bolt/deps/llvm-18.1.8/mlir/lib/Dialect/Mesh/Transforms/Spmdization.cpp
2025-02-14 19:21:04 +01:00

637 lines
27 KiB
C++

//===- Spmdization.cpp --------------------------------------------- C++ --===//
//
// 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
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Mesh/Transforms/Spmdization.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/ControlFlow/IR/ControlFlow.h"
#include "mlir/Dialect/ControlFlow/IR/ControlFlowOps.h"
#include "mlir/Dialect/Mesh/IR/MeshOps.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Utils/StaticValueUtils.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/BuiltinAttributes.h"
#include "mlir/IR/BuiltinTypeInterfaces.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/ImplicitLocOpBuilder.h"
#include "mlir/IR/Location.h"
#include "mlir/IR/MLIRContext.h"
#include "mlir/IR/Value.h"
#include "mlir/Support/LLVM.h"
#include "mlir/Support/LogicalResult.h"
#include "mlir/Support/MathExtras.h"
#include "llvm/ADT/ADL.h"
#include "llvm/ADT/APInt.h"
#include "llvm/ADT/DenseSet.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/SmallVector.h"
#include <algorithm>
#include <iterator>
#include <numeric>
#include <optional>
#include <tuple>
#include <type_traits>
namespace mlir {
namespace mesh {
int64_t shardDimension(int64_t dim, int64_t shardCount) {
if (ShapedType::isDynamic(dim) || ShapedType::isDynamic(shardCount))
return ShapedType::kDynamic;
assert(dim % shardCount == 0);
return ceilDiv(dim, shardCount);
}
int64_t unshardDimension(int64_t dim, int64_t shardCount) {
if (ShapedType::isDynamic(dim) || ShapedType::isDynamic(shardCount))
return ShapedType::kDynamic;
return dim * shardCount;
}
template <typename MeshShape, typename SplitAxes>
int64_t shardCount(const MeshShape &meshShape, const SplitAxes &splitAxes) {
int64_t res = 1;
for (auto splitAxis : splitAxes) {
int64_t meshDimSize = meshShape[splitAxis];
if (ShapedType::isDynamic(meshDimSize)) {
return ShapedType::kDynamic;
}
res *= meshDimSize;
}
return res;
}
// Compute the shape for the tensor on each device in the mesh.
// Example:
// On a 2x4x? mesh with split axes = [[0], [1], [2]] the shape ?x5x1
// would result in a shape for each shard of ?x2x?.
template <typename InShape, typename MeshShape, typename SplitAxes,
typename OutShape>
static void shardShape(const InShape &inShape, const MeshShape &meshShape,
const SplitAxes &splitAxes, OutShape &outShape) {
std::copy(llvm::adl_begin(inShape), llvm::adl_end(inShape),
llvm::adl_begin(outShape));
for (auto [tensorAxis, innerSplitAxes] : llvm::enumerate(splitAxes)) {
outShape[tensorAxis] =
shardDimension(inShape[tensorAxis],
shardCount(meshShape, innerSplitAxes.asArrayRef()));
}
}
ShapedType shardShapedType(ShapedType shape, ClusterOp mesh,
MeshShardingAttr sharding) {
using Dim = std::decay_t<decltype(shape.getDimSize(0))>;
SmallVector<Dim> resShapeArr(shape.getShape().size());
shardShape(shape.getShape(), mesh.getShape(), sharding.getSplitAxes(),
resShapeArr);
return shape.clone(resShapeArr);
}
template <typename SourceAxes, typename TargetAxes>
static bool arePartialAxesCompatible(const SourceAxes &sourceAxes,
const TargetAxes &targetAxes) {
return llvm::all_of(targetAxes, [&sourceAxes](auto &targetAxis) {
return sourceAxes.contains(targetAxis);
});
}
// Return the reduced value and its corresponding sharding.
