2018-10-25 00:47:36 +08:00
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# MLIR Specification
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2019-07-19 01:34:19 +08:00
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MLIR (Multi-Level IR) is a compiler intermediate representation with
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similarities to traditional three-address SSA representations (like
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2018-10-25 00:47:36 +08:00
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[LLVM IR](http://llvm.org/docs/LangRef.html) or
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[SIL](https://github.com/apple/swift/blob/master/docs/SIL.rst)), but which
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introduces notions from polyhedral loop optimization as first-class concepts.
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This hybrid design is optimized to represent, analyze, and transform high level
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dataflow graphs as well as target-specific code generated for high performance
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data parallel systems. Beyond its representational capabilities, its single
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continuous design provides a framework to lower from dataflow graphs to
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high-performance target-specific code.
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2019-07-19 01:34:19 +08:00
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This document defines and describes the key concepts in MLIR, and is intended to
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be a dry reference document - [rationale documentation](Rationale.md) and other
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content is hosted elsewhere.
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MLIR is designed to be used in three different forms: a human-readable textual
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form suitable for debugging, an in-memory form suitable for programmatic
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transformations and analysis, and a compact serialized form suitable for storage
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and transport. The different forms all describe the same semantic content. This
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document describes the human-readable textual form.
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[TOC]
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2019-04-05 23:19:42 +08:00
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## High-Level Structure
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MLIR is an
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[SSA-based](https://en.wikipedia.org/wiki/Static_single_assignment_form) IR,
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which means that values are defined before use and have scope defined by their
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dominance relations. Operations may produce zero or more results, and each is a
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distinct SSA value with its own type defined by the [type system](#type-system).
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2019-09-27 22:44:52 +08:00
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The unit of code in MLIR is an [Operation](#operations). Operations allow for
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representing many different concepts: allocating buffers, producing views to
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transform them, target-independent arithmetic, target-specific operations, and
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even arbitrary user-defined high-level operations including the
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[Module](#module) and [Function](#functions) operations. Operations may contain
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[Regions](#regions) that contain a Control Flow Graph (CFG) of
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[Blocks](#blocks), which contain operations and end with a
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[terminator operation](#terminator-operations) (like branches).
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Here's an example of an MLIR module:
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2018-11-14 23:52:12 +08:00
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```mlir {.mlir}
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// Compute A*B using an implementation of multiply kernel and print the
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// result using a TensorFlow op. The dimensions of A and B are partially
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// known. The shapes are assumed to match.
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func @mul(%A: tensor<100x?xf32>, %B: tensor<?x50xf32>) -> (tensor<100x50xf32>) {
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// Compute the inner dimension of %A using the dim operation.
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%n = dim %A, 1 : tensor<100x?xf32>
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// Allocate addressable "buffers" and copy tensors %A and %B into them.
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%A_m = alloc(%n) : memref<100x?xf32>
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tensor_store %A to %A_m : memref<100x?xf32>
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2019-02-21 06:12:21 +08:00
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%B_m = alloc(%n) : memref<?x50xf32>
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tensor_store %B to %B_m : memref<?x50xf32>
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2019-02-06 08:29:25 +08:00
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// Call function @multiply passing memrefs as arguments,
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// and getting returned the result of the multiplication.
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%C_m = call @multiply(%A_m, %B_m)
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: (memref<100x?xf32>, memref<?x50xf32>) -> (memref<100x50xf32>)
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dealloc %A_m : memref<100x?xf32>
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dealloc %B_m : memref<?x50xf32>
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// Load the buffer data into a higher level "tensor" value.
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%C = tensor_load %C_m : memref<100x50xf32>
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dealloc %C_m : memref<100x50xf32>
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// Call TensorFlow built-in function to print the result tensor.
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"tf.Print"(%C){message: "mul result"}
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: (tensor<100x50xf32) -> (tensor<100x50xf32>)
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return %C : tensor<100x50xf32>
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}
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// A function that multiplies two memrefs and returns the result.
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func @multiply(%A: memref<100x?xf32>, %B: memref<?x50xf32>)
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-> (memref<100x50xf32>) {
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// Compute the inner dimension of %A.
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%n = dim %A, 1 : memref<100x?xf32>
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// Allocate memory for the multiplication result.
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%C = alloc() : memref<100x50xf32>
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// Multiplication loop nest.
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affine.for %i = 0 to 100 {
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affine.for %j = 0 to 50 {
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store 0 to %C[%i, %j] : memref<100x50xf32>
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affine.for %k = 0 to %n {
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%a_v = load %A[%i, %k] : memref<100x?xf32>
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%b_v = load %B[%k, %j] : memref<?x50xf32>
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%prod = mulf %a_v, %b_v : f32
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%c_v = load %C[%i, %j] : memref<100x50xf32>
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%sum = addf %c_v, %prod : f32
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store %sum, %C[%i, %j] : memref<100x50xf32>
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}
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}
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}
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return %C : memref<100x50xf32>
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}
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```
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2019-04-05 23:19:42 +08:00
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## Notation
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MLIR has a simple and unambiguous grammar, allowing it to reliably round-trip
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through a textual form. This is important for development of the compiler - e.g.
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understanding the state of code as it is being transformed and for writing test
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cases.
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This document describes the grammar using
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[Extended Backus-Naur Form (EBNF)](https://en.wikipedia.org/wiki/Extended_Backus%E2%80%93Naur_form).
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This is the EBNF grammar used in this document, presented in yellow boxes.
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``` {.ebnf}
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alternation ::= expr0 | expr1 | expr2 // Either expr0 or expr1 or expr2.
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sequence ::= expr0 expr1 expr2 // Sequence of expr0 expr1 expr2.
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repetition0 ::= expr* // 0 or more occurrences.
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repetition1 ::= expr+ // 1 or more occurrences.
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optionality ::= expr? // 0 or 1 occurrence.
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grouping ::= (expr) // Everything inside parens is grouped together.
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literal ::= `abcd` // Matches the literal `abcd`.
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```
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Code examples are presented in blue boxes.
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2018-11-14 23:52:12 +08:00
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```mlir {.mlir}
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// This is an example use of the grammar above:
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// This matches things like: ba, bana, boma, banana, banoma, bomana...
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example ::= `b` (`an` | `om`)* `a`
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```
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2019-04-05 23:19:42 +08:00
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### Common syntax
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The following core grammar productions are used in this document:
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``` {.ebnf}
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// TODO: Clarify the split between lexing (tokens) and parsing (grammar).
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digit ::= [0-9]
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hex_digit ::= [0-9a-fA-F]
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letter ::= [a-zA-Z]
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id-punct ::= [$._-]
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2019-02-08 00:36:50 +08:00
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integer-literal ::= decimal-literal | hexadecimal-literal
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decimal-literal ::= digit+
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hexadecimal-literal ::= `0x` hex_digit+
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float-literal ::= TODO
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string-literal ::= `"` [^"\n\f\v\r]* `"` TODO define escaping rules
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```
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Not listed here, but MLIR does support comments. They use standard BCPL syntax,
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starting with a `//` and going until the end of the line.
