[mlir][docs] Remove the BuiltinDialect documentation from langref and generate it from ODS

Now that all of the builtin dialect is generated from ODS, its documentation in LangRef can be split out and replaced with references to Dialects/Builtin.md. LangRef is quite crusty right now and should really have a full cleanup done in a followup.

Differential Revision: https://reviews.llvm.org/D98562
This commit is contained in:
River Riddle 2021-03-19 18:19:16 -07:00
parent b2f232b830
commit caddfbd2a9
6 changed files with 157 additions and 966 deletions

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@ -11,69 +11,9 @@ structure of the IR, operations, etc.
## Source Locations
Source location information is extremely important for any compiler, because it
provides a baseline for debuggability and error-reporting. MLIR provides several
different location types depending on the situational need.
### CallSite Location
```
callsite-location ::= 'callsite' '(' location 'at' location ')'
```
An instance of this location allows for representing a directed stack of
location usages. This connects a location of a `callee` with the location of a
`caller`.
### FileLineCol Location
```
filelinecol-location ::= string-literal ':' integer-literal ':' integer-literal
```
An instance of this location represents a tuple of file, line number, and column
number. This is similar to the type of location that you get from most source
languages.
### Fused Location
```
fused-location ::= `fused` fusion-metadata? '[' location (location ',')* ']'
fusion-metadata ::= '<' attribute-value '>'
```
An instance of a `fused` location represents a grouping of several other source
locations, with optional metadata that describes the context of the fusion.
There are many places within a compiler in which several constructs may be fused
together, e.g. pattern rewriting, that normally result partial or even total
loss of location information. With `fused` locations, this is a non-issue.
### Name Location
```
name-location ::= string-literal ('(' location ')')?
```
An instance of this location allows for attaching a name to a child location.
This can be useful for representing the locations of variable, or node,
definitions.
### Opaque Location
An instance of this location essentially contains a pointer to some data
structure that is external to MLIR and an optional location that can be used if
the first one is not suitable. Since it contains an external structure, only the
optional location is used during serialization.
### Unknown Location
```
unknown-location ::= `unknown`
```
Source location information is an extremely integral part of the MLIR
infrastructure. As such, location information is always present in the IR, and
must explicitly be set to unknown. Thus an instance of the `unknown` location,
represents an unspecified source location.
provides a baseline for debuggability and error-reporting. The
[builtin dialect](Dialects/Builtin.md) provides several different location
attributes types depending on the situational need.
## Diagnostic Engine

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@ -0,0 +1,32 @@
# Builtin Dialect
The builtin dialect contains a core set of Attributes, Operations, and Types
that have wide applicability across a very large number of domains and
abstractions. Many of the components of this dialect are also instrumental in
the implementation of the core IR. As such, this dialect is implicitly loaded in
every `MLIRContext`, and available directly to all users of MLIR.
Given the far-reaching nature of this dialect and the fact that MLIR is
extensible by design, any potential additions are heavily scrutinized.
[TOC]
## Attributes
[include "Dialects/BuiltinAttributes.md"]
## Location Attributes
A subset of the builtin attribute values correspond to
[source locations](../Diagnostics.md#source-locations), that may be attached to
Operations.
[include "Dialects/BuiltinLocationAttributes.md"]
## Operations
[include "Dialects/BuiltinOps.md"]
## Types
[include "Dialects/BuiltinTypes.md"]

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@ -60,14 +60,13 @@ Operation](docs/Tutorials/Toy/Ch-2/#op-vs-operation-using-mlir-operations))
One obvious application of MLIR is to represent an
[SSA-based](https://en.wikipedia.org/wiki/Static_single_assignment_form) IR,
like the LLVM core IR, with appropriate choice of Operation Types to define
[Modules](#module), [Functions](#functions), Branches, Allocations, and
verification constraints to ensure the SSA Dominance property. MLIR includes a
'standard' dialect which defines just such structures. However, MLIR is
intended to be general enough to represent other compiler-like data
structures, such as Abstract Syntax Trees in a language frontend, generated
instructions in a target-specific backend, or circuits in a High-Level
Synthesis tool.
like the LLVM core IR, with appropriate choice of operation types to define
Modules, Functions, Branches, Memory Allocation, and verification constraints to
ensure the SSA Dominance property. MLIR includes a collection of dialects which
defines just such structures. However, MLIR is intended to be general enough to
represent other compiler-like data structures, such as Abstract Syntax Trees in
a language frontend, generated instructions in a target-specific backend, or
circuits in a High-Level Synthesis tool.
Here's an example of an MLIR module:
@ -328,96 +327,12 @@ In addition to the basic syntax above, dialects may register known operations.
This allows those dialects to support _custom assembly form_ for parsing and
printing operations. In the operation sets listed below, we show both forms.
### Terminator Operations
### Builtin Operations
These are a special category of operations that *must* terminate a block, e.g.
[branches](Dialects/Standard.md#terminator-operations). These operations may
also have a list of successors ([blocks](#blocks) and their arguments).
Example:
```mlir
// Branch to ^bb1 or ^bb2 depending on the condition %cond.
// Pass value %v to ^bb2, but not to ^bb1.