// Example:
// sourceSharding = <@mesh_1d, [[0]], partial = sum[0]>
// targetSharding = <@mesh_1d, [[]]>
// Then will apply all-reduce on the source value
// and return it with the sharding <@mesh_1d, [[0]]>.
static std::tuple<TypedValue<ShapedType>, MeshShardingAttr>
handlePartialAxesDuringResharding(OpBuilder &builder,
MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding,
TypedValue<ShapedType> sourceShard) {
if (sourceSharding.getPartialAxes().empty() &&
targetSharding.getPartialAxes().empty()) {
return {sourceShard, sourceSharding};
}
assert(targetSharding.getPartialAxes().empty() ||
(!sourceSharding.getPartialAxes().empty() &&
sourceSharding.getPartialType() == targetSharding.getPartialType()));
using Axis = std::decay_t<decltype(sourceSharding.getPartialAxes().front())>;
using AxisSet = llvm::SmallDenseSet<Axis>;
AxisSet sourceShardingPartialAxesSet(sourceSharding.getPartialAxes().begin(),
sourceSharding.getPartialAxes().end());
AxisSet targetShardingPartialAxesSet(targetSharding.getPartialAxes().begin(),
targetSharding.getPartialAxes().end());
assert(arePartialAxesCompatible(sourceShardingPartialAxesSet,
targetShardingPartialAxesSet));
llvm::SmallVector<MeshAxis> allReduceMeshAxes;
llvm::copy_if(sourceShardingPartialAxesSet,
std::back_inserter(allReduceMeshAxes),
[&targetShardingPartialAxesSet](Axis a) {
return !targetShardingPartialAxesSet.contains(a);
});
if (allReduceMeshAxes.empty()) {
return {sourceShard, sourceSharding};
}
builder.setInsertionPointAfterValue(sourceShard);
TypedValue<ShapedType> resultValue =
builder
.create<AllReduceOp>(sourceShard.getLoc(), sourceShard.getType(),
sourceSharding.getCluster().getLeafReference(),
allReduceMeshAxes, sourceShard,
sourceSharding.getPartialType())
.getResult()
.cast<TypedValue<ShapedType>>();
llvm::SmallVector<MeshAxis> remainingPartialAxes;
llvm::copy_if(sourceShardingPartialAxesSet,
std::back_inserter(allReduceMeshAxes),
[&targetShardingPartialAxesSet](Axis a) {
return targetShardingPartialAxesSet.contains(a);
});
MeshShardingAttr resultSharding =
MeshShardingAttr::get(builder.getContext(), sourceSharding.getCluster(),
sourceSharding.getSplitAxes(), remainingPartialAxes,
sourceSharding.getPartialType());
return {resultValue, resultSharding};
}
static MeshShardingAttr
targetShardingInSplitLastAxis(MLIRContext *ctx, MeshShardingAttr sourceSharding,
int64_t splitTensorAxis, MeshAxis splitMeshAxis) {
SmallVector<MeshAxesAttr> targetShardingSplitAxes =
llvm::to_vector(sourceSharding.getSplitAxes());
while (static_cast<int64_t>(targetShardingSplitAxes.size()) <=
splitTensorAxis) {
targetShardingSplitAxes.push_back(MeshAxesAttr::get(ctx, {}));
}
auto targetSplitAxes =
llvm::to_vector(targetShardingSplitAxes[splitTensorAxis].asArrayRef());
targetSplitAxes.push_back(splitMeshAxis);
targetShardingSplitAxes[splitTensorAxis] =
MeshAxesAttr::get(ctx, targetSplitAxes);
return MeshShardingAttr::get(
ctx, sourceSharding.getCluster(), targetShardingSplitAxes,
sourceSharding.getPartialAxes(), sourceSharding.getPartialType());
}
static ShapedType targetShapeInSplitLastAxis(ShapedType sourceShape,
int64_t splitTensorAxis,
int64_t splitCount) {
SmallVector<int64_t> targetShape = llvm::to_vector(sourceShape.getShape());
targetShape[splitTensorAxis] =
shardDimension(targetShape[splitTensorAxis], splitCount);
return sourceShape.cloneWith(targetShape, sourceShape.getElementType());
}
// Split a replicated tensor along a mesh axis.
// e.g. [[0, 1]] -> [[0, 1, 2]].
// Returns the spmdized target value with its sharding.