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2019-04-05 23:19:42 +08:00
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### Identifiers and keywords
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Syntax:
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``` {.ebnf}
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// Identifiers
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bare-id ::= (letter|[_]) (letter|digit|[_$.])*
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bare-id-list ::= bare-id (`,` bare-id)*
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suffix-id ::= digit+ | ((letter|id-punct) (letter|id-punct|digit)*)
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2019-07-12 02:41:04 +08:00
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symbol-ref-id ::= `@` bare-id
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ssa-id ::= `%` suffix-id
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ssa-id-list ::= ssa-id (`,` ssa-id)*
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// Uses of an SSA value, e.g. in an operand list to an operation.
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ssa-use ::= ssa-id
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ssa-use-list ::= ssa-use (`,` ssa-use)*
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```
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Identifiers name entities such as SSA values, types and functions, and are
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chosen by the writer of MLIR code. Identifiers may be descriptive (e.g.
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`%batch_size`, `@matmul`), or may be non-descriptive when they are
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auto-generated (e.g. `%23`, `@func42`). Identifier names for SSA values may be
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used in an MLIR text file but are not persisted as part of the IR - the printer
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will give them anonymous names like `%42`.
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MLIR guarantees identifiers never collide with keywords by prefixing identifiers
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with a sigil (e.g. `%`, `#`, `@`, `^`, `!`). In certain unambiguous contexts
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(e.g. affine expressions), identifiers are not prefixed, for brevity. New
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keywords may be added to future versions of MLIR without danger of collision
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with existing identifiers.
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The scope of SSA values is defined based on the standard definition of
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[dominance](https://en.wikipedia.org/wiki/Dominator_\(graph_theory\)). Argument
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identifiers in mapping functions are in scope for the mapping body. Function
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identifiers and mapping identifiers are visible across the entire module.
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2019-08-23 06:53:41 +08:00
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## Dialects
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Dialects are the mechanism in which to engage with and extend the MLIR
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ecosystem. They allow for defining new [operations](#operations), as well as
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[attributes](#attributes) and [types](#type-system). Each dialect is given a
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unique `namespace` that is prefixed to each defined attribute/operation/type.
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For example, the [Affine dialect](Dialects/Affine.md) defines the namespace:
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`affine`.
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MLIR allows for multiple dialects, even those outside of the main tree, to
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co-exist together within one module. Dialects are produced and consumed by
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certain passes. MLIR provides a [framework](DialectConversion.md) to convert
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between, and within different dialects.
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A few of the dialects supported by MLIR:
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* [Affine dialect](Dialects/Affine.md)
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* [GPU dialect](Dialects/GPU.md)
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* [LLVM dialect](Dialects/LLVM.md)
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* [SPIR-V dialect](Dialects/SPIR-V.md)
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* [Standard dialect](Dialects/Standard.md)
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* [Vector dialect](Dialects/Vector.md)
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### Target specific operations
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Dialects provide a modular way in which targets can expose target-specific
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operations directly through to MLIR. As an example, some targets go through
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LLVM. LLVM has a rich set of intrinsics for certain target-independent
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operations (e.g. addition with overflow check) as well as providing access to
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target-specific operations for the targets it supports (e.g. vector permutation
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operations). LLVM intrinsics in MLIR are represented via operations that start
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with an "llvm." name.
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Example:
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```mlir {.mlir}
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// LLVM: %x = call {i16, i1} @llvm.sadd.with.overflow.i16(i16 %a, i16 %b)
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%x:2 = "llvm.sadd.with.overflow.i16"(%a, %b) : (i16, i16) -> (i16, i1)
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```
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These operations only work when targeting LLVM as a backend (e.g. for CPUs and
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GPUs), and are required to align with the LLVM definition of these intrinsics.
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2019-08-24 01:08:42 +08:00
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## Operations
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Syntax:
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``` {.ebnf}
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operation ::= op-result? string-literal `(` ssa-use-list? `)`
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(`[` successor-list `]`)? (`(` region-list `)`)?
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attribute-dict? `:` function-type
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op-result ::= ssa-id ((`:` integer-literal) | (`,` ssa-id)*) `=`
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successor-list ::= successor (`,` successor)*
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region-list ::= region (`,` region)*
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```
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MLIR introduces a uniform concept called _operations_ to enable describing many
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different levels of abstractions and computations. Operations in MLIR are fully
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extensible (there is no fixed list of operations), and have application-specific
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semantics. For example, MLIR supports
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[target-independent operations](Dialects/Standard.md#memory-operations),
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[affine operations](Dialects/Affine.md), and
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[target-specific machine operations](#target-specific-operations).
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The internal representation of an operation is simple: an operation is
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identified by a unique string (e.g. `dim`, `tf.Conv2d`, `x86.repmovsb`,
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`ppc.eieio`, etc), can return zero or more results, take zero or more SSA
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operands, may have zero or more attributes, may have zero or more successors,
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and zero or more enclosed [regions](#regions). The generic printing form
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includes all these elements literally, with a function type to indicate the
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types of the results and operands.
|
|
|
|
|
|
|
|
|
|
Example:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
// An operation that produces two results.
|
|
|
|
|
// The results of %result can be accessed via the <name> `#` <opNo> syntax.
|
|
|
|
|
%result:2 = "foo_div"() : () -> (f32, i32)
|
|
|
|
|
|
|
|
|
|
// Pretty form that defines a unique name for each result.
|
|
|
|
|
%foo, %bar = "foo_div"() : () -> (f32, i32)
|
|
|
|
|
|
|
|
|
|
// Invoke a TensorFlow function called tf.scramble with two inputs
|
|
|
|
|
// and an attribute "fruit".
|
|
|
|
|
%2 = "tf.scramble"(%result#0, %bar) {fruit: "banana"} : (f32, i32) -> f32
|
|
|
|
|
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
These are a special class of operations that *must* terminate a block, for
|
|
|
|
|
example [branches](Dialects/Standard.md#terminator-operations). These operations
|
|
|
|
|
may also have a list of successors ([blocks](#blocks) and their arguments).
|
|
|
|
|
|
|
|
|
|
Example:
|
|
|
|
|
|
|
|
|
|
```mlir {.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
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-10-04 01:04:05 +08:00
|
|
|
|
module ::= `module` symbol-ref-id? (`attributes` attribute-dict)? region
|
2019-08-24 01:08:42 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
An MLIR module represents an opaque top-level container operation. It contains a
|
|
|
|
|
single region containing a single block that is comprised of any operations.
|
|
|
|
|
Operations within this region must not implicitly capture values defined above
|
2019-10-04 01:04:05 +08:00
|
|
|
|
it. Modules have an optional symbol name that can be used to refer to them in
|
|
|
|
|
operations.
|
2019-08-24 01:08:42 +08:00
|
|
|
|
|
|
|
|
|
### Functions
|
|
|
|
|
|
|
|
|
|
An MLIR Function is an operation with a name containing one [region](#regions).
|
|
|
|
|
The region of a function is not allowed to implicitly capture values defined
|
2019-09-26 02:57:13 +08:00
|
|
|
|
outside of the function, and all external references must use function arguments
|
|
|
|
|
or attributes that establish a symbolic connection (e.g. symbols referenced by
|
2019-08-24 01:08:42 +08:00
|
|
|
|
name via a string attribute like [SymbolRefAttr](#symbol-reference-attribute)):
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
function ::= `func` function-signature function-attributes? function-body?