"cond_br"(%cond)[^bb1, ^bb2(%v : index)] : (i1) -> ()
```
### Module
```
module ::= `module` symbol-ref-id? (`attributes` dictionary-attribute)? region
```
An MLIR Module represents a top-level container operation. It contains a single
[SSACFG region](#control-flow-and-ssacfg-regions) containing a single block
which can contain any operations. Operations within this region cannot
implicitly capture values defined outside the module, i.e. Modules are
[IsolatedFromAbove](Traits.md#isolatedfromabove). Modules have an optional
[symbol name](SymbolsAndSymbolTables.md) which can be used to refer to them in
operations.
### Functions
An MLIR Function is an operation with a name containing a single [SSACFG
region](#control-flow-and-ssacfg-regions). Operations within this region
cannot implicitly capture values defined outside of the function,
i.e. Functions are [IsolatedFromAbove](Traits.md#isolatedfromabove). All
external references must use function arguments or attributes that establish a
symbolic connection (e.g. symbols referenced by name via a string attribute
like [SymbolRefAttr](#symbol-reference-attribute)):
```
function ::= `func` function-signature function-attributes? function-body?
function-signature ::= symbol-ref-id `(` argument-list `)`
(`->` function-result-list)?
argument-list ::= (named-argument (`,` named-argument)*) | /*empty*/
argument-list ::= (type dictionary-attribute? (`,` type dictionary-attribute?)*)
| /*empty*/
named-argument ::= value-id `:` type dictionary-attribute?
function-result-list ::= function-result-list-parens
| non-function-type
function-result-list-parens ::= `(` `)`
| `(` function-result-list-no-parens `)`
function-result-list-no-parens ::= function-result (`,` function-result)*
function-result ::= type dictionary-attribute?
function-attributes ::= `attributes` dictionary-attribute
function-body ::= region
```
An external function declaration (used when referring to a function declared
in some other module) has no body. While the MLIR textual form provides a nice
inline syntax for function arguments, they are internally represented as
"block arguments" to the first block in the region.
Only dialect attribute names may be specified in the attribute dictionaries
for function arguments, results, or the function itself.
Examples:
```mlir
// External function definitions.
func @abort()
func @scribble(i32, i64, memref<? x 128 x f32, #layout_map0>) -> f64
// A function that returns its argument twice:
func @count(%x: i64) -> (i64, i64)
attributes {fruit: "banana"} {
return %x, %x: i64, i64
}
// A function with an argument attribute
func @example_fn_arg(%x: i32 {swift.self = unit})
// A function with a result attribute
func @example_fn_result() -> (f64 {dialectName.attrName = 0 : i64})
// A function with an attribute
func @example_fn_attr() attributes {dialectName.attrName = false}
```
The [builtin dialect](Dialects/Builtin.md) defines a select few operations that
are widely applicable by MLIR dialects, such as a universal conversion cast
operation that simplifies inter/intra dialect conversion. This dialect also
defines a top-level `module` operation, that represents a useful IR container.
## Blocks
@ -701,14 +616,10 @@ defines the relation between the region results and the operation results.
## Type System
Each value in MLIR has a type defined by the type system below. There are a
number of primitive types (like integers) and also aggregate types for tensors
and memory buffers. MLIR [builtin types](#builtin-types) do not include
structures, arrays, or dictionaries.
MLIR has an open type system (i.e. there is no fixed list of types), and types
may have application-specific semantics. For example, MLIR supports a set of
[dialect types](#dialect-types).
Each value in MLIR has a type defined by the type system. MLIR has an open type
system (i.e. there is no fixed list of types), and types may have
application-specific semantics. MLIR dialects may define any number of types
with no restrictions on the abstractions they represent.
```
type ::= type-alias | dialect-type | builtin-type
@ -806,497 +717,14 @@ the lighter syntax: `!foo.something<a%%123^^^>>>` because it contains characters
that are not allowed in the lighter syntax, as well as unbalanced `<>`
characters.
See [here](Tutorials/DefiningAttributesAndTypes.md) to learn how to define dialect types.
See [here](Tutorials/DefiningAttributesAndTypes.md) to learn how to define
dialect types.
### Builtin Types
Builtin types are a core set of [dialect types](#dialect-types) that are defined
in a builtin dialect and thus available to all users of MLIR.
```
builtin-type ::= complex-type
| float-type
| function-type
| index-type
| integer-type
| memref-type
| none-type
| tensor-type
| tuple-type
| vector-type
```
#### Complex Type
Syntax:
```
complex-type ::= `complex` `<` type `>`
```
The value of `complex` type represents a complex number with a parameterized
element type, which is composed of a real and imaginary value of that element
type. The element must be a floating point or integer scalar type.
Examples:
```mlir
complex<f32>
complex<i32>
```
#### Floating Point Types
Syntax:
```
// Floating point.
float-type ::= `f16` | `bf16` | `f32` | `f64` | `f80` | `f128`
```
MLIR supports float types of certain widths that are widely used as indicated
above.
#### Function Type
Syntax:
```
// MLIR functions can return multiple values.
function-result-type ::= type-list-parens
| non-function-type
function-type ::= type-list-parens `->` function-result-type
```
MLIR supports first-class functions: for example, the
[`constant` operation](Dialects/Standard.md#stdconstant-constantop) produces the
address of a function as a value. This value may be passed to and
returned from functions, merged across control flow boundaries with
[block arguments](#blocks), and called with the
[`call_indirect` operation](Dialects/Standard.md#call-indirect-operation).
Function types are also used to indicate the arguments and results of
[operations](#operations).
