string(as we do with custom operation syntax), or avoid many nested ifs for parsing a set of known keywords.
PiperOrigin-RevId: 269695451
This method parses an operation in its generic form, from the current parser
state. This is the symmetric of OpAsmPrinter::printGenericOp(). An immediate
use case is illustrated in the test dialect, where an operation wraps another
one in its region and makes use of a single-line pretty-print form.
PiperOrigin-RevId: 267930869
Tweak to the pretty type parser to recognize that `->` is a special token that
shouldn't be split into two characters. This change allows dialect
types to wrap function types as in `!my.ptr_type<(i32) -> i32>`.
Closestensorflow/mlir#105
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/105 from schweitzpgi:parse-arrow 8b2d768053f419daae5a1a864121a44c4319acbe
PiperOrigin-RevId: 265986240
This commit adds `PositiveI32Attr` and `PositiveI64Attr` to match positive
integers but not zero nor negative integers. This commit also adds
`HasAnyRankOfPred` to match tensors with the specified ranks.
PiperOrigin-RevId: 264867046
- fix missing check while simplifying an expression with floordiv to a
mod
- fixes issue tensorflow/mlir#82
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Closestensorflow/mlir#84
PiperOrigin-RevId: 264338353
This will allow for naming values the same as existing SSA values for regions attached to operations that are isolated from above. This fits in with how the system already allows separate name scopes for sibling regions. This name shadowing can be enabled in the custom parser of operations by setting the 'enableNameShadowing' flag to true when calling 'parseRegion'.
%arg = constant 10 : i32
foo.op {
%arg = constant 10 : i32
}
PiperOrigin-RevId: 264255999
LLVM function type has first-class support for variadic functions. In the
current lowering pipeline, it is emulated using an attribute on functions of
standard function type. In LLVMFuncOp that has LLVM function type, this can be
modeled directly. Introduce parsing support for variadic arguments to the
function and use it to support variadic function declarations in LLVMFuncOp.
Function definitions are currently not supported as that would require modeling
va_start/va_end LLVM intrinsics in the dialect and we don't yet have a
consistent story for LLVM intrinsics.
PiperOrigin-RevId: 262372651
Now that modules are also operations, nothing prevents one from defining SSA
values in the module. Doing so in an implicit top-level module, i.e. outside
of a `module` operation, was leading to a crash because the implicit module was
not associated with an SSA name scope. Create a name scope before parsing the
top-level module to fix this.
PiperOrigin-RevId: 262366891
Verification complained when using zero-dimensional memrefs in
affine.load, affine.store, std.load and std.store. This PR extends
verification so that those memrefs can be used.
Closestensorflow/mlir#58
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/58 from dcaballe:dcaballe/zero-dim 49bcdcd45c52c48beca776431328e5ce551dfa9e
PiperOrigin-RevId: 262164916
Extend the recently introduced support for hexadecimal float literals to tensor
literals, which may also contain special floating point values such as
infinities and NaNs.
Modify TensorLiteralParser to store the list of tokens representing values
until the type is parsed instead of trying to guess the tensor element type
from the token kinds (hexadecimal values can be either integers or floats, and
can be mixed with both). Maintain the error reports as close as possible to
the existing implementation to avoid disturbing the tests. They can be
improved in a separate clean-up if deemed necessary.
PiperOrigin-RevId: 260794716
MLIR does not have support for parsing special floating point values such as
infinities and NaNs. If programmatically constructed, these values are printed
as NaN and (+-)Inf and cannot be parsed back. Add parser support for
hexadecimal literals in float attributes, following LLVM IR. The literal
corresponds to the in-memory representation of the floating point value.
IEEE 754 defines a range of possible values for NaNs, storing the bitwise
representation allows MLIR to properly roundtrip NaNs with different bit values
of significands.
The initial version of this commit was missing support for float literals that
used to be printed in decimal notation as a fallback, but ended up being
printed in hexadecimal format which became the fallback for special values.
The decimal fallback behavior was not exercised by tests. It is currently
reinstated and tested by the newly added test @f32_potential_precision_loss in
parser.mlir.
PiperOrigin-RevId: 260790900
The code was written with the assumption that on failure an error would be
issued by another verifier. However verification is stopping on the first
failure which lead to an empty output. Instead we make sure an error is
displayed.
Also add tests in the test dialect for this trait.
PiperOrigin-RevId: 260541290
MLIR does not have support for parsing special floating point values such as
infinities and NaNs. If programmatically constructed, these values are printed
as NaN and (+-)Inf and cannot be parsed back. Add parser support for
hexadecimal literals in float attributes, following LLVM IR. The literal
corresponds to the in-memory representation of the floating point value.
IEEE 754 defines a range of possible values for NaNs, storing the bitwise
representation allows MLIR to properly roundtrip NaNs with different bit values
of significands.
PiperOrigin-RevId: 260018802
Conversion from integers (window or input size, padding etc) to floating point is required to express many ML kernels, for example average pooling.
PiperOrigin-RevId: 259575284
In the trait verifier of SingleBlockImplicitTerminator, report the name of the
unexpected terminator op found in the end of the block in addition to the name
of the expected terminator op. This may simplify debugging, especially in
cases where the terminator is omitted for brevity and/or after a long series of
conversions.
PiperOrigin-RevId: 259287452
Several groups of operations in different dialects (e.g. AffineForOp,
AffineIfOp; loop::ForOp, loop::IfOp) share the requirement for their regions to
contain 0 or 1 block, and for blocks to always have a specific terminator type.
Furthermore, this terminator may be omitted from the custom syntax. Generalize
this behavior into OpTrait::SingleBlockImplicitTerminator, parameterized by the
terminator operation type. This trait provides the verifier that checks the
presence of the terminator, and utility functions adding the terminator in case
of absence.
PiperOrigin-RevId: 258957180
We already parse boolean "true"/"false" as ElementsAttr elements.
This CL makes it round-trippable that we are printing the same way.
PiperOrigin-RevId: 258784962
This cl standardizes the printing of the type of dialect attributes to work the same as other attribute kinds. The type of dialect attributes will trail the dialect specific portion:
`#` dialect-namespace `<` attr-data `>` `:` type
The attribute parsing hooks on Dialect have been updated to take an optionally null expected type for the attribute. This matches the respective parseAttribute hooks in the OpAsmParser.
PiperOrigin-RevId: 258661298
These ops should not belong to the std dialect.
This CL extracts them in their own dialect and updates the corresponding conversions and tests.
PiperOrigin-RevId: 258123853
This changes the top-level module parser to handle the case where the top-level module is defined with the module operation syntax, i.e:
module ... {
}
The printer is also updated to always print the top-level module in this form. This allows for cleanly round-tripping the location and attributes of the top-level module.
PiperOrigin-RevId: 257492069
This was an arbitrary restriction caused by the way that modules were printed. Now that that has been fixed, this restriction can be removed.
PiperOrigin-RevId: 257240329
Change the AsmPrinter to number values breadth-first so that values in adjacent regions can have the same name. This allows for ModuleOp to contain operations that produce results. This also standardizes the special name of region entry arguments to "arg[0-9+]" now that Functions are also operations.
PiperOrigin-RevId: 257225069
This CL adds an "std.if" op to represent an if-then-else construct whose condition is an arbitrary value of type i1.
This is necessary to lower all the existing examples from affine and linalg to std.for + std.if.
This CL introduces the op and adds the relevant positive and negative unit test. Lowering will be done in a separate followup CL.
PiperOrigin-RevId: 256649138
This is an important step in allowing for the top-level of the IR to be extensible. FuncOp and ModuleOp contain all of the necessary functionality, while using the existing operation infrastructure. As an interim step, many of the usages of Function and Module, including the name, will remain the same. In the future, many of these will be relaxed to allow for many different types of top-level operations to co-exist.
PiperOrigin-RevId: 256427100
This CL is the first step of a refactoring unification of the control flow abstraction used in different dialects. The `std.for` loop accepts unrestricted indices to encode min, max and step and will be used as a common abstraction on the way to lower level dialects.
PiperOrigin-RevId: 256331795
In ODS, right now we use StringAttrs to emulate enum attributes. It is
suboptimal if the op actually can and wants to store the enum as a
single integer value; we are paying extra cost on storing and comparing
the attribute value.
This CL introduces a new enum attribute subclass that are backed by
IntegerAttr. The downside with IntegerAttr-backed enum attributes is
that the assembly form now uses integer values, which is less obvious
than the StringAttr-backed ones. However, that can be remedied by
defining custom assembly form with the help of the conversion utility
functions generated via EnumsGen.
Choices are given to the dialect writers to decide which one to use for
their enum attributes.
PiperOrigin-RevId: 255935542
This functionality is now moved to a new class, ModuleManager. This class allows for inserting functions into a module, and will auto-rename them on insert to ensure a unique name. This now means that users adding new functions to a module must ensure that the function name is unique, as the Module will no longer do it automatically. This also means that Module::getNamedFunction now operates in O(N) instead of the O(c) time it did before. This simplifies the move of Modules to Operations as the ModuleOp will not be able to have this functionality.
PiperOrigin-RevId: 255846088
The current syntax separates the name and value with ':', but ':' is already overloaded by several other things(e.g. trailing types). This makes the syntax difficult to parse in some situtations:
Old:
"foo: 10 : i32"
New:
"foo = 10 : i32"
PiperOrigin-RevId: 255097928
This is the standard syntax for types on operations, and is also already used by IntegerAttr and FloatAttr.
Example:
dense<5> : tensor<i32>
dense<[3]> : tensor<1xi32>
PiperOrigin-RevId: 255069157
The error would look like:
path/filename.mlir:32:23: error: use of value '%28' expects different type than prior uses: ''i32'' vs ''!_tf.control''
PiperOrigin-RevId: 254874859
The ModuleOp contains a single region that must contain a single block. This block must be terminated by a new pseudo operation 'module_terminator'. The syntax for this operations is as follows:
`module` (`attributes` attr-dict)? region
Example:
module {
...
}
module attributes { ... } {
...
}
PiperOrigin-RevId: 254513752
This will allow for locations to be used in the same contexts as attributes. Given that attributes are nullable types, the 'Location' class now represents a non-nullable wrapper around a 'LocationAttr'. This preserves the desired semantics we have for non-optional locations.
PiperOrigin-RevId: 254505278
This name has caused some confusion because it suggests that it's running op verification (and that this verification isn't getting run by default).
PiperOrigin-RevId: 254035268
Index types integers of platform-specific bit width. They are used to index
memrefs and as loop induction variables, however they could not be obtained
from an integer until now, making it virtually impossible to express indirect
accesses (given that memrefs of indices are not allowed) or data-dependent
loops. Introduce `std.index_cast` to transform indices into integers and vice
versa. The semantics of this cast is to sign-extend when casting to a wider
integer, and to truncate when casting to a narrower integer. It belongs to
StandardOps because both types it operates on are standard types, and because
its results are likely to be used in std.load and std.store.
Introduce llvm.sext, llvm.zext and llvm.trunc operations to the LLVM dialect.
Provide the conversion of `std.index_cast` to llvm.sext or llvm.trunc,
depending on the actual bitwidth of `index` known during the conversion.
PiperOrigin-RevId: 253624100
This CL enables verification code generation for variadic operands and results.
In verify(), we use fallback getter methods to access all the dynamic values
belonging to one static variadic operand/result to reuse the value range
calculation there.
PiperOrigin-RevId: 252288219
Similar to arguments and results, now we require region definition in ops to
be specified as a DAG expression with the 'region' operator. This way we can
specify the constraints for each region and optionally give the region a name.
Two kinds of region constraints are added, one allowing any region, and the
other requires a certain number of blocks.
--
PiperOrigin-RevId: 250790211
This is in preparation for making MemRef a ShapedType. In general, a shaped type should be anything with shape, rank, and element type properties, so use sites shouldn't assume more than that.
I also pulled the trailing comma parsing out the parseElementsLiteralType (new name) method. It seems weird to have the method parse the type + a trailing comma, even if all call sites currently need that. It's surprising behavior without looking at the implementation.
--
PiperOrigin-RevId: 250558363
* There is no longer a need to explicitly remap function attrs.
- This removes a potentially expensive call from the destructor of Function.
- This will enable some interprocedural transformations to now run intraprocedurally.
- This wasn't scalable and forces dialect defined attributes to override
a virtual function.
* Replacing a function is now a trivial operation.
* This is a necessary first step to representing functions as operations.
--
PiperOrigin-RevId: 249510802
We now have sufficient extensibility in dialects to move attribute components
such as SDBM out of the core IR into a dedicated dialect and make them
optional. Introduce an SDBM dialect and move the code. This is a mostly
non-functional change.
--
PiperOrigin-RevId: 249244802
SDBM has an output format representing the unterlying matrix and stripe
expressions. Move the SDBM tests from unit testing framework to
FileCheck-based tests, printing them to the standard output and using FileCheck
to test the output. Tests that check the API proper (e.g. that SDBM
expressions have a specific subtype) and that rely on non-syntatic properties
(equality of the set of constraints) are not ported.
--
PiperOrigin-RevId: 249006055
Make it clear that it cares about the aggregate type being a vector or tensor and not just that it has a shape.
Remove redundant validation from the custom method that is now covered by the tablegen'ed verification
This is related to making MemRefs a ShapedType as well.
--
PiperOrigin-RevId: 248610443
This is in preparation for making it also support/be a parent class of MemRefType. MemRefs have similar shape/rank/element semantics and it would be useful to be able to use these same utilities for them.
This CL should not change any semantics and only change variables, types, string literals, and comments. In follow-up CLs I will prepare all callers to handle MemRef types or remove their dependence on ShapedType.
Discussion/Rationale in https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/cHLoyfGu8y8
--
PiperOrigin-RevId: 248476449
This closely mirrors the llvm fcmp instruction, defining 16 different predicates
Constant folding is unsupported for NaN and Inf because there's no way to represent those as constants at the moment
--
PiperOrigin-RevId: 246932358
`#` alias `=` attribute-value
This also allows for dialects to define aliases for attributes in the AsmPrinter. The printer supports two types of attribute aliases, 'direct' and 'kind'.
* Direct aliases are synonymous with the current support for type aliases, i.e. this maps an alias to a specific instance of an attribute.
// A direct alias ("foo_str") for the string attribute "foo".
#foo_str = "foo"
* Kind aliases generates unique names for all instances of a given attribute kind. The generated aliases are of the form: `alias[0-9]+`.
// A kind alias ("strattr") for all string attributes could generate.
#strattr0 = "foo"
#strattr1 = "bar"
...
#strattrN = "baz"
--
PiperOrigin-RevId: 246851916
The generic form of operations currently supports optional regions to be
located after the operation type. As we are going to add a type to each
region in a leading position in the region syntax, similarly to functions, it
becomes ambiguous to have regions immediately after the operation type. Put
regions between operands the optional list of successors in the generic
operation syntax and wrap them in parentheses. The effect on the exisitng IR
syntax is minimal since only three operations (`affine.for`, `affine.if` and
`gpu.kernel`) currently use regions.
--
PiperOrigin-RevId: 246787087
none-type ::= `none`
The `none` type is a unit type, i.e. a type with exactly one possible value, where its value does not have a defined dynamic representation.
--
PiperOrigin-RevId: 245599248
A unit attribute is an attribute that represents a value of `unit` type. The
`unit` type allows only one value forming a singleton set. This attribute value
is used to represent attributes that only have meaning from their existence.
One example of such an attribute could be the `swift.self` attribute. This attribute indicates that a function parameter is the self/context
parameter. It could be represented as a boolean attribute(true or false), but a
value of false doesn't really bring any value. The parameter either is the
self/context or it isn't.
```mlir {.mlir}
// A unit attribute defined with the `unit` value specifier.
func @verbose_form(i1 {unitAttr : unit})
// A unit attribute can also be defined without the `unit` value specifier.
func @simple_form(i1 {unitAttr})
```
--
PiperOrigin-RevId: 245254045
other characters within the <>'s now that we can. This will allow quantized
types to use the pretty syntax (among others) after a few changes.
--
PiperOrigin-RevId: 243521268
There are no empty lines in output for three of these directives so removed
them and replaced the remaining one with 'CHECK-NOT:' as otherwise it is
failing with the following error.
error: found 'CHECK-EMPTY' without previous 'CHECK: line
TESTED = n/a
PiperOrigin-RevId: 243288605
This adds parsing, printing and some folding/canonicalization.
Also extends rewriting of subi %0, %0 to handle vectors and tensors.
--
PiperOrigin-RevId: 242448164
making the IR dumps much nicer.
This is part 2/3 of the path to making dialect types more nice. Part 3/3 will
slightly generalize the set of characters allowed in pretty types and make it
more principled.
--
PiperOrigin-RevId: 242249955
restricted grammar. This will make certain common types much easier to read.
This is part tensorflow/mlir#1 of 2, which allows us to accept the new syntax. Part 2 will
change the asmprinter to automatically use it when appropriate, which will
require updating a bunch of tests.
This is motivated by the EuroLLVM tutorial and cleaning up the LLVM dialect aesthetics a bit more.
--
PiperOrigin-RevId: 242234821
Example:
func @unknown_std_op() {
%0 = "std.foo_bar_op"() : () -> index
return
}
Will result in:
error: unregistered operation 'std.foo_bar_op' found in dialect ('std') that does not allow unknown operations
--
PiperOrigin-RevId: 241266009
have no standard ops for working with these yet, this is simply enough to
represent and round trip them in the printer and parser.
--
PiperOrigin-RevId: 241102728
Example:
%call:2 = call @multi_return() : () -> (f32, i32)
use(%calltensorflow/mlir#0, %calltensorflow/mlir#1)
This cl also adds parser support for uniquely named result values. This means that a test writer can now write something like:
%foo, %bar = call @multi_return() : () -> (f32, i32)
use(%foo, %bar)
Note: The printer will still print the collapsed form.
PiperOrigin-RevId: 240860058
Due to legacy reasons (ML/CFG function separation), regions in affine control
flow operations require contained blocks not to have terminators. This is
inconsistent with the notion of the block and may complicate code motion
between regions of affine control operations and other regions.
Introduce `affine.terminator`, a special terminator operation that must be used
to terminate blocks inside affine operations and transfers the control back to
he region enclosing the affine operation. For brevity and readability reasons,
allow `affine.for` and `affine.if` to omit the `affine.terminator` in their
regions when using custom printing and parsing format. The custom parser
injects the `affine.terminator` if it is missing so as to always have it
present in constructed operations.
Update transformations to account for the presence of terminator. In
particular, most code motion transformation between loops should leave the
terminator in place, and code motion between loops and non-affine blocks should
drop the terminator.
PiperOrigin-RevId: 240536998
Currently, regions can only be constructed by passing in a `Function` or an
`Instruction` pointer referencing the parent object, unlike `Function`s or
`Instruction`s themselves that can be created without a parent. It leads to a
rather complex flow in operation construction where one has to create the
operation first before being able to work with its regions. It may be
necessary to work with the regions before the operation is created. In
particular, in `build` and `parse` functions that are executed _before_ the
operation is created in cases where boilerplate region manipulation is required
(for example, inserting the hypothetical default terminator in affine regions).
Allow creating standalone regions. Such regions are meant to own a list of
blocks and transfer them to other regions on demand.
Each instruction stores a fixed number of regions as trailing objects and has
ownership of them. This decreases the size of the Instruction object for the
common case of instructions without regions. Keep this behavior intact. To
allow some flexibility in construction, make OperationState store an owning
vector of regions. When the Builder creates an Instruction from
OperationState, the bodies of the regions are transferred into the
instruction-owned regions to minimize copying. Thus, it becomes possible to
fill standalone regions with blocks and move them to an operation when it is
constructed, or move blocks from a region to an operation region, e.g., for
inlining.
PiperOrigin-RevId: 240368183
Dialect attributes are defined as:
dialect-namespace `.` attr-name `:` attribute-value
Dialects can override any of the following hooks to verify the validity of a given attribute:
* verifyFunctionAttribute
* verifyFunctionArgAttribute
* verifyInstructionAttribute
PiperOrigin-RevId: 236507970
Add support for lowering DivF and RemF to LLVM::FDiv and LLMV::FRem
respectively. The lowering is a trivial one-to-one transformation.
The corresponding operations already existed in the LLVM IR dialect and can be
lowered to the LLVM IR proper. Add the necessary tests for scalar and vector
forms.
PiperOrigin-RevId: 234984608
Associates opaque constants with a particular dialect. Adds general mechanism to register dialect-specific hooks defined in external components. Adds hooks to decode opaque tensor constant and extract an element of an opaque tensor constant.
This CL does not change the existing mechanism for registering constant folding hook yet. One thing at a time.
PiperOrigin-RevId: 233544757
Aggregate types where at least one dimension is zero do not fully make sense as
they cannot contain any values (their total size is zero). However, TensorFlow
and XLA support tensors with zero sizes, so we must support those too. This is
relatively safe since, unlike vectors and memrefs, we don't have first-class
element accessors for MLIR tensors.
To support sparse element attributes of vector types that have no non-zero
elements, make sure that index and value element attributes have tensor type so
that we never need to create a zero vector type internally. Note that this is
already consistent with the inline documentation of the sparse elements
attribute. Users of the sparse elements attribute should not rely on the
storage schema anyway.
PiperOrigin-RevId: 232896707
Existing IR syntax is ambiguous in type declarations in presence of zero sizes.
In particular, `0x1` in the type size can be interpreted as either a
hexadecimal literal corresponding to 1, or as two distinct decimal literals
separated by an `x` for sizes. Furthermore, the shape `<0xi32>` fails lexing
because it is expected to be an integer literal.
Fix the lexer to treat `0xi32` as an integer literal `0` followed by a bare
identifier `xi32` (look one character ahead and early return instead of
erroring out).
Disallow hexadecimal literals in type declarations and forcibly split the token
into multiple parts while parsing the type. Note that the splitting trick has
been already present to separate the element type from the preceding `x`
character.
PiperOrigin-RevId: 232880373
Existing type syntax contains the following productions:
function-type ::= type-list-parens `->` type-list
type-list ::= type | type-list-parens
type ::= <..> | function-type
Due to these rules, when the parser sees `->` followed by `(`, it cannot
disambiguate if `(` starts a parenthesized list of function result types, or a
parenthesized list of operands of another function type, returned from the
current function. We would need an unknown amount of lookahead to try to find
the `->` at the right level of function nesting to differentiate between type
lists and singular function types.
Instead, require the result type of the function that is a function type itself
to be always parenthesized, at the syntax level. Update the spec and the
parser to correspond to the production rule names used in the spec (although it
would have worked without modifications). Fix the function type parsing bug in
the process, as it used to accept the non-parenthesized list of types for
arguments, disallowed by the spec.
PiperOrigin-RevId: 232528361
Uday Bondhugula