|
|
|
|
|
|
|
|
|
|
function-signature ::= symbol-ref-id `(` argument-list `)`
|
|
|
|
|
(`->` function-result-type)?
|
|
|
|
|
argument-list ::= (named-argument (`,` named-argument)*) | /*empty*/
|
|
|
|
|
argument-list ::= (type attribute-dict? (`,` type attribute-dict?)*) | /*empty*/
|
|
|
|
|
named-argument ::= ssa-id `:` type attribute-dict?
|
|
|
|
|
|
|
|
|
|
function-attributes ::= `attributes` attribute-dict
|
|
|
|
|
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.
|
|
|
|
|
|
|
|
|
|
Examples:
|
|
|
|
|
|
|
|
|
|
```mlir {.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
|
|
|
|
|
}
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
## Blocks
|
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
block ::= bb-label operation+
|
|
|
|
|
bb-label ::= bb-id bb-arg-list? `:`
|
|
|
|
|
bb-id ::= caret-id
|
|
|
|
|
ssa-id-and-type ::= ssa-id `:` type
|
|
|
|
|
|
|
|
|
|
// Non-empty list of names and types.
|
|
|
|
|
ssa-id-and-type-list ::= ssa-id-and-type (`,` ssa-id-and-type)*
|
|
|
|
|
|
|
|
|
|
bb-arg-list ::= `(` ssa-id-and-type-list? `)`
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
A [block](https://en.wikipedia.org/wiki/Basic_block) is a sequential list of
|
|
|
|
|
operations without control flow (calls are not considered control flow for this
|
|
|
|
|
purpose) that are executed from top to bottom. The last operation in a block is
|
|
|
|
|
a [terminator operation](#terminator-operations), which ends the block.
|
|
|
|
|
|
|
|
|
|
Blocks in MLIR take a list of block arguments, which represent SSA PHI nodes in
|
|
|
|
|
a functional notation. The arguments are defined by the block, and values are
|
|
|
|
|
provided for these block arguments by branches that go to the block.
|
|
|
|
|
|
|
|
|
|
Here is a simple example function showing branches, returns, and block
|
|
|
|
|
arguments:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
func @simple(i64, i1) -> i64 {
|
|
|
|
|
^bb0(%a: i64, %cond: i1): // Code dominated by ^bb0 may refer to %a
|
|
|
|
|
cond_br %cond, ^bb1, ^bb2
|
|
|
|
|
|
|
|
|
|
^bb1:
|
|
|
|
|
br ^bb3(%a: i64) // Branch passes %a as the argument
|
|
|
|
|
|
|
|
|
|
^bb2:
|
|
|
|
|
%b = addi %a, %a : i64
|
|
|
|
|
br ^bb3(%b: i64) // Branch passes %b as the argument
|
|
|
|
|
|
|
|
|
|
// ^bb3 receives an argument, named %c, from predecessors
|
|
|
|
|
// and passes it on to bb4 twice.
|
|
|
|
|
^bb3(%c: i64):
|
|
|
|
|
br ^bb4(%c, %c : i64, i64)
|
|
|
|
|
|
|
|
|
|
^bb4(%d : i64, %e : i64):
|
|
|
|
|
%0 = addi %d, %e : i64
|
|
|
|
|
return %0 : i64
|
|
|
|
|
}
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
**Context:** The "block argument" representation eliminates a number of special
|
|
|
|
|
cases from the IR compared to traditional "PHI nodes are operations" SSA IRs
|
|
|
|
|
(like LLVM). For example, the
|
|
|
|
|
[parallel copy semantics](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.524.5461&rep=rep1&type=pdf)
|
|
|
|
|
of SSA is immediately apparent, and function arguments are no longer a special
|
|
|
|
|
case: they become arguments to the entry block
|
|
|
|
|
[[more rationale](Rationale.md#block-arguments-vs-phi-nodes)].
|
|
|
|
|
|
|
|
|
|
## Regions
|
|
|
|
|
|
|
|
|
|
### Definition
|
|
|
|
|
|
|
|
|
|
A region is a CFG of MLIR [Blocks](#blocks). Regions serve to group semantically
|
|
|
|
|
connected blocks, where the semantics is not imposed by the IR. Instead, the
|
|
|
|
|
containing operation defines the semantics of the regions it contains. Regions
|
|
|
|
|
do not have a name or an address, only the blocks contained in a region do.
|
|
|
|
|
Regions are meaningless outside of the containing entity and have no type or
|
|
|
|
|
attributes.
|
|
|
|
|
|
|
|
|
|
The first block in the region cannot be a successor of any other block. The
|
|
|
|
|
syntax for the region is as follows:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
region ::= `{` block+ `}`
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
The function body is an example of a region: it consists of a CFG of blocks and
|
|
|
|
|
has additional semantic restrictions that other types of regions may not have
|
|
|
|
|
(block terminators must either branch to a different block, or return from a
|
|
|
|
|
function where the types of the `return` arguments must match the result types
|
|
|
|
|
of the function signature).
|
|
|
|
|
|
|
|
|
|
### Control and Value Scoping
|
|
|
|
|
|
|
|
|
|
Regions provide nested control isolation: it is impossible to branch to a block
|
|
|
|
|
within a region from outside it, or to branch from within a region to a block
|
|
|
|
|
outside it. Similarly it provides a natural scoping for value visibility: SSA
|
|
|
|
|
values defined in a region don't escape to the enclosing region if any. By
|
|
|
|
|
default, a region can reference values defined outside of the region, whenever
|
|
|
|
|
it would have been legal to use them as operands to the enclosing operation.
|
|
|
|
|
|
|
|
|
|
Example:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
func @accelerator_compute(i64, i1) -> i64 {
|
|
|
|
|
^bb0(%a: i64, %cond: i1): // Code dominated by ^bb0 may refer to %a
|
|
|
|
|
cond_br %cond, ^bb1, ^bb2
|
|
|
|
|
|
|
|
|
|
^bb1:
|
|
|
|
|
// This def for %value does not dominate ^bb2
|
|
|
|
|
%value = "op.convert"(%a) : (i64) -> i64
|
|
|
|
|
br ^bb3(%a: i64) // Branch passes %a as the argument
|
|
|
|
|
|
|
|
|
|
^bb2:
|
|
|
|
|
"accelerator.launch"() {
|
|
|
|
|
^bb0:
|
2019-09-26 02:57:13 +08:00
|
|
|
|
// Region of code nested under "accelerator.launch", it can reference %a but
|
2019-08-24 01:08:42 +08:00
|
|
|
|
// not %value.
|
|
|
|
|
%new_value = "accelerator.do_something"(%a) : (i64) -> ()
|
|
|
|
|
}
|
|
|
|
|
// %new_value cannot be referenced outside of the region
|
2019-09-26 02:57:13 +08:00
|
|
|
|
|
|
|
|
|
^bb3:
|
|
|
|
|
...
|
2019-08-24 01:08:42 +08:00
|
|
|
|
}
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
This can be further restricted using the custom verifier associated with the
|
|
|
|
|
enclosing operation, for example, disallowing references to values defined
|
|
|
|
|
outside the region completely.