#### Index Type
Syntax:
```
// Target word-sized integer.
index-type ::= `index`
```
The `index` type is a signless integer whose size is equal to the natural
machine word of the target
([rationale](Rationale/Rationale.md#integer-signedness-semantics)) and is used
by the affine constructs in MLIR. Unlike fixed-size integers, it cannot be used
as an element of vector
([rationale](Rationale/Rationale.md#index-type-disallowed-in-vector-types)).
**Rationale:** integers of platform-specific bit widths are practical to express
sizes, dimensionalities and subscripts.
#### Integer Type
Syntax:
```
// Sized integers like i1, i4, i8, i16, i32.
signed-integer-type ::= `si` [1-9][0-9]*
unsigned-integer-type ::= `ui` [1-9][0-9]*
signless-integer-type ::= `i` [1-9][0-9]*
integer-type ::= signed-integer-type |
unsigned-integer-type |
signless-integer-type
```
MLIR supports arbitrary precision integer types. Integer types have a designated
width and may have signedness semantics.
**Rationale:** low precision integers (like `i2`, `i4` etc) are useful for
low-precision inference chips, and arbitrary precision integers are useful for
hardware synthesis (where a 13 bit multiplier is a lot cheaper/smaller than a 16
bit one).
TODO: Need to decide on a representation for quantized integers
([initial thoughts](Rationale/Rationale.md#quantized-integer-operations)).
#### Memref Type
Syntax:
```
memref-type ::= ranked-memref-type | unranked-memref-type
ranked-memref-type ::= `memref` `<` dimension-list-ranked type
(`,` layout-specification)? (`,` memory-space)? `>`
unranked-memref-type ::= `memref` `<*x` type (`,` memory-space)? `>`
stride-list ::= `[` (dimension (`,` dimension)*)? `]`
strided-layout ::= `offset:` dimension `,` `strides: ` stride-list
semi-affine-map-composition ::= (semi-affine-map `,` )* semi-affine-map
layout-specification ::= semi-affine-map-composition | strided-layout
memory-space ::= integer-literal /* | TODO: address-space-id */
```
A `memref` type is a reference to a region of memory (similar to a buffer
pointer, but more powerful). The buffer pointed to by a memref can be allocated,
aliased and deallocated. A memref can be used to read and write data from/to the
memory region which it references. Memref types use the same shape specifier as
tensor types. Note that `memref<f32>`, `memref<0 x f32>`, `memref<1 x 0 x f32>`,
and `memref<0 x 1 x f32>` are all different types.
A `memref` is allowed to have an unknown rank (e.g. `memref<*xf32>`). The
purpose of unranked memrefs is to allow external library functions to receive
memref arguments of any rank without versioning the functions based on the rank.
Other uses of this type are disallowed or will have undefined behavior.
##### Codegen of Unranked Memref
Using unranked memref in codegen besides the case mentioned above is highly
discouraged. Codegen is concerned with generating loop nests and specialized
instructions for high-performance, unranked memref is concerned with hiding the
rank and thus, the number of enclosing loops required to iterate over the data.
However, if there is a need to code-gen unranked memref, one possible path is to
cast into a static ranked type based on the dynamic rank. Another possible path
is to emit a single while loop conditioned on a linear index and perform
delinearization of the linear index to a dynamic array containing the (unranked)
indices. While this is possible, it is expected to not be a good idea to perform
this during codegen as the cost of the translations is expected to be
prohibitive and optimizations at this level are not expected to be worthwhile.
If expressiveness is the main concern, irrespective of performance, passing
unranked memrefs to an external C++ library and implementing rank-agnostic logic
there is expected to be significantly simpler.
Unranked memrefs may provide expressiveness gains in the future and help bridge
the gap with unranked tensors. Unranked memrefs will not be expected to be
exposed to codegen but one may query the rank of an unranked memref (a special
op will be needed for this purpose) and perform a switch and cast to a ranked
memref as a prerequisite to codegen.
Example:
```mlir
// With static ranks, we need a function for each possible argument type
%A = alloc() : memref<16x32xf32>
%B = alloc() : memref<16x32x64xf32>
call @helper_2D(%A) : (memref<16x32xf32>)->()
call @helper_3D(%B) : (memref<16x32x64xf32>)->()
// With unknown rank, the functions can be unified under one unranked type
%A = alloc() : memref<16x32xf32>
%B = alloc() : memref<16x32x64xf32>
// Remove rank info
%A_u = memref_cast %A : memref<16x32xf32> -> memref<*xf32>
%B_u = memref_cast %B : memref<16x32x64xf32> -> memref<*xf32>
// call same function with dynamic ranks
call @helper(%A_u) : (memref<*xf32>)->()
call @helper(%B_u) : (memref<*xf32>)->()
```
The core syntax and representation of a layout specification is a
[semi-affine map](Dialects/Affine.md#semi-affine-maps). Additionally, syntactic
sugar is supported to make certain layout specifications more intuitive to read.
For the moment, a `memref` supports parsing a strided form which is converted to
a semi-affine map automatically.
The memory space of a memref is specified by a target-specific attribute.
It might be an integer value, string, dictionary or custom dialect attribute.
The empty memory space (attribute is None) is target specific.
The notionally dynamic value of a memref value includes the address of the
buffer allocated, as well as the symbols referred to by the shape, layout map,
and index maps.
Examples of memref static type
```mlir
// Identity index/layout map
#identity = affine_map<(d0, d1) -> (d0, d1)>
// Column major layout.
#col_major = affine_map<(d0, d1, d2) -> (d2, d1, d0)>
// A 2-d tiled layout with tiles of size 128 x 256.