//
// The implementation is the extract the tensor slice corresponding
// to the current device.
static std::tuple<TypedValue<ShapedType>, MeshShardingAttr>
splitLastAxisInResharding(ImplicitLocOpBuilder &builder,
MeshShardingAttr sourceSharding,
TypedValue<ShapedType> sourceShard, ClusterOp mesh,
int64_t splitTensorAxis, MeshAxis splitMeshAxis) {
MLIRContext *ctx = builder.getContext();
builder.setInsertionPointAfterValue(sourceShard);
Value zero = builder.create<arith::ConstantOp>(builder.getIndexAttr(0));
Value processIndexAlongAxis =
builder
.create<ProcessMultiIndexOp>(mesh.getSymName(),
SmallVector<MeshAxis>({splitMeshAxis}))
.getResult()[0];
MeshShardingAttr targetSharding = targetShardingInSplitLastAxis(
ctx, sourceSharding, splitTensorAxis, splitMeshAxis);
ShapedType targetShape = targetShapeInSplitLastAxis(
sourceShard.getType(), splitTensorAxis, mesh.getShape()[splitMeshAxis]);
Value meshAxisSize =
builder
.create<ClusterShapeOp>(mesh.getSymName(),
SmallVector<MeshAxis>({splitMeshAxis}))
.getResult()[0];
Value sourceAxisSize =
builder.create<tensor::DimOp>(sourceShard, splitTensorAxis);
Value sourceAxisSizeModMeshAxisSize =
builder.create<arith::RemUIOp>(sourceAxisSize, meshAxisSize);
Value isTargetShapeExactlyDivisible = builder.create<arith::CmpIOp>(
arith::CmpIPredicate::eq, sourceAxisSizeModMeshAxisSize, zero);
builder.create<cf::AssertOp>(
isTargetShapeExactlyDivisible,
"Sharding a tensor with axis size that is not exactly divisible by the "
"mesh axis size is not supported.");
Value targetAxisSize =
builder.create<arith::DivUIOp>(sourceAxisSize, meshAxisSize);
Value axisOffset =
builder.create<arith::MulIOp>(targetAxisSize, processIndexAlongAxis);
SmallVector<int64_t> staticOffsets(targetShape.getRank(), 0);
staticOffsets[splitTensorAxis] = ShapedType::kDynamic;
DenseI64ArrayAttr staticOffsetsAttr =
DenseI64ArrayAttr::get(ctx, staticOffsets);
SmallVector<Value> dynamicOffsets(1, axisOffset);
DenseI64ArrayAttr staticSizesAttr =
DenseI64ArrayAttr::get(ctx, targetShape.getShape());
SmallVector<Value> dynamicSizes;
for (int64_t i = 0; i < targetShape.getRank(); ++i) {
if (ShapedType::isDynamic(staticSizesAttr.asArrayRef()[i])) {
if (i == splitTensorAxis) {
dynamicSizes.push_back(targetAxisSize);
} else {
Value dimSize = builder.create<tensor::DimOp>(sourceShard, i);
dynamicSizes.push_back(dimSize);
}
}
}
DenseI64ArrayAttr staticStridesAttr = DenseI64ArrayAttr::get(
ctx, SmallVector<int64_t>(targetShape.getRank(), 1));
TypedValue<RankedTensorType> targetShard =
builder
.create<tensor::ExtractSliceOp>(
targetShape, sourceShard, dynamicOffsets, dynamicSizes,
SmallVector<Value>({}), staticOffsetsAttr, staticSizesAttr,
staticStridesAttr)
.getResult();
return {targetShard.cast<TypedValue<ShapedType>>(), targetSharding};
}
// Detect if the resharding is of type e.g.
// [[0, 1]] -> [[0, 1, 2]].
// If detected, returns the corresponding tensor axis mesh axis pair.
// Does not detect insertions like
// [[0, 1]] -> [[0, 2, 1]].
static std::optional<std::tuple<int64_t, MeshAxis>>
detectSplitLastAxisInResharding(MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding) {
for (size_t tensorAxis = 0; tensorAxis < targetSharding.getSplitAxes().size();
++tensorAxis) {
if (sourceSharding.getSplitAxes().size() > tensorAxis) {
if (sourceSharding.getSplitAxes()[tensorAxis].size() + 1 !=
targetSharding.getSplitAxes()[tensorAxis].size()) {
continue;
}
if (!llvm::equal(
sourceSharding.getSplitAxes()[tensorAxis].asArrayRef(),
llvm::make_range(
targetSharding.getSplitAxes()[tensorAxis]
.asArrayRef()
.begin(),
targetSharding.getSplitAxes()[tensorAxis].asArrayRef().end() -
1))) {
continue;
}
} else {
if (targetSharding.getSplitAxes()[tensorAxis].size() != 1) {
continue;
}
}
return std::make_tuple(
tensorAxis,
targetSharding.getSplitAxes()[tensorAxis].asArrayRef().back());
}
return std::nullopt;
}
static std::optional<std::tuple<TypedValue<ShapedType>, MeshShardingAttr>>
trySplitLastAxisInResharding(ImplicitLocOpBuilder &builder, ClusterOp mesh,
MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding,
TypedValue<ShapedType> sourceShard) {
if (auto detectRes =
detectSplitLastAxisInResharding(sourceSharding, targetSharding)) {
auto [tensorAxis, meshAxis] = detectRes.value();
return splitLastAxisInResharding(builder, sourceSharding, sourceShard, mesh,
tensorAxis, meshAxis);
}
return std::nullopt;
}
// Detect if the resharding is of type e.g.