|
|
|
|
|
|
|
|
|
|
### Control Flow
|
|
|
|
|
|
|
|
|
|
Regions are Single-Entry-Multiple-Exit (SEME). This means that control can only
|
|
|
|
|
flow into the first block of the region, but can flow out of the region at the
|
|
|
|
|
end of any of the contained blocks (This behavior is similar to that of a
|
|
|
|
|
function body in most programming languages). When exiting a Region, control is
|
|
|
|
|
returned to the enclosing operation.
|
|
|
|
|
|
|
|
|
|
The enclosing operation determines the way in which control is transmitted into
|
|
|
|
|
the entry block of a Region. The successor to a region’s exit points may not
|
|
|
|
|
necessarily exist: for example a call to a function that does not return.
|
|
|
|
|
Concurrent or asynchronous execution of regions is unspecified. Operations may
|
|
|
|
|
define specific rules of execution, e.g. sequential loops or switch cases.
|
|
|
|
|
|
|
|
|
|
A Region may also enter another region within the enclosing operation. If an
|
|
|
|
|
operation has multiple regions, the semantics of the operation defines into
|
|
|
|
|
which regions the control flows and in which order, if any. An operation may
|
|
|
|
|
transmit control into regions that were specified in other operations, in
|
|
|
|
|
particular those that defined the values the given operation uses. Thus such
|
|
|
|
|
operations can be treated opaquely in the enclosing control flow graph,
|
|
|
|
|
providing a level of control flow isolation similar to that of the call
|
|
|
|
|
operation.
|
|
|
|
|
|
|
|
|
|
#### Closure
|
|
|
|
|
|
|
|
|
|
Regions allow defining an operation that creates a closure, for example by
|
|
|
|
|
“boxing” the body of the region into a value they produce. It remains up to the
|
|
|
|
|
operation to define its semantics. Note that if an operation triggers
|
|
|
|
|
asynchronous execution of the region, it is under the responsibility of the
|
|
|
|
|
operation caller to wait for the region to be executed guaranteeing that any
|
|
|
|
|
directly used values remain live.
|
|
|
|
|
|
|
|
|
|
### Arguments and Results
|
|
|
|
|
|
|
|
|
|
The arguments of the first block of a region are treated as arguments of the
|
|
|
|
|
region. The source of these arguments is defined by the semantics of the parent
|
|
|
|
|
operation. They may correspond to some of the values the operation itself uses.
|
|
|
|
|
|
|
|
|
|
Regions produce a (possibly empty) list of values. The operation semantics
|
|
|
|
|
defines the relation between the region results and the operation results.
|
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
## Type System
|
|
|
|
|
|
|
|
|
|
Each SSA 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 standard types do not include structures, arrays, or
|
|
|
|
|
dictionaries.
|
|
|
|
|
|
|
|
|
|
MLIR has an open type system (there is no fixed list of types), and types may
|
|
|
|
|
have application-specific semantics. For example, MLIR supports a set of
|
|
|
|
|
[standard types](#standard-types) as well as [dialect types](#dialect-types).
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
type ::= type-alias | dialect-type | standard-type
|
|
|
|
|
|
|
|
|
|
type-list-no-parens ::= type (`,` type)*
|
|
|
|
|
type-list-parens ::= `(` `)`
|
|
|
|
|
| `(` type-list-no-parens `)`
|
|
|
|
|
|
|
|
|
|
// This is a common way to refer to an SSA value with a specified type.
|
|
|
|
|
ssa-use-and-type ::= ssa-use `:` type
|
|
|
|
|
|
|
|
|
|
// Non-empty list of names and types.
|
|
|
|
|
ssa-use-and-type-list ::= ssa-use-and-type (`,` ssa-use-and-type)*
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
### Type Aliases
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
type-alias-def ::= '!' alias-name '=' 'type' type
|
|
|
|
|
type-alias ::= '!' alias-name
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
MLIR supports defining named aliases for types. A type alias is an identifier
|
|
|
|
|
that can be used in the place of the type that it defines. These aliases *must*
|
|
|
|
|
be defined before their uses. Alias names may not contain a '.', since those
|
|
|
|
|
names are reserved for [dialect types](#dialect-types).
|
|
|
|
|
|
|
|
|
|
Example:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
!avx_m128 = type vector<4 x f32>
|
|
|
|
|
|
|
|
|
|
// Using the original type.
|
|
|
|
|
"foo"(%x) : vector<4 x f32> -> ()
|
|
|
|
|
|
|
|
|
|
// Using the type alias.
|
|
|
|
|
"foo"(%x) : !avx_m128 -> ()
|
|
|
|
|
```
|
|
|
|
|
|
2019-08-23 08:51:06 +08:00
|
|
|
|
### Dialect Types
|
2019-08-23 06:53:41 +08:00
|
|
|
|
|
|
|
|
|
Similarly to operations, dialects may define custom extensions to the type
|
2019-08-23 07:43:06 +08:00
|
|
|
|
system.
|
2019-08-23 06:53:41 +08:00
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
dialect-type ::= '!' dialect-namespace '<' '"' type-specific-data '"' '>'
|
|
|
|
|
dialect-type ::= '!' alias-name pretty-dialect-type-body?
|
|
|
|
|
|
|
|
|
|
pretty-dialect-type-body ::= '<' pretty-dialect-type-contents+ '>'
|
|
|
|
|
pretty-dialect-type-contents ::= pretty-dialect-type-body
|
|
|
|
|
| '(' pretty-dialect-type-contents+ ')'
|
|
|
|
|
| '[' pretty-dialect-type-contents+ ']'
|
|
|
|
|
| '{' pretty-dialect-type-contents+ '}'
|
|
|
|
|
| '[^[<({>\])}\0]+'
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
Dialect types can be specified in a verbose form, e.g. like this:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
// LLVM type that wraps around llvm IR types.
|
|
|
|
|
!llvm<"i32*">
|
|
|
|
|
|
|
|
|
|
// Tensor flow string type.
|
|
|
|
|
!tf.string
|
|
|
|
|
|
|
|
|
|
// Complex type
|
|
|
|
|
!foo<"something<abcd>">
|
|
|
|
|
|
|
|
|
|
// Even more complex type
|
|
|
|
|
!foo<"something<a%%123^^^>>>">
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
Dialect types that are simple enough can use the pretty format, which is a
|
|
|
|
|
lighter weight syntax that is equivalent to the above forms:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
// Tensor flow string type.
|
|
|
|
|
!tf.string
|
|
|
|
|
|
|
|
|
|
// Complex type
|
|
|
|
|
!foo.something<abcd>
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
Sufficiently complex dialect types are required to use the verbose form for
|
|
|
|
|
generality. For example, the more complex type shown above wouldn't be valid in
|
|
|
|
|
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](DefiningAttributesAndTypes.md) to learn how to define dialect types.
|
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
### Standard Types
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
Standard 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.