#tiled_2d_128x256 = affine_map<(d0, d1) -> (d0 div 128, d1 div 256, d0 mod 128, d1 mod 256)>
// A tiled data layout with non-constant tile sizes.
#tiled_dynamic = affine_map<(d0, d1)[s0, s1] -> (d0 floordiv s0, d1 floordiv s1,
d0 mod s0, d1 mod s1)>
// A layout that yields a padding on two at either end of the minor dimension.
#padded = affine_map<(d0, d1) -> (d0, (d1 + 2) floordiv 2, (d1 + 2) mod 2)>
// The dimension list "16x32" defines the following 2D index space:
//
// { (i, j) : 0 <= i < 16, 0 <= j < 32 }
//
memref<16x32xf32, #identity>
// The dimension list "16x4x?" defines the following 3D index space:
//
// { (i, j, k) : 0 <= i < 16, 0 <= j < 4, 0 <= k < N }
//
// where N is a symbol which represents the runtime value of the size of
// the third dimension.
//
// %N here binds to the size of the third dimension.
%A = alloc(%N) : memref<16x4x?xf32, #col_major>
// A 2-d dynamic shaped memref that also has a dynamically sized tiled layout.
// The memref index space is of size %M x %N, while %B1 and %B2 bind to the
// symbols s0, s1 respectively of the layout map #tiled_dynamic. Data tiles of
// size %B1 x %B2 in the logical space will be stored contiguously in memory.
// The allocation size will be (%M ceildiv %B1) * %B1 * (%N ceildiv %B2) * %B2
// f32 elements.
%T = alloc(%M, %N) [%B1, %B2] : memref<?x?xf32, #tiled_dynamic>
// A memref that has a two-element padding at either end. The allocation size
// will fit 16 * 64 float elements of data.
%P = alloc() : memref<16x64xf32, #padded>
// Affine map with symbol 's0' used as offset for the first dimension.
#imapS = affine_map<(d0, d1) [s0] -> (d0 + s0, d1)>
// Allocate memref and bind the following symbols:
// '%n' is bound to the dynamic second dimension of the memref type.
// '%o' is bound to the symbol 's0' in the affine map of the memref type.
%n = ...
%o = ...
%A = alloc (%n)[%o] : <16x?xf32, #imapS>
```
##### Index Space
A memref dimension list defines an index space within which the memref can be
indexed to access data.
##### Index
Data is accessed through a memref type using a multidimensional index into the
multidimensional index space defined by the memref's dimension list.
Examples
```mlir
// Allocates a memref with 2D index space:
// { (i, j) : 0 <= i < 16, 0 <= j < 32 }
%A = alloc() : memref<16x32xf32, #imapA>
// Loads data from memref '%A' using a 2D index: (%i, %j)
%v = load %A[%i, %j] : memref<16x32xf32, #imapA>
```
##### Index Map
An index map is a one-to-one
[semi-affine map](Dialects/Affine.md#semi-affine-maps) that transforms a
multidimensional index from one index space to another. For example, the
following figure shows an index map which maps a 2-dimensional index from a 2x2
index space to a 3x3 index space, using symbols `S0` and `S1` as offsets.
![Index Map Example](/includes/img/index-map.svg)
The number of domain dimensions and range dimensions of an index map can be
different, but must match the number of dimensions of the input and output index
spaces on which the map operates. The index space is always non-negative and
integral. In addition, an index map must specify the size of each of its range
dimensions onto which it maps. Index map symbols must be listed in order with
symbols for dynamic dimension sizes first, followed by other required symbols.
##### Layout Map
A layout map is a [semi-affine map](Dialects/Affine.md#semi-affine-maps) which
encodes logical to physical index space mapping, by mapping input dimensions to
their ordering from most-major (slowest varying) to most-minor (fastest
varying). Therefore, an identity layout map corresponds to a row-major layout.
Identity layout maps do not contribute to the MemRef type identification and are
discarded on construction. That is, a type with an explicit identity map is
`memref<?x?xf32, (i,j)->(i,j)>` is strictly the same as the one without layout
maps, `memref<?x?xf32>`.
Layout map examples:
```mlir
// MxN matrix stored in row major layout in memory:
#layout_map_row_major = (i, j) -> (i, j)
// MxN matrix stored in column major layout in memory:
#layout_map_col_major = (i, j) -> (j, i)
// MxN matrix stored in a 2-d blocked/tiled layout with 64x64 tiles.
#layout_tiled = (i, j) -> (i floordiv 64, j floordiv 64, i mod 64, j mod 64)
```
##### Affine Map Composition
A memref specifies a semi-affine map composition as part of its type. A
semi-affine map composition is a composition of semi-affine maps beginning with
zero or more index maps, and ending with a layout map. The composition must be
conformant: the number of dimensions of the range of one map, must match the
number of dimensions of the domain of the next map in the composition.
The semi-affine map composition specified in the memref type, maps from accesses
used to index the memref in load/store operations to other index spaces (i.e.
logical to physical index mapping). Each of the
[semi-affine maps](Dialects/Affine.md) and thus its composition is required to
be one-to-one.
The semi-affine map composition can be used in dependence analysis, memory
access pattern analysis, and for performance optimizations like vectorization,
copy elision and in-place updates. If an affine map composition is not specified
for the memref, the identity affine map is assumed.
