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[mlir][tensor][linalg] Move Pack/UnPack Ops to Linalg (#123902)
Moves `PackOp` and `UnPackOp` from the Tensor dialect to Linalg. This change was discussed in the following RFC: * https://discourse.llvm.org/t/rfc-move-tensor-pack-and-tensor-unpack-into-linalg This change involves significant churn but only relocates existing code - no new functionality is added. **Note for Downstream Users** Downstream users must update references to `PackOp` and `UnPackOp` as follows: * Code: `s/tensor::(Up)PackOp/linalg::(Un)PackOp/g` * Tests: `s/tensor.(un)pack/linalg.(un)pack/g` No other modifications should be required.
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mlir/include/mlir/Dialect/Linalg/IR/LinalgRelayoutOps.td
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//===- LinalgReleayoutOps.td - Linalg relayout ops ---------*- tablegen -*-===// | ||
// | ||
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. | ||
// See https://llvm.org/LICENSE.txt for license information. | ||
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception | ||
// | ||
//===----------------------------------------------------------------------===// | ||
// | ||
// This file defines Pack + Unpack Ops that have been moved from the Tensor | ||
// dialect. As such, these are defined as memory-effect-free and only accept | ||
// "tensors" as inputs. | ||
// | ||
// TODO: Once a good motivating example is identified, relax these | ||
// restrictions. | ||
// | ||
//===----------------------------------------------------------------------===// | ||
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#ifndef LINALG_RELEAYOUT_OPS | ||
#define LINALG_RELEAYOUT_OPS | ||
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include "mlir/Dialect/Linalg/IR/LinalgBase.td" | ||
include "mlir/Interfaces/DestinationStyleOpInterface.td" | ||
include "mlir/Interfaces/SideEffectInterfaces.td" | ||
include "mlir/Interfaces/InferTypeOpInterface.td" | ||
include "mlir/Dialect/Linalg/IR/LinalgInterfaces.td" | ||
include "mlir/IR/OpAsmInterface.td" | ||
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//===----------------------------------------------------------------------===// | ||
// RelayoutOp | ||
//===----------------------------------------------------------------------===// | ||
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class Linalg_RelayoutOp<string mnemonic, list<Trait> traits = []> : | ||
Op<Linalg_Dialect, mnemonic, !listconcat(traits, [ | ||
DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>, | ||
DestinationStyleOpInterface, LinalgRelayoutOpInterface, | ||
ConditionallySpeculatable, NoMemoryEffect, | ||
DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>, | ||
TypesMatchWith<"result type matches type of dest", | ||
"dest", "result", | ||
"$_self">])> { | ||
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code commonExtraClassDeclaration = [{ | ||
size_t getSourceRank() { return getSourceType().getRank(); }; | ||
size_t getDestRank() { return getDestType().getRank(); }; | ||
RankedTensorType getSourceType() { | ||
return ::llvm::cast<RankedTensorType>(getSource().getType()); }; | ||
RankedTensorType getDestType() { | ||
return ::llvm::cast<RankedTensorType>(getDest().getType()); }; | ||
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MutableOperandRange getDpsInitsMutable() { return getDestMutable(); } | ||
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/// Interface method for ConditionallySpeculatable. | ||
Speculation::Speculatability getSpeculatability(); | ||
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/// Return a mapping from positions `inner_dims_pos` to their | ||
/// tile factors. | ||
DenseMap<int64_t, OpFoldResult> getDimAndTileMapping(); | ||
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/// Return the tile sizes as OpFoldResult. | ||
SmallVector<OpFoldResult> getMixedTiles(); | ||
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/// Return the tile sizes as `int64_t`. If a tile size is dynamic | ||
/// a sentinel `kDynamic` is introduced at that position in | ||
/// the returned vector. | ||
SmallVector<int64_t> getStaticTiles(); | ||
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/// Retrieve all outer dims for this Pack/UnPack Op, i.e. all the leading | ||
/// dims excluding the trailing dims corresponding to `innerTiles`. Note | ||