|
2019-01-03 04:32:30 +08:00
|
|
|
|
|
2018-10-25 00:47:36 +08:00
|
|
|
|
``` {.ebnf}
|
2019-08-23 07:43:06 +08:00
|
|
|
|
standard-type ::= complex-type
|
2019-02-06 03:47:02 +08:00
|
|
|
|
| float-type
|
2019-08-23 07:43:06 +08:00
|
|
|
|
| function-type
|
|
|
|
|
| index-type
|
|
|
|
|
| integer-type
|
2019-02-06 03:47:02 +08:00
|
|
|
|
| memref-type
|
2019-04-28 09:35:04 +08:00
|
|
|
|
| none-type
|
2019-08-23 07:43:06 +08:00
|
|
|
|
| tensor-type
|
|
|
|
|
| tuple-type
|
|
|
|
|
| vector-type
|
2018-10-25 00:47:36 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
#### Complex Type
|
|
|
|
|
|
|
|
|
|
Syntax:
|
2019-01-08 10:42:04 +08:00
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-08-23 07:43:06 +08:00
|
|
|
|
complex-type ::= `complex` `<` type `>`
|
2019-01-08 10:42:04 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
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.
|
2019-01-08 10:42:04 +08:00
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
Examples:
|
2019-01-08 10:42:04 +08:00
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
2019-08-23 07:43:06 +08:00
|
|
|
|
complex<f32>
|
|
|
|
|
complex<i32>
|
|
|
|
|
```
|
2019-01-08 10:42:04 +08:00
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
#### Floating Point Types
|
2019-01-08 10:42:04 +08:00
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
Syntax:
|
2019-01-08 10:42:04 +08:00
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
``` {.ebnf}
|
|
|
|
|
// Floating point.
|
|
|
|
|
float-type ::= `f16` | `bf16` | `f32` | `f64`
|
|
|
|
|
```
|
2019-01-08 01:59:55 +08:00
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
MLIR supports float types of certain widths that are widely used as indicated
|
|
|
|
|
above.
|
2019-01-08 01:59:55 +08:00
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Function Type
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-03-20 01:59:02 +08:00
|
|
|
|
// MLIR functions can return multiple values.
|
2019-02-06 03:47:02 +08:00
|
|
|
|
function-result-type ::= type-list-parens
|
|
|
|
|
| non-function-type
|
|
|
|
|
|
|
|
|
|
function-type ::= type-list-parens `->` function-result-type
|
2018-10-25 00:47:36 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-08-21 09:41:38 +08:00
|
|
|
|
MLIR supports first-class functions: for example, the
|
|
|
|
|
[`constant` operation](Dialects/Standard.md#constant-operation) produces the
|
|
|
|
|
address of a function as an SSA value. This SSA 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).
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-01-08 01:59:55 +08:00
|
|
|
|
Function types are also used to indicate the arguments and results of
|
|
|
|
|
[operations](#operations).
|
Enable arithmetics for index types.
Arithmetic and comparison instructions are necessary to implement, e.g.,
control flow when lowering MLFunctions to CFGFunctions. (While it is possible
to replace some of the arithmetics by affine_apply instructions for loop
bounds, it is still necessary for loop bounds checking, steps, if-conditions,
non-trivial memref subscripts, etc.) Furthermore, working with indirect
accesses in, e.g., lookup tables for large embeddings, may require operating on
tensors of indexes. For example, the equivalents to C code "LUT[Index[i]]" or
"ResultIndex[i] = i + j" where i, j are loop induction variables require the
arithmetics on indices as well as the possibility to operate on tensors
thereof. Allow arithmetic and comparison operations to apply to index types by
declaring them integer-like. Allow tensors whose element type is index for
indirection purposes.
The absence of vectors with "index" element type is explicitly tested, but the
only justification for this restriction in the CL introducing the test is
"because we don't need them". Do NOT enable vectors of index types, although
it makes vector and tensor types inconsistent with respect to allowed element
types.
PiperOrigin-RevId: 220614055
2018-11-08 20:04:32 +08:00
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Index Type
|
Enable arithmetics for index types.
Arithmetic and comparison instructions are necessary to implement, e.g.,
control flow when lowering MLFunctions to CFGFunctions. (While it is possible
to replace some of the arithmetics by affine_apply instructions for loop
bounds, it is still necessary for loop bounds checking, steps, if-conditions,
non-trivial memref subscripts, etc.) Furthermore, working with indirect
accesses in, e.g., lookup tables for large embeddings, may require operating on
tensors of indexes. For example, the equivalents to C code "LUT[Index[i]]" or
"ResultIndex[i] = i + j" where i, j are loop induction variables require the
arithmetics on indices as well as the possibility to operate on tensors
thereof. Allow arithmetic and comparison operations to apply to index types by
declaring them integer-like. Allow tensors whose element type is index for
indirection purposes.
The absence of vectors with "index" element type is explicitly tested, but the
only justification for this restriction in the CL introducing the test is
"because we don't need them". Do NOT enable vectors of index types, although
it makes vector and tensor types inconsistent with respect to allowed element
types.
PiperOrigin-RevId: 220614055
2018-11-08 20:04:32 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
// Target word-sized integer.
|
|
|
|
|
index-type ::= `index`
|
|
|
|
|
```
|
|
|
|
|
|
2019-01-08 01:59:55 +08:00
|
|
|
|
The `index` type is a signless integer whose size is equal to the natural
|
|
|
|
|
machine word of the target ([rationale](Rationale.md#signless-types)) and is
|
2019-09-25 03:44:11 +08:00
|
|
|
|
used by the affine constructs in MLIR. Unlike fixed-size integers, it cannot be
|
2019-01-08 01:59:55 +08:00
|
|
|
|
used as an element of vector, tensor or memref type
|
2019-04-05 23:19:42 +08:00
|
|
|
|
([rationale](Rationale.md#index-type-disallowed-in-vectortensormemref-types)).
|
2019-01-08 01:59:55 +08:00
|
|
|
|
|
Enable arithmetics for index types.
Arithmetic and comparison instructions are necessary to implement, e.g.,
control flow when lowering MLFunctions to CFGFunctions. (While it is possible
to replace some of the arithmetics by affine_apply instructions for loop
bounds, it is still necessary for loop bounds checking, steps, if-conditions,
non-trivial memref subscripts, etc.) Furthermore, working with indirect
accesses in, e.g., lookup tables for large embeddings, may require operating on
tensors of indexes. For example, the equivalents to C code "LUT[Index[i]]" or
"ResultIndex[i] = i + j" where i, j are loop induction variables require the
arithmetics on indices as well as the possibility to operate on tensors
thereof. Allow arithmetic and comparison operations to apply to index types by
declaring them integer-like. Allow tensors whose element type is index for
indirection purposes.
The absence of vectors with "index" element type is explicitly tested, but the
only justification for this restriction in the CL introducing the test is
"because we don't need them". Do NOT enable vectors of index types, although
it makes vector and tensor types inconsistent with respect to allowed element
types.