##### Strided MemRef
A memref may specify strides as part of its type. A stride specification is a
list of integer values that are either static or `?` (dynamic case). Strides
encode the distance, in number of elements, in (linear) memory between
successive entries along a particular dimension. A stride specification is
syntactic sugar for an equivalent strided memref representation using
semi-affine maps. For example, `memref<42x16xf32, offset: 33, strides: [1, 64]>`
specifies a non-contiguous memory region of `42` by `16` `f32` elements such
that:
1. the minimal size of the enclosing memory region must be `33 + 42 * 1 + 16 *
64 = 1066` elements;
2. the address calculation for accessing element `(i, j)` computes `33 + i +
64 * j`
3. the distance between two consecutive elements along the inner dimension is
`1` element and the distance between two consecutive elements along the
outer dimension is `64` elements.
This corresponds to a column major view of the memory region and is internally
represented as the type `memref<42x16xf32, (i, j) -> (33 + i + 64 * j)>`.
The specification of strides must not alias: given an n-D strided memref,
indices `(i1, ..., in)` and `(j1, ..., jn)` may not refer to the same memory
address unless `i1 == j1, ..., in == jn`.
Strided memrefs represent a view abstraction over preallocated data. They are
constructed with special ops, yet to be introduced. Strided memrefs are a
special subclass of memrefs with generic semi-affine map and correspond to a
normalized memref descriptor when lowering to LLVM.
#### None Type
Syntax:
```
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.
#### Tensor Type
Syntax:
```
tensor-type ::= `tensor` `<` dimension-list type `>`
dimension-list ::= dimension-list-ranked | (`*` `x`)
dimension-list-ranked ::= (dimension `x`)*
dimension ::= `?` | decimal-literal
```
Values with tensor type represents aggregate N-dimensional data values, and
have a known element type. It may have an unknown rank (indicated by `*`) or may
have a fixed rank with a list of dimensions. Each dimension may be a static
non-negative decimal constant or be dynamically determined (indicated by `?`).
The runtime representation of the MLIR tensor type is intentionally abstracted -
you cannot control layout or get a pointer to the data. For low level buffer
access, MLIR has a [`memref` type](#memref-type). This abstracted runtime
representation holds both the tensor data values as well as information about
the (potentially dynamic) shape of the tensor. The
[`dim` operation](Dialects/Standard.md#dim-operation) returns the size of a
dimension from a value of tensor type.
Note: hexadecimal integer literals are not allowed in tensor type declarations
to avoid confusion between `0xf32` and `0 x f32`. Zero sizes are allowed in
tensors and treated as other sizes, e.g., `tensor<0 x 1 x i32>` and `tensor<1 x
0 x i32>` are different types. Since zero sizes are not allowed in some other
types, such tensors should be optimized away before lowering tensors to vectors.
Examples:
```mlir
// Tensor with unknown rank.
tensor<* x f32>
// Known rank but unknown dimensions.
tensor<? x ? x ? x ? x f32>
// Partially known dimensions.
tensor<? x ? x 13 x ? x f32>
// Full static shape.
tensor<17 x 4 x 13 x 4 x f32>
// Tensor with rank zero. Represents a scalar.
tensor<f32>
// Zero-element dimensions are allowed.
tensor<0 x 42 x f32>
// Zero-element tensor of f32 type (hexadecimal literals not allowed here).
tensor<0xf32>
```
#### Tuple Type
Syntax:
```
tuple-type ::= `tuple` `<` (type ( `,` type)*)? `>`
```
The value of `tuple` type represents a fixed-size collection of elements, where
each element may be of a different type.
**Rationale:** Though this type is first class in the type system, MLIR provides
no standard operations for operating on `tuple` types
([rationale](Rationale/Rationale.md#tuple-types)).
Examples:
```mlir
// Empty tuple.
tuple<>
// Single element
tuple<f32>
// Many elements.
tuple<i32, f32, tensor<i1>, i5>
```
#### Vector Type
Syntax:
```
vector-type ::= `vector` `<` static-dimension-list vector-element-type `>`
vector-element-type ::= float-type | integer-type
static-dimension-list ::= (decimal-literal `x`)+
```
The vector type represents a SIMD style vector, used by target-specific
operation sets like AVX. While the most common use is for 1D vectors (e.g.
vector<16 x f32>) we also support multidimensional registers on targets that
support them (like TPUs).
Vector shapes must be positive decimal integers.
Note: hexadecimal integer literals are not allowed in vector type declarations,
`vector<0x42xi32>` is invalid because it is interpreted as a 2D vector with
shape `(0, 42)` and zero shapes are not allowed.
The [builtin dialect](Dialects/Builtin.md) defines a set of types that are
directly usable by any other dialect in MLIR. These types cover a range from
primitive integer and floating-point types, function types, and more.
## Attributes
@ -1401,263 +829,7 @@ attribute values.
### Builtin Attribute Values
Builtin attributes are a core set of
[dialect attribute values](#dialect-attribute-values) that are defined in a
builtin dialect and thus available to all users of MLIR.
```
builtin-attribute ::= affine-map-attribute
| array-attribute
| bool-attribute
| dictionary-attribute
| elements-attribute
| float-attribute
| integer-attribute
| integer-set-attribute
| string-attribute
| symbol-ref-attribute
| type-attribute
| unit-attribute
```
#### AffineMap Attribute
Syntax:
```
affine-map-attribute ::= `affine_map` `<` affine-map `>`
```
An affine-map attribute is an attribute that represents an affine-map object.