/// that this will include both tiled and non-tiled dimensions. The order | ||
/// of the output dimensions is consistent with the shape of the packed | ||
/// tensor. | ||
ArrayRef<int64_t> getAllOuterDims(); | ||
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/// Similar to `getAllOuterDims`, but only retrieve the outer dims that | ||
/// have been tiled. Also, the order of the output dimensions is consistent | ||
/// with `inner_dims_pos` rather than the packed tensor. | ||
SmallVector<int64_t> getTiledOuterDims(); | ||
}]; | ||
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let hasVerifier = 1; | ||
} | ||
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//===----------------------------------------------------------------------===// | ||
// PackOp | ||
//===----------------------------------------------------------------------===// | ||
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def Linalg_PackOp : Linalg_RelayoutOp<"pack", [ | ||
AttrSizedOperandSegments]> { | ||
let summary = "linalg.pack operation"; | ||
let description = [{ | ||
The "pack" operation converts a source tensor of rank `n` into a result | ||
tensor of rank `n + k` with a tiled and packed layout (maybe with padding) | ||
and optionally transposes the tiled source tensor dimensions. | ||
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`inner_dims_pos` (mandatory) specifies `k` source tensor dimensions that are | ||
being tiled, where `0 < k <= n`. The order of the dimensions matters: | ||
- The tiled dimensions (of size `inner_tiles`) are added to the end of the result | ||
tensor in the order in which they appear in `inner_dims_pos`. | ||
- `inner_dims_pos[i]` specifies the source tensor dimension tiled by | ||
`inner_tiles[i]`. | ||
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`inner_tiles` (mandatory) specifies `k` tile sizes. These tile sizes | ||
correspond to the least significant ("inner") result tensor dimension sizes, | ||
in the same order. Tile sizes can be static or dynamic. | ||
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Example: If `inner_tiles = [16, 32]`, the result tensor has a shape of | ||
`...x16x32`. If `inner_dims_pos = [0, 1]`, the 0th source dimension is tiled | ||
by 16 and the 1st source dimension is tiled by 32. Other source dimensions | ||
(if any) are not tiled. If `inner_dims_pos = [1, 0]`, the 1st dimension is | ||
tiled by 16 and the 0th dimension is tiled by 32. | ||
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Example: | ||
```mlir | ||
// NC to NCnc | ||
%0 = linalg.pack %source inner_dims_pos = [0, 1] inner_tiles = [8, 32] | ||
into %dest : tensor<128x256xf32> -> tensor<16x8 x 8x32 xf32> | ||
// \ / \ / | ||
// outer dims inner dims | ||
``` | ||
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`outer_dims_perm` (optional) specifies a permutation for the outer | ||
dimensions. If specified, it must have `n` elements. | ||
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Example: | ||
```mlir | ||
// CK to KCck | ||
%0 = linalg.pack %source outer_dims_perm = [1, 0] inner_dims_pos = [0, 1] | ||
inner_tiles = [8, 32] into %dest | ||
: tensor<128x256xf32> -> tensor<8x16 x 8x32 xf32> | ||
// \ / | ||
// compare with "NC to NCnc": outer dims are transposed | ||
``` | ||
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`padding_value` specifies a padding value at the boundary on non-perfectly | ||
divisible dimensions. Padding is optional: | ||
- If absent, it is UB if the tile does not perfectly divide the dimension. | ||
- If present, it will pad along high dimensions (high-padding) to make the | ||
tile complete. | ||
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Example: | ||
```mlir | ||
%0 = linalg.pack %arg0 padding_value(%pad : f32) outer_dims_perm = [2, 1, 0] | ||
inner_dims_pos = [1] inner_tiles = [2] into %arg1 | ||
: tensor<200x127x256xf32> -> tensor<256x64x200x2xf32> | ||
// \ | ||
// padded and tiled dim | ||
// | ||
// Source dimension 1 is tiled. 64 does not divide 127 evenly, so 1 padded | ||
// element is added at the end. | ||
// | ||
// Note: Only tiled dimensions can be padded. | ||
``` | ||
}]; | ||
let arguments = (ins AnyRankedTensor:$source, | ||
AnyRankedTensor:$dest, | ||
Optional<AnyType>:$padding_value, | ||
DefaultValuedOptionalAttr<DenseI64ArrayAttr, "{}">:$outer_dims_perm, | ||
DenseI64ArrayAttr:$inner_dims_pos, | ||
Variadic<Index>:$inner_tiles, | ||