PiperOrigin-RevId: 220614055
2018-11-08 20:04:32 +08:00
|
|
|
|
**Rationale:** integers of platform-specific bit widths are practical to express
|
|
|
|
|
sizes, dimensionalities and subscripts.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Integer Type
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-01-08 01:59:55 +08:00
|
|
|
|
// Sized integers like i1, i4, i8, i16, i32.
|
2019-04-23 22:58:03 +08:00
|
|
|
|
integer-type ::= `i` [1-9][0-9]*
|
2018-10-25 00:47:36 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-01-08 01:59:55 +08:00
|
|
|
|
MLIR supports arbitrary precision integer types. Integer types are signless, but
|
|
|
|
|
have a designated width.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-01-08 01:59:55 +08:00
|
|
|
|
**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).
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-01-08 01:59:55 +08:00
|
|
|
|
TODO: Need to decide on a representation for quantized integers
|
|
|
|
|
([initial thoughts](Rationale.md#quantized-integer-operations)).
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Memref Type
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
memref-type ::= `memref` `<` dimension-list-ranked tensor-memref-element-type
|
2019-10-04 03:33:47 +08:00
|
|
|
|
(`,` layout-specification)? |
|
|
|
|
|
(`,` memory-space)? `>`
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-10-04 03:33:47 +08:00
|
|
|
|
stride-list ::= `[` (dimension (`,` dimension)*)? `]`
|
|
|
|
|
strided-layout ::= `offset:` dimension `,` `strides: ` stride-list
|
|
|
|
|
layout-specification ::= semi-affine-map | strided-layout
|
2018-10-25 00:47:36 +08:00
|
|
|
|
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
|
2019-04-25 04:25:49 +08:00
|
|
|
|
tensor types, but do not allow unknown rank. 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.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-10-04 03:33:47 +08:00
|
|
|
|
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.
|
|
|
|
|
|
2018-10-25 00:47:36 +08:00
|
|
|
|
The memory space of a memref is specified by a target-specific integer index. If
|
|
|
|
|
no memory space is specified, then the default memory space (0) is used. The
|
|
|
|
|
default space is target specific but always at index 0.
|
|
|
|
|
|
|
|
|
|
TODO: MLIR will eventually have target-dialects which allow symbolic use of
|
2019-04-06 09:34:49 +08:00
|
|
|
|
memory hierarchy names (e.g. L3, L2, L1, ...) but we have not spec'd the details
|
2018-10-25 00:47:36 +08:00
|
|
|
|
of that mechanism yet. Until then, this document pretends that it is valid to
|
2019-08-17 02:00:31 +08:00
|
|
|
|
refer to these memories by `bare-id`.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
2018-11-14 23:52:12 +08:00
|
|
|
|
```mlir {.mlir}
|
2018-10-25 00:47:36 +08:00
|
|
|
|
// Identity index/layout map
|
2019-09-23 01:14:11 +08:00
|
|
|
|
#identity = (d0, d1) -> (d0, d1)
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
// Column major layout.
|
2019-09-23 01:14:11 +08:00
|
|
|
|
#col_major = (d0, d1, d2) -> (d2, d1, d0)
|
|
|
|
|
|
|
|
|
|
// A 2-d tiled layout with tiles of size 128 x 256.
|
|
|
|
|
#tiled_2d_128x256 = (d0, d1) -> (d0 div 128, d1 div 256, d0 mod 128, d0 mod 256)
|
|
|
|
|
|
|
|
|
|
// A tiled data layout with non-constant tile sizes.
|
|
|
|
|
#tiled_dynamic = (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 = (d0, d1) -> (d0, (d1 + 2) floordiv 2, (d1 + 2) mod 2)
|
|
|
|
|
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
// The dimension list "16x32" defines the following 2D index space:
|
|
|
|
|
//
|
|
|
|
|
// { (i, j) : 0 <= i < 16, 0 <= j < 32 }
|
|
|
|
|
//
|
2019-09-23 01:14:11 +08:00
|
|
|
|
memref<16x32xf32, #identity, memspace0>
|
|
|
|
|
|
2018-10-25 00:47:36 +08:00
|
|
|
|
// 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.
|
2019-09-23 01:14:11 +08:00
|
|
|
|
//
|
|
|
|
|
// %N here binds to the size of the third dimension.
|
|
|
|
|
%A = alloc(%N) : memref<16x4x?xf32, #col_major, memspace0>
|
|
|
|
|
|
|
|
|
|
// 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.
|
2019-10-09 01:21:26 +08:00
|
|
|
|
// The allocation size will be (%M ceildiv %B1) * %B1 * (%N ceildiv %B2) * %B2
|
2019-09-23 01:14:11 +08:00
|
|
|
|
// f32 elements.
|
|
|
|
|
%T = alloc(%M, %N) [%B1, %B2] : memref<?x?xf32, #tiled_dynamic>
|
|
|
|
|
|
2019-09-26 02:57:13 +08:00
|
|
|
|
// A memref that has a two-element padding at either end. The allocation size
|
2019-09-23 01:14:11 +08:00
|
|
|
|
// will fit 16 * 68 float elements of data.
|
|
|
|
|
%P = alloc() : memref<16x64xf32, #padded>
|
|
|
|
|
|
|
|
|
|
// Affine map with symbol 's0' used as offset for the first dimension.
|
|
|
|
|
#imapS = (d0, d1) [s0] -> (d0 + s0, d1)
|
2018-10-25 00:47:36 +08:00
|
|
|
|
// 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 = ...
|
2019-09-23 01:14:11 +08:00
|
|
|
|
%A = alloc (%n)[%o] : <16x?xf32, #imapS>
|
2018-10-25 00:47:36 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
##### Index Space
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
A memref dimension list defines an index space within which the memref can be
|
|
|
|
|
indexed to access data.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
##### Index
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
Data is accessed through a memref type using a multidimensional index into the
|
|
|
|
|
multidimensional index space defined by the memref's dimension list.
|
|
|
|
|
|
|
|
|
|
Examples
|
|
|
|
|
|
2018-11-14 23:52:12 +08:00
|
|
|
|
```mlir {.mlir}
|
2018-10-25 00:47:36 +08:00
|
|
|
|
// Allocates a memref with 2D index space:
|
|
|
|
|
// { (i, j) : 0 <= i < 16, 0 <= j < 32 }
|
2019-04-06 09:34:49 +08:00
|
|
|
|
%A = alloc() : memref<16x32xf32, #imapA, memspace0>
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
// Loads data from memref '%A' using a 2D index: (%i, %j)
|
2019-04-06 09:34:49 +08:00
|
|
|
|
%v = load %A[%i, %j] : memref<16x32xf32, #imapA, memspace0>
|
2018-10-25 00:47:36 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
##### Index Map
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
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.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
![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.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
##### Layout Map
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
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.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
Layout map examples:
|
|
|
|
|
|
2018-11-14 23:52:12 +08:00
|
|
|
|
```mlir {.mlir}
|
2018-10-25 00:47:36 +08:00
|
|
|
|
// MxN matrix stored in row major layout in memory:
|
2019-09-23 01:14:11 +08:00
|
|
|
|
#layout_map_row_major = (i, j) -> (i, j)
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
// MxN matrix stored in column major layout in memory:
|
2019-09-23 01:14:11 +08:00
|
|
|
|
#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)
|
2018-10-25 00:47:36 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
##### Affine Map Composition
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
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
|
2019-03-30 04:15:06 +08:00
|
|
|
|
used to index the memref in load/store operations to other index spaces (i.e.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
logical to physical index mapping). Each of the
|
2019-08-23 07:43:06 +08:00
|
|
|
|
[semi-affine maps](Dialects/Affine.md) and thus its composition is required to
|
|
|
|
|
be one-to-one.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
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.