#### Array Attribute
Syntax:
```
array-attribute ::= `[` (attribute-value (`,` attribute-value)*)? `]`
```
An array attribute is an attribute that represents a collection of attribute
values.
#### Boolean Attribute
Syntax:
```
bool-attribute ::= bool-literal
```
A boolean attribute is a literal attribute that represents a one-bit boolean
value, true or false.
#### Dictionary Attribute
Syntax:
```
dictionary-attribute ::= `{` (attribute-entry (`,` attribute-entry)*)? `}`
```
A dictionary attribute is an attribute that represents a sorted collection of
named attribute values. The elements are sorted by name, and each name must be
unique within the collection.
#### Elements Attributes
Syntax:
```
elements-attribute ::= dense-elements-attribute
| opaque-elements-attribute
| sparse-elements-attribute
```
An elements attribute is a literal attribute that represents a constant
[vector](#vector-type) or [tensor](#tensor-type) value.
##### Dense Elements Attribute
Syntax:
```
dense-elements-attribute ::= `dense` `<` attribute-value `>` `:`
( tensor-type | vector-type )
```
A dense elements attribute is an elements attribute where the storage for the
constant vector or tensor value has been densely packed. The attribute supports
storing integer or floating point elements, with integer/index/floating element
types. It also support storing string elements with a custom dialect string
element type.
##### Opaque Elements Attribute
Syntax:
```
opaque-elements-attribute ::= `opaque` `<` dialect-namespace `,`
hex-string-literal `>` `:`
( tensor-type | vector-type )
```
An opaque elements attribute is an elements attribute where the content of the
value is opaque. The representation of the constant stored by this elements
attribute is only understood, and thus decodable, by the dialect that created
it.
Note: The parsed string literal must be in hexadecimal form.
##### Sparse Elements Attribute
Syntax:
```
sparse-elements-attribute ::= `sparse` `<` attribute-value `,` attribute-value
`>` `:` ( tensor-type | vector-type )
```
A sparse elements attribute is an elements attribute that represents a sparse
vector or tensor object. This is where very few of the elements are non-zero.
The attribute uses COO (coordinate list) encoding to represent the sparse
elements of the elements attribute. The indices are stored via a 2-D tensor of
64-bit integer elements with shape [N, ndims], which specifies the indices of
the elements in the sparse tensor that contains non-zero values. The element
values are stored via a 1-D tensor with shape [N], that supplies the
corresponding values for the indices.
Example:
```mlir
sparse<[[0, 0], [1, 2]], [1, 5]> : tensor<3x4xi32>
// This represents the following tensor:
/// [[1, 0, 0, 0],
/// [0, 0, 5, 0],
/// [0, 0, 0, 0]]
```
#### Float Attribute
Syntax:
```
float-attribute ::= (float-literal (`:` float-type)?)
| (hexadecimal-literal `:` float-type)
```
A float attribute is a literal attribute that represents a floating point value
of the specified [float type](#floating-point-types). It can be represented in
the hexadecimal form where the hexadecimal value is interpreted as bits of the
underlying binary representation. This form is useful for representing infinity
and NaN floating point values. To avoid confusion with integer attributes,
hexadecimal literals _must_ be followed by a float type to define a float
attribute.
Examples:
```
42.0 // float attribute defaults to f64 type
42.0 : f32 // float attribute of f32 type
0x7C00 : f16 // positive infinity
0x7CFF : f16 // NaN (one of possible values)
42 : f32 // Error: expected integer type
```
#### Integer Attribute
Syntax:
```
integer-attribute ::= integer-literal ( `:` (index-type | integer-type) )?
```
An integer attribute is a literal attribute that represents an integral value of
the specified integer or index type. The default type for this attribute, if one
is not specified, is a 64-bit integer.
##### Integer Set Attribute
Syntax:
```
integer-set-attribute ::= `affine_set` `<` integer-set `>`
```
An integer-set attribute is an attribute that represents an integer-set object.
#### String Attribute
Syntax:
```
string-attribute ::= string-literal (`:` type)?
```
A string attribute is an attribute that represents a string literal value.
#### Symbol Reference Attribute
Syntax:
```
symbol-ref-attribute ::= symbol-ref-id (`::` symbol-ref-id)*
```
A symbol reference attribute is a literal attribute that represents a named
reference to an operation that is nested within an operation with the
`OpTrait::SymbolTable` trait. As such, this reference is given meaning by the
nearest parent operation containing the `OpTrait::SymbolTable` trait. It may
optionally contain a set of nested references that further resolve to a symbol
nested within a different symbol table.
This attribute can only be held internally by
[array attributes](#array-attribute) and
[dictionary attributes](#dictionary-attribute)(including the top-level operation
attribute dictionary), i.e. no other attribute kinds such as Locations or
extended attribute kinds.
**Rationale:** Identifying accesses to global data is critical to
enabling efficient multi-threaded compilation. Restricting global
data access to occur through symbols and limiting the places that can
legally hold a symbol reference simplifies reasoning about these data
accesses.
See [`Symbols And SymbolTables`](SymbolsAndSymbolTables.md) for more
information.
#### Type Attribute
Syntax:
```
type-attribute ::= type
```
A type attribute is an attribute that represents a [type object](#type-system).