// [[0, 1, 2]] -> [[0, 1]].
// If detected, returns the corresponding tensor axis mesh axis pair.
static std::optional<std::tuple<int64_t, MeshAxis>>
detectUnsplitLastAxisInResharding(MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding) {
for (size_t tensorAxis = 0; tensorAxis < sourceSharding.getSplitAxes().size();
++tensorAxis) {
if (targetSharding.getSplitAxes().size() > tensorAxis) {
if (sourceSharding.getSplitAxes()[tensorAxis].size() !=
targetSharding.getSplitAxes()[tensorAxis].size() + 1)
continue;
if (!llvm::equal(
llvm::make_range(
sourceSharding.getSplitAxes()[tensorAxis]
.asArrayRef()
.begin(),
sourceSharding.getSplitAxes()[tensorAxis].asArrayRef().end() -
1),
targetSharding.getSplitAxes()[tensorAxis].asArrayRef()))
continue;
} else {
if (sourceSharding.getSplitAxes()[tensorAxis].size() != 1)
continue;
}
return std::make_tuple(
tensorAxis,
sourceSharding.getSplitAxes()[tensorAxis].asArrayRef().back());
}
return std::nullopt;
}
static MeshShardingAttr
targetShardingInUnsplitLastAxis(MLIRContext *ctx,
MeshShardingAttr sourceSharding,
int64_t splitTensorAxis) {
SmallVector<MeshAxesAttr> targetShardingSplitAxes =
llvm::to_vector(sourceSharding.getSplitAxes());
assert(static_cast<int64_t>(targetShardingSplitAxes.size()) >
splitTensorAxis);
auto targetSplitAxes =
llvm::to_vector(targetShardingSplitAxes[splitTensorAxis].asArrayRef());
targetSplitAxes.pop_back();
targetShardingSplitAxes[splitTensorAxis] =
MeshAxesAttr::get(ctx, targetSplitAxes);
return MeshShardingAttr::get(
ctx, sourceSharding.getCluster(), targetShardingSplitAxes,
sourceSharding.getPartialAxes(), sourceSharding.getPartialType());
}
static ShapedType allGatherResultShapeInUnsplitLastAxis(
ShapedType sourceShape, int64_t splitCount, int64_t splitTensorAxis) {
SmallVector<int64_t> targetShape = llvm::to_vector(sourceShape.getShape());
targetShape[splitTensorAxis] =
unshardDimension(targetShape[splitTensorAxis], splitCount);
return sourceShape.cloneWith(targetShape, sourceShape.getElementType());
}
static std::tuple<TypedValue<ShapedType>, MeshShardingAttr>
unsplitLastAxisInResharding(ImplicitLocOpBuilder &builder,
MeshShardingAttr sourceSharding,
ShapedType sourceUnshardedShape,
TypedValue<ShapedType> sourceShard, ClusterOp mesh,
int64_t splitTensorAxis, MeshAxis splitMeshAxis) {
MLIRContext *ctx = builder.getContext();
builder.setInsertionPointAfterValue(sourceShard);
MeshShardingAttr targetSharding =
targetShardingInUnsplitLastAxis(ctx, sourceSharding, splitMeshAxis);
ShapedType allGatherResultShape = allGatherResultShapeInUnsplitLastAxis(
sourceShard.getType(), mesh.getShape()[splitMeshAxis], splitTensorAxis);
Value allGatherResult = builder.create<AllGatherOp>(
RankedTensorType::get(allGatherResultShape.getShape(),
allGatherResultShape.getElementType()),
mesh.getSymName(), SmallVector<MeshAxis>({splitMeshAxis}), sourceShard,
APInt(64, splitTensorAxis));
ShapedType targetShape =
shardShapedType(sourceUnshardedShape, mesh, targetSharding);
TypedValue<ShapedType> targetShard =
builder.create<tensor::CastOp>(targetShape, allGatherResult)
.getResult()
.cast<TypedValue<ShapedType>>();
return {targetShard, targetSharding};
}
static std::optional<std::tuple<TypedValue<ShapedType>, MeshShardingAttr>>
tryUnsplitLastAxisInResharding(ImplicitLocOpBuilder &builder, ClusterOp mesh,
MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding,
ShapedType sourceUnshardedShape,
TypedValue<ShapedType> sourceShard) {
if (auto detectRes =
detectUnsplitLastAxisInResharding(sourceSharding, targetSharding)) {
auto [tensorAxis, meshAxis] = detectRes.value();
return unsplitLastAxisInResharding(builder, sourceSharding,
sourceUnshardedShape, sourceShard, mesh,
tensorAxis, meshAxis);
}
return std::nullopt;
}
// Detect if the resharding is of type e.g.