|
|
|
|
|
|
2019-10-04 03:33:47 +08:00
|
|
|
|
##### 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 outer 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.
|
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
#### None Type
|
2019-03-30 13:23:34 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-08-23 07:43:06 +08:00
|
|
|
|
none-type ::= `none`
|
2019-03-30 13:23:34 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
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:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
tensor-type ::= `tensor` `<` dimension-list tensor-memref-element-type `>`
|
|
|
|
|
tensor-memref-element-type ::= vector-element-type | vector-type
|
|
|
|
|
|
|
|
|
|
// memref requires a known rank, but tensor does not.
|
|
|
|
|
dimension-list ::= dimension-list-ranked | (`*` `x`)
|
|
|
|
|
dimension-list-ranked ::= (dimension `x`)*
|
|
|
|
|
dimension ::= `?` | decimal-literal
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
SSA values of 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.
|
2019-03-30 13:23:34 +08:00
|
|
|
|
|
|
|
|
|
Examples:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
2019-08-23 07:43:06 +08:00
|
|
|
|
// 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>
|
2019-03-30 13:23:34 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Tuple Type
|
2019-03-20 01:59:02 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
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
|
2019-04-05 23:19:42 +08:00
|
|
|
|
([rationale](Rationale.md#tuple-types)).
|
2019-03-20 01:59:02 +08:00
|
|
|
|
|
|
|
|
|
Examples:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
// Empty tuple.
|
|
|
|
|
tuple<>
|
|
|
|
|
|
|
|
|
|
// Single element
|
|
|
|
|
tuple<f32>
|
|
|
|
|
|
|
|
|
|
// Many elements.
|
|
|
|
|
tuple<i32, f32, tensor<i1>, i5>
|
|
|
|
|
```
|
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
#### Vector Type
|
2019-04-28 09:35:04 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-08-23 07:43:06 +08:00
|
|
|
|
vector-type ::= `vector` `<` static-dimension-list vector-element-type `>`
|
|
|
|
|
vector-element-type ::= float-type | integer-type
|
|
|
|
|
|
|
|
|
|
static-dimension-list ::= (decimal-literal `x`)+
|
2019-04-28 09:35:04 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-08-23 07:43:06 +08:00
|
|
|
|
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.
|
2019-04-28 09:35:04 +08:00
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
## Attributes
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
attribute-dict ::= `{` `}`
|
|
|
|
|
| `{` attribute-entry (`,` attribute-entry)* `}`
|
2019-03-03 14:34:18 +08:00
|
|
|
|
attribute-entry ::= dialect-attribute-entry | dependent-attribute-entry
|
2019-06-26 10:06:06 +08:00
|
|
|
|
dialect-attribute-entry ::= dialect-namespace `.` bare-id `=` attribute-value
|
|
|
|
|
dependent-attribute-entry ::= dependent-attribute-name `=` attribute-value
|
2019-03-03 14:34:18 +08:00
|
|
|
|
dependent-attribute-name ::= (letter|[_]) (letter|digit|[_$])*
|
2018-10-25 00:47:36 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-08-23 08:51:06 +08:00
|
|
|
|
Attributes are the mechanism for specifying constant data on operations in
|
|
|
|
|
places where a variable is never allowed - e.g. the index of a
|
2019-08-21 09:41:38 +08:00
|
|
|
|
[`dim` operation](Dialects/Standard.md#dim-operation), or the stride of a
|
2019-08-23 08:51:06 +08:00
|
|
|
|
convolution. They consist of a name and a concrete attribute value. The set of
|
|
|
|
|
expected attributes, their structure, and their interpretation are all
|
|
|
|
|
contextually dependent on what they are attached to.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
2019-03-03 14:34:18 +08:00
|
|
|
|
There are two main classes of attributes; dependent and dialect. Dependent
|
|
|
|
|
attributes derive their structure and meaning from what they are attached to,
|
|
|
|
|
e.g the meaning of the `index` attribute on a `dim` operation is defined by the
|
|
|
|
|
`dim` operation. Dialect attributes, on the other hand, derive their context and
|
|
|
|
|
meaning from a specific dialect. An example of a dialect attribute may be a
|
|
|
|
|
`swift.self` function argument attribute that indicates an argument is the
|
|
|
|
|
self/context parameter. The context of this attribute is defined by the `swift`
|
|
|
|
|
dialect and not the function argument.
|
|
|
|
|
|
2019-08-23 08:51:06 +08:00
|
|
|
|
Attributes values are represented by the following forms:
|
2019-03-03 14:34:18 +08:00
|
|
|
|
|
2019-08-23 08:51:06 +08:00
|
|
|
|
``` {.ebnf}
|
|
|
|
|
attribute-value ::= attribute-alias | dialect-attribute | standard-attribute
|
|
|
|
|
```
|
2019-03-03 14:34:18 +08:00
|
|
|
|
|
2019-08-23 08:51:06 +08:00
|
|
|
|
### Attribute Value Aliases
|
2019-03-03 14:34:18 +08:00
|
|
|
|
|
2019-08-23 08:51:06 +08:00
|
|
|
|
``` {.ebnf}
|
|
|
|
|
attribute-alias ::= '#' alias-name '=' 'type' type
|
|
|
|
|
attribute-alias ::= '#' alias-name
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
MLIR supports defining named aliases for attribute values. An attribute alias is
|
|
|
|
|
an identifier that can be used in the place of the attribute that it defines.
|
|
|
|
|
These aliases *must* be defined before their uses. Alias names may not contain a
|
|
|
|
|
'.', since those names are reserved for
|
|
|
|
|
[dialect attributes](#dialect-attribute-values).
|
|
|
|
|
|
|
|
|
|
Example:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
#map = (d0) -> (d0 + 10)
|
|
|
|
|
|
|
|
|
|
// Using the original attribute.
|
|
|
|
|
%b = affine.apply (d0) -> (d0 + 10) (%a)
|
|
|
|
|
|
|
|
|
|
// Using the attribute alias.
|
|
|
|
|
%b = affine.apply #map(%a)
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
### Dialect Attribute Values
|
|
|
|
|
|
|
|
|
|
Similarly to operations, dialects may define custom attribute values.