DenseI64ArrayAttr:$static_inner_tiles); | ||
let results = (outs AnyRankedTensor:$result); | ||
let assemblyFormat = [{ | ||
$source | ||
(`padding_value` `(` $padding_value^ `:` type($padding_value) `)`)? | ||
(`outer_dims_perm` `=` $outer_dims_perm^)? | ||
`inner_dims_pos` `=` $inner_dims_pos | ||
`inner_tiles` `=` | ||
custom<DynamicIndexList>($inner_tiles, $static_inner_tiles) | ||
`into` $dest attr-dict `:` type($source) `->` type($dest) | ||
}]; | ||
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let builders = [ | ||
OpBuilder<(ins "Value":$source, "Value":$dest, | ||
"ArrayRef<int64_t>":$innerDimsPos, | ||
"ArrayRef<OpFoldResult>":$innerTiles, | ||
CArg<"std::optional<Value>", "std::nullopt">:$paddingValue, | ||
CArg<"ArrayRef<int64_t>", "{}">:$outerDimsPerm)> | ||
]; | ||
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let extraClassDeclaration = commonExtraClassDeclaration # [{ | ||
// Method to get the shape of the result as `SmallVector<OpFoldResult>`. | ||
// This is a static method to allow getting the shape of the destination | ||
// expected while creating a `pack` op. | ||
static SmallVector<OpFoldResult> getResultShape(OpBuilder &builder, | ||
Location loc, ArrayRef<OpFoldResult> sourceDims, | ||
ArrayRef<OpFoldResult> innerTileDims, ArrayRef<int64_t> innerDimsPos, | ||
ArrayRef<int64_t> outerDimsPerm = {}); | ||
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// Method to get the `RankedTensorType` of the result based on the inner | ||
// tiles, position of the inner tiles (innerDimsPos) and interchange vector | ||
// of outer loops (outerDimsPerm). | ||
static RankedTensorType inferPackedType(RankedTensorType sourceType, | ||
ArrayRef<int64_t> innerTileSizes, ArrayRef<int64_t> innerDimsPos, | ||
ArrayRef<int64_t> outerDimsPerm = {}); | ||
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// Returns true if we have enough static information to catch undefined | ||
// behavior when the tile size does not divide perfectly the dimension of | ||
// the input tensor. Detecting UB requires that the input size and either | ||
// corresponding tile or output size are static. | ||
static bool requirePaddingValue(ArrayRef<int64_t> inputShape, | ||
ArrayRef<int64_t> innerDimsPos, | ||
ArrayRef<int64_t> outputShape, | ||
ArrayRef<int64_t> outerDimsPerm, | ||
ArrayRef<OpFoldResult> innerTiles); | ||
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static Value createDestinationTensor(OpBuilder &b, Location loc, | ||
Value source, ArrayRef<OpFoldResult> innerTileSizes, | ||
ArrayRef<int64_t> innerDimsPos, ArrayRef<int64_t> outerDimsPerm); | ||
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/// Build and return a new PackOp that is a clone of the current PackOp with | ||
/// (innerDimsPos, innerTiles) (resp. outerDimsPerm) are permuted by | ||
/// innerPermutation (resp. outerPermutation). | ||
/// A new `tensor.empty` of the proper shape is built in the process. | ||
/// Asserts that: | ||
/// - At least one of innerPermutation or outerPermutation is non-empty. | ||
/// - If not empty, innerPermutation is a valid permutation of size | ||
/// matching innerDimPos. | ||
/// - If not empty, outerPermutation is a valid permutation of size | ||
/// matching outerDimsPerm. | ||
PackOp createTransposedClone(OpBuilder &b, | ||
Location loc, | ||
ArrayRef<int64_t> innerPermutation, | ||
ArrayRef<int64_t> outerPermutation); | ||
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/// Check if this PackOp is like a simple pad operation. | ||
/// In other words, this operation: | ||
/// 1. adds useless dimensions (dimension of size 1), | ||
/// 2. pads the other ones, and | ||
/// 3. doesn't shuffle the dimensions | ||
bool isLikePad(); | ||
}]; | ||
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let hasCanonicalizeMethod = 1; | ||
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let hasFolder = 1; | ||
} | ||
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//===----------------------------------------------------------------------===// | ||
// UnPackOp | ||
//===----------------------------------------------------------------------===// | ||
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def Linalg_UnPackOp : Linalg_RelayoutOp<"unpack"> { | ||
let summary = "linalg.unpack operation"; | ||
let description = [{ | ||
The "unpack" operation converts a source tensor of rank `n` with a tiled and | ||