#### Unit Attribute
```
unit-attribute ::= `unit`
```
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](#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
// A unit attribute defined with the `unit` value specifier.
func @verbose_form(i1) attributes {dialectName.unitAttr = unit}
// A unit attribute can also be defined without the value specifier.
func @simple_form(i1) attributes {dialectName.unitAttr}
```
The [builtin dialect](Dialects/Builtin.md) defines a set of attribute values
that are directly usable by any other dialect in MLIR. These types cover a range
from primitive integer and floating-point values, attribute dictionaries, dense
multi-dimensional arrays, and more.

View file

@ -131,7 +131,6 @@ def Builtin_Function : Builtin_Type<"Function"> {
The function type can be thought of as a function signature. It consists of
a list of formal parameter types and a list of formal result types.
```
}];
let parameters = (ins "ArrayRef<Type>":$inputs, "ArrayRef<Type>":$results);
let builders = [

View file

@ -26,4 +26,7 @@ mlir_tablegen(BuiltinTypes.h.inc -gen-typedef-decls)
mlir_tablegen(BuiltinTypes.cpp.inc -gen-typedef-defs)
add_public_tablegen_target(MLIRBuiltinTypesIncGen)
add_mlir_doc(BuiltinOps -gen-dialect-doc Builtin Dialects/)
add_mlir_doc(BuiltinAttributes -gen-attrdef-doc BuiltinAttributes Dialects/)
add_mlir_doc(BuiltinLocationAttributes -gen-attrdef-doc BuiltinLocationAttributes Dialects/)
add_mlir_doc(BuiltinOps -gen-op-doc BuiltinOps Dialects/)
add_mlir_doc(BuiltinTypes -gen-typedef-doc BuiltinTypes Dialects/)

View file

@ -162,46 +162,51 @@ static void emitTypeDoc(const Type &type, raw_ostream &os) {
// TypeDef Documentation
//===----------------------------------------------------------------------===//
/// Emit the assembly format of a type.
static void emitTypeAssemblyFormat(TypeDef td, raw_ostream &os) {
static void emitAttrOrTypeDefAssemblyFormat(const AttrOrTypeDef &def,
raw_ostream &os) {
SmallVector<AttrOrTypeParameter, 4> parameters;
td.getParameters(parameters);
if (parameters.size() == 0) {
os << "\nSyntax: `!" << td.getDialect().getName() << "." << td.getMnemonic()
<< "`\n";
def.getParameters(parameters);
if (parameters.empty()) {
os << "\nSyntax: `!" << def.getDialect().getName() << "."
<< def.getMnemonic() << "`\n";
return;
}
os << "\nSyntax:\n\n```\n!" << td.getDialect().getName() << "."
<< td.getMnemonic() << "<\n";
for (auto *it = parameters.begin(), *e = parameters.end(); it < e; ++it) {
os << " " << it->getSyntax();
if (it < parameters.end() - 1)
os << "\nSyntax:\n\n```\n!" << def.getDialect().getName() << "."
<< def.getMnemonic() << "<\n";
for (auto it : llvm::enumerate(parameters)) {
const AttrOrTypeParameter &param = it.value();
os << " " << param.getSyntax();
if (it.index() < (parameters.size() - 1))
os << ",";
os << " # " << it->getName() << "\n";
os << " # " << param.getName() << "\n";
}
os << ">\n```\n";
}
static void emitTypeDefDoc(TypeDef td, raw_ostream &os) {
os << llvm::formatv("### `{0}` ({1})\n", td.getName(), td.getCppClassName());
static void emitAttrOrTypeDefDoc(const AttrOrTypeDef &def, raw_ostream &os) {
os << llvm::formatv("### {0}\n", def.getCppClassName());
// Emit the summary, syntax, and description if present.
if (td.hasSummary())
os << "\n" << td.getSummary() << "\n";
if (td.getMnemonic() && td.getPrinterCode() && *td.getPrinterCode() == "" &&
td.getParserCode() && *td.getParserCode() == "")
emitTypeAssemblyFormat(td, os);
if (td.hasDescription()) {
// Emit the summary if present.
if (def.hasSummary())
os << "\n" << def.getSummary() << "\n";
// Emit the syntax if present.
if (def.getMnemonic() && def.getPrinterCode() == StringRef() &&
def.getParserCode() == StringRef())
emitAttrOrTypeDefAssemblyFormat(def, os);
// Emit the description if present.
if (def.hasDescription()) {
os << "\n";
mlir::tblgen::emitDescription(td.getDescription(), os);
mlir::tblgen::emitDescription(def.getDescription(), os);
}
// Emit attribute documentation.
// Emit parameter documentation.