// [[0, 1], [2]] -> [[0], [1, 2]].
// Only moving the last axis counts.
// If detected, returns the corresponding (source_tensor_axis,
// target_tensor_axis, mesh_axis) tuple.
static std::optional<std::tuple<int64_t, int64_t, MeshAxis>>
detectMoveLastSplitAxisInResharding(MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding) {
for (size_t sourceTensorAxis = 0;
sourceTensorAxis < sourceSharding.getSplitAxes().size();
++sourceTensorAxis) {
for (size_t targetTensorAxis = 0;
targetTensorAxis < targetSharding.getSplitAxes().size();
++targetTensorAxis) {
if (sourceTensorAxis == targetTensorAxis)
continue;
if (sourceSharding.getSplitAxes()[sourceTensorAxis].empty() ||
targetSharding.getSplitAxes()[targetTensorAxis].empty() ||
sourceSharding.getSplitAxes()[sourceTensorAxis].asArrayRef().back() !=
targetSharding.getSplitAxes()[targetTensorAxis]
.asArrayRef()
.back())
continue;
if (!llvm::equal(
llvm::make_range(sourceSharding.getSplitAxes()[sourceTensorAxis]
.asArrayRef()
.begin(),
sourceSharding.getSplitAxes()[sourceTensorAxis]
.asArrayRef()
.end() -
1),
llvm::make_range(targetSharding.getSplitAxes()[targetTensorAxis]
.asArrayRef()
.begin(),
targetSharding.getSplitAxes()[targetTensorAxis]
.asArrayRef()
.end() -
1)))
continue;
return std::make_tuple(
sourceTensorAxis, targetTensorAxis,
sourceSharding.getSplitAxes()[sourceTensorAxis].asArrayRef().back());
}
}
return std::nullopt;
}
static MeshShardingAttr
targetShardingInMoveLastAxis(MLIRContext *ctx, MeshShardingAttr sourceSharding,
int64_t sourceTensorAxis,
int64_t targetTensorAxis) {
SmallVector<MeshAxesAttr> targetShardingSplitAxes =
llvm::to_vector(sourceSharding.getSplitAxes());
while (static_cast<int64_t>(targetShardingSplitAxes.size()) <=
targetTensorAxis) {
targetShardingSplitAxes.push_back(MeshAxesAttr::get(ctx, {}));
}
auto sourceSplitAxes =
llvm::to_vector(targetShardingSplitAxes[sourceTensorAxis].asArrayRef());
assert(!sourceSplitAxes.empty());
auto meshAxis = sourceSplitAxes.back();
sourceSplitAxes.pop_back();
targetShardingSplitAxes[sourceTensorAxis] =
MeshAxesAttr::get(ctx, sourceSplitAxes);
auto targetSplitAxes =
llvm::to_vector(targetShardingSplitAxes[targetTensorAxis].asArrayRef());
targetSplitAxes.push_back(meshAxis);
targetShardingSplitAxes[targetTensorAxis] =
MeshAxesAttr::get(ctx, targetSplitAxes);
return MeshShardingAttr::get(
ctx, sourceSharding.getCluster(), targetShardingSplitAxes,
sourceSharding.getPartialAxes(), sourceSharding.getPartialType());
}
static ShapedType allToAllResultShapeInMoveLastAxis(ShapedType sourceShape,
int64_t splitCount,
int64_t sourceTensorAxis,
int64_t targetTensorAxis) {
SmallVector<int