packed layout to a result tensor of rank `n - k`. | ||
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`inner_dims_pos` (mandatory) specifies `k` source tensor dimensions with | ||
which the last `k` source tensor dimensions are combined, where | ||
`0 < k <= n/2`. Each `inner_dims_pos` element must be `>= 0` and `< n - k`. | ||
The order of the dimensions in `inner_dims_pos` matters: dimension | ||
`inner_dims_pos[i]` is combined with dimension `n - k + i` (assuming that | ||
`outer_dims_perm` is not specified). | ||
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`inner_tiles` (mandatory) specifies `k` tile sizes. These tile sizes | ||
correspond to the least significant ("inner") source tensor dimension sizes. | ||
The behavior of this op is undefined if: | ||
- `inner_tiles` do not exactly match with the corresponding source tensor | ||
dimension sizes. | ||
- Or, `inner_tiles[i]` does not divide the size of dimension | ||
`inner_dims_pos[i]` (assuming that `outer_dims_perm` is not specified) | ||
evenly. | ||
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`outer_dims_perm` (optional) specifies a permutation for the outer | ||
dimensions. If specified, it must have `n - k` elements. If specified, this | ||
permutation is applied before combining any dimensions. | ||
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Example: | ||
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```mlir | ||
// NCnc to NC: | ||
%0 = linalg.unpack %source inner_dims_pos = [0, 1] inner_tiles = [8, 32] | ||
into %dest : tensor<16x8x8x32xf32> -> tensor<128x256xf32> | ||
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// CK to KCck: | ||
%0 = linalg.unpack %source outer_dims_perm = [1, 0] inner_dims_pos = [0, 1] | ||
inner_tiles = [8, 32] into %dest | ||
: tensor<8x16x8x32xf32> -> tensor<128x256xf32> | ||
``` | ||
}]; | ||
let arguments = (ins AnyRankedTensor:$source, | ||
AnyRankedTensor:$dest, | ||
DefaultValuedOptionalAttr<DenseI64ArrayAttr, "{}">:$outer_dims_perm, | ||
DenseI64ArrayAttr:$inner_dims_pos, | ||
Variadic<Index>:$inner_tiles, | ||
DenseI64ArrayAttr:$static_inner_tiles); | ||
let results = (outs AnyRankedTensor:$result); | ||
let assemblyFormat = [{ | ||
$source | ||
(`outer_dims_perm` `=` $outer_dims_perm^)? | ||
`inner_dims_pos` `=` $inner_dims_pos | ||
`inner_tiles` `=` | ||
custom<DynamicIndexList>($inner_tiles, $static_inner_tiles) | ||
`into` $dest attr-dict `:` type($source) `->` type($dest) | ||
}]; | ||
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let builders = [ | ||
OpBuilder<(ins "Value":$source, "Value":$dest, | ||
"ArrayRef<int64_t>":$innerDimsPos, | ||
"ArrayRef<OpFoldResult>":$innerTiles, | ||
CArg<"ArrayRef<int64_t>", "{}">:$outerDimsPerm)> | ||
]; | ||
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let extraClassDeclaration = commonExtraClassDeclaration # [{ | ||
static Value createDestinationTensor(OpBuilder &b, Location loc, | ||
Value source, ArrayRef<OpFoldResult> innerTileSizes, | ||
ArrayRef<int64_t> innerDimsPos, ArrayRef<int64_t> outerDimsPerm); | ||
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/// Build and return a new UnPackOp that is a clone of the current UnPackOp | ||
/// with (innerDimsPos, innerTiles) (resp. outerDimsPerm) are permuted by | ||
/// innerPermutation (resp. outerPermutation). | ||
/// Asserts that: | ||
/// - At least one of innerPermutation or outerPermutation is non-empty. | ||
/// - If not empty, innerPermutation is a valid permutation of size | ||
/// matching innerDimPos. | ||
/// - If not empty, outerPermutation is a valid permutation of size | ||
/// matching outerDimsPerm. | ||
UnPackOp createTransposedClone(OpBuilder &b, | ||
Location loc, | ||
Value transposedSource, | ||
ArrayRef<int64_t> innerPermutation, | ||
ArrayRef<int64_t> outerPermutation); | ||
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/// Check if this UnPackOp is like a simple unpad operation. | ||
/// In other words, this operation: | ||
/// 1. drops useless dimensions (dimension of size 1), and | ||
/// 2. reduces dimensions in place (i.e., no transpose.) | ||
bool isLikeUnPad(); | ||
}]; | ||
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let hasCanonicalizeMethod = 1; | ||
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let hasFolder = 1; | ||
} | ||
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#endif // LINALG_RELEAYOUT_OPS |
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