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
dialect-attribute ::= '#' dialect-namespace '<' '"' attr-specific-data '"' '>'
|
|
|
|
|
dialect-attribute ::= '#' alias-name pretty-dialect-attr-body?
|
|
|
|
|
|
|
|
|
|
pretty-dialect-attr-body ::= '<' pretty-dialect-attr-contents+ '>'
|
|
|
|
|
pretty-dialect-attr-contents ::= pretty-dialect-attr-body
|
|
|
|
|
| '(' pretty-dialect-attr-contents+ ')'
|
|
|
|
|
| '[' pretty-dialect-attr-contents+ ']'
|
|
|
|
|
| '{' pretty-dialect-attr-contents+ '}'
|
|
|
|
|
| '[^[<({>\])}\0]+'
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
Dialect attributes can be specified in a verbose form, e.g. like this:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
// Complex attribute
|
|
|
|
|
#foo<"something<abcd>">
|
|
|
|
|
|
|
|
|
|
// Even more complex attribute
|
|
|
|
|
#foo<"something<a%%123^^^>>>">
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
Dialect attributes that are simple enough can use the pretty format, which is a
|
|
|
|
|
lighter weight syntax that is equivalent to the above forms:
|
|
|
|
|
|
|
|
|
|
```mlir {.mlir}
|
|
|
|
|
// Complex attribute
|
|
|
|
|
#foo.something<abcd>
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
Sufficiently complex dialect attributes are required to use the verbose form for
|
|
|
|
|
generality. For example, the more complex type shown above wouldn't be valid in
|
|
|
|
|
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](DefiningAttributesAndTypes.md) to learn how to define dialect
|
|
|
|
|
attribute values.
|
|
|
|
|
|
|
|
|
|
### Standard Attribute Values
|
|
|
|
|
|
|
|
|
|
Standard attributes are a core set of
|
|
|
|
|
[dialect attributes](#dialect-attribute-values) that are defined in a builtin
|
|
|
|
|
dialect and thus available to all users of MLIR.
|
2018-10-25 00:47:36 +08:00
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-08-23 08:51:06 +08:00
|
|
|
|
standard-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
|
2018-10-25 00:47:36 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### AffineMap Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
affine-map-attribute ::= affine-map
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
An affine-map attribute is an attribute that represents a affine-map object.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Array Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
array-attribute ::= `[` (attribute-value (`,` attribute-value)*)? `]`
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
An array attribute is an attribute that represents a collection of attribute
|
|
|
|
|
values.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Boolean Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
bool-attribute ::= bool-literal
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
A boolean attribute is a literal attribute that represents a one-bit boolean
|
|
|
|
|
value, true or false.
|
|
|
|
|
|
2019-06-01 00:24:48 +08:00
|
|
|
|
#### Dictionary Attribute
|
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
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.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Elements Attributes
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
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.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
##### Dense Elements Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-06-26 07:06:13 +08:00
|
|
|
|
dense-elements-attribute ::= `dense` `<` attribute-value `>` `:`
|
|
|
|
|
( tensor-type | vector-type )
|
2019-02-13 04:55:40 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
A dense elements attribute is an elements attribute where the storage for the
|
|
|
|
|
constant vector or tensor value has been packed to the element bitwidth. The
|
|
|
|
|
element type of the vector or tensor constant must be of integer, index, or
|
|
|
|
|
floating point type.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
##### Opaque Elements Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
opaque-elements-attribute ::= `opaque` `<` dialect-namespace `,`
|
2019-06-26 07:06:13 +08:00
|
|
|
|
hex-string-literal `>` `:`
|
|
|
|
|
( tensor-type | vector-type )
|
2019-02-13 04:55:40 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
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.
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
##### Sparse Elements Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-06-26 07:06:13 +08:00
|
|
|
|
sparse-elements-attribute ::= `sparse` `<` attribute-value `,` attribute-value
|
|
|
|
|
`>` `:` ( tensor-type | vector-type )
|
2019-02-13 04:55:40 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
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 {.mlir}
|
2019-08-17 02:00:31 +08:00
|
|
|
|
sparse<[[0, 0], [1, 2]], [1, 5]> : tensor<3x4xi32>
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
// This represents the following tensor:
|
|
|
|
|
/// [[1, 0, 0, 0],
|
|
|
|
|
/// [0, 0, 5, 0],
|
|
|
|
|
/// [0, 0, 0, 0]]
|
|
|
|
|
```
|
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Float Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-08-17 02:00:31 +08:00
|
|
|
|
float-attribute ::= (float-literal (`:` float-type)?)
|
|
|
|
|
| (hexadecimal-literal `:` float-type)
|
2019-02-13 04:55:40 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
A float attribute is a literal attribute that represents a floating point value
|
2019-07-31 05:05:49 +08:00
|
|
|
|
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:
|
|
|
|
|
|
|
|
|
|
``` {.mlir}
|
|
|
|
|
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
|
|
|
|
|
```
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
2019-08-23 08:51:06 +08:00
|
|
|
|
#### Integer Attribute
|
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
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:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
integer-set-attribute ::= affine-map
|
|
|
|
|
```
|
|
|
|
|
|
2019-09-26 02:57:13 +08:00
|
|
|
|
An integer-set attribute is an attribute that represents an integer-set object.
|
2019-08-23 08:51:06 +08:00
|
|
|
|
|
2019-07-12 02:41:04 +08:00
|
|
|
|
#### String Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-07-12 02:41:04 +08:00
|
|
|
|
string-attribute ::= string-literal (`:` type)?
|
2019-02-13 04:55:40 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-07-12 02:41:04 +08:00
|
|
|
|
A string attribute is an attribute that represents a string literal value.
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
2019-07-12 02:41:04 +08:00
|
|
|
|
#### Symbol Reference Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
2019-07-12 02:41:04 +08:00
|
|
|
|
symbol-ref-attribute ::= symbol-ref-id
|
2019-02-13 04:55:40 +08:00
|
|
|
|
```
|
|
|
|
|
|
2019-07-12 02:41:04 +08:00
|
|
|
|
A symbol reference attribute is a literal attribute that represents a named
|
2019-10-09 01:21:26 +08:00
|
|
|
|
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.
|
|
|
|
|
|
|
|
|
|
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. If a reference to a symbol is necessary from outside
|
|
|
|
|
of the symbol table that the symbol is defined in, a
|
|
|
|
|
[string attribute](string-attribute) can be used to refer to the symbol name.
|
|
|
|
|
|
|
|
|
|
**Rationale:** Given that MLIR models global accesses with symbol references, to
|
|
|
|
|
enable efficient multi-threading, it becomes difficult to effectively reason
|
|
|
|
|
about their uses. By restricting the places that can legally hold a symbol
|
|
|
|
|
reference, we can always opaquely reason about a symbols usage characteristics.
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
2019-04-05 23:19:42 +08:00
|
|
|
|
#### Type Attribute
|
2019-02-13 04:55:40 +08:00
|
|
|
|
|
|
|
|
|
Syntax:
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
type-attribute ::= type
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
A type attribute is an attribute that represents a [type object](#type-system).
|
|
|
|
|
|
2019-04-26 00:56:09 +08:00
|
|
|
|
#### Unit Attribute
|
|
|
|
|
|
|
|
|
|
``` {.ebnf}
|
|
|
|
|
unit-attribute ::= `unit`
|
|
|
|
|
```
|
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A unit attribute is an attribute that represents a value of `unit` type. The
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`unit` type allows only one value forming a singleton set. This attribute value
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is used to represent attributes that only have meaning from their existence.
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One example of such an attribute could be the `swift.self` attribute. This
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attribute indicates that a function parameter is the self/context parameter. It
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could be represented as a [boolean attribute](#boolean-attribute)(true or
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false), but a value of false doesn't really bring any value. The parameter
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either is the self/context or it isn't.
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```mlir {.mlir}
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// A unit attribute defined with the `unit` value specifier.
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func @verbose_form(i1 {unitAttr : unit})
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// A unit attribute can also be defined without the value specifier.
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func @simple_form(i1 {unitAttr})
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```
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