SmallVector<AttrOrTypeParameter, 4> parameters;
td.getParameters(parameters);
def.getParameters(parameters);
if (!parameters.empty()) {
os << "\n#### Type parameters:\n\n";
os << "\n#### Parameters:\n\n";
os << "| Parameter | C++ type | Description |\n"
<< "| :-------: | :-------: | ----------- |\n";
for (const auto &it : parameters) {
@ -214,24 +219,35 @@ static void emitTypeDefDoc(TypeDef td, raw_ostream &os) {
os << "\n";
}
static void emitAttrOrTypeDefDoc(const RecordKeeper &recordKeeper,
raw_ostream &os, StringRef recordTypeName) {
std::vector<llvm::Record *> defs =
recordKeeper.getAllDerivedDefinitions(recordTypeName);
os << "<!-- Autogenerated by mlir-tblgen; don't manually edit -->\n";
for (const llvm::Record *def : defs)
emitAttrOrTypeDefDoc(AttrOrTypeDef(def), os);
}
//===----------------------------------------------------------------------===//
// Dialect Documentation
//===----------------------------------------------------------------------===//
static void emitDialectDoc(const Dialect &dialect, ArrayRef<Operator> ops,
ArrayRef<Type> types, ArrayRef<TypeDef> typeDefs,
raw_ostream &os) {
os << "# ";
if (dialect.getName().empty())
os << "Builtin";
else
os << "'" << dialect.getName() << "'";
os << " Dialect\n\n";
static void emitDialectDoc(const Dialect &dialect, ArrayRef<AttrDef> attrDefs,
ArrayRef<Operator> ops, ArrayRef<Type> types,
ArrayRef<TypeDef> typeDefs, raw_ostream &os) {
os << "# '" << dialect.getName() << "' Dialect\n\n";
emitIfNotEmpty(dialect.getSummary(), os);
emitIfNotEmpty(dialect.getDescription(), os);
os << "[TOC]\n\n";
if (!attrDefs.empty()) {
os << "## Attribute definition\n\n";
for (const AttrDef &def : attrDefs)
emitAttrOrTypeDefDoc(def, os);
}
// TODO: Add link between use and def for types
if (!types.empty()) {
os << "## Type constraint definition\n\n";
@ -247,46 +263,68 @@ static void emitDialectDoc(const Dialect &dialect, ArrayRef<Operator> ops,
if (!typeDefs.empty()) {
os << "## Type definition\n\n";
for (const TypeDef &td : typeDefs)
emitTypeDefDoc(td, os);
for (const TypeDef &def : typeDefs)
emitAttrOrTypeDefDoc(def, os);
}
}
static void emitDialectDoc(const RecordKeeper &recordKeeper, raw_ostream &os) {
const auto &opDefs = recordKeeper.getAllDerivedDefinitions("Op");
const auto &typeDefs = recordKeeper.getAllDerivedDefinitions("DialectType");
const auto &typeDefDefs = recordKeeper.getAllDerivedDefinitions("TypeDef");
std::vector<Record *> opDefs = recordKeeper.getAllDerivedDefinitions("Op");
std::vector<Record *> typeDefs =
recordKeeper.getAllDerivedDefinitions("DialectType");
std::vector<Record *> typeDefDefs =
recordKeeper.getAllDerivedDefinitions("TypeDef");
std::vector<Record *> attrDefDefs =
recordKeeper.getAllDerivedDefinitions("AttrDef");
std::set<Dialect> dialectsWithDocs;
std::map<Dialect, std::vector<Operator>> dialectOps;
std::map<Dialect, std::vector<Type>> dialectTypes;
std::map<Dialect, std::vector<TypeDef>> dialectTypeDefs;
llvm::StringMap<std::vector<AttrDef>> dialectAttrDefs;
llvm::StringMap<std::vector<Operator>> dialectOps;
llvm::StringMap<std::vector<Type>> dialectTypes;
llvm::StringMap<std::vector<TypeDef>> dialectTypeDefs;
for (auto *attrDef : attrDefDefs) {
AttrDef attr(attrDef);
dialectAttrDefs[attr.getDialect().getName()].push_back(attr);
dialectsWithDocs.insert(attr.getDialect());
}
for (auto *opDef : opDefs) {
Operator op(opDef);
dialectOps[op.getDialect()].push_back(op);
dialectOps[op.getDialect().getName()].push_back(op);
dialectsWithDocs.insert(op.getDialect());
}
for (auto *typeDef : typeDefs) {
Type type(typeDef);
if (auto dialect = type.getDialect())
dialectTypes[dialect].push_back(type);
dialectTypes[dialect.getName()].push_back(type);
}
for (auto *typeDef : typeDefDefs) {
TypeDef type(typeDef);
dialectTypeDefs[type.getDialect()].push_back(type);
dialectTypeDefs[type.getDialect().getName()].push_back(type);
dialectsWithDocs.insert(type.getDialect());
}
os << "<!-- Autogenerated by mlir-tblgen; don't manually edit -->\n";
for (auto dialect : dialectsWithDocs)
emitDialectDoc(dialect, dialectOps[dialect], dialectTypes[dialect],
dialectTypeDefs[dialect], os);
for (const Dialect &dialect : dialectsWithDocs) {
StringRef dialectName = dialect.getName();
emitDialectDoc(dialect, dialectAttrDefs[dialectName],
dialectOps[dialectName], dialectTypes[dialectName],
dialectTypeDefs[dialectName], os);
}
}
//===----------------------------------------------------------------------===//
// Gen Registration
//===----------------------------------------------------------------------===//
static mlir::GenRegistration
genAttrRegister("gen-attrdef-doc",
"Generate dialect attribute documentation",
[](const RecordKeeper &records, raw_ostream &os) {
emitAttrOrTypeDefDoc(records, os, "AttrDef");
return false;
});
static mlir::GenRegistration
genOpRegister("gen-op-doc", "Generate dialect documentation",
[](const RecordKeeper &records, raw_ostream &os) {
@ -294,6 +332,13 @@ static mlir::GenRegistration
return false;
});
static mlir::GenRegistration
genTypeRegister("gen-typedef-doc", "Generate dialect type documentation",
[](const RecordKeeper &records, raw_ostream &os) {
emitAttrOrTypeDefDoc(records, os, "TypeDef");
return false;
});
static mlir::GenRegistration
genRegister("gen-dialect-doc", "Generate dialect documentation",
[](const RecordKeeper &records, raw_ostream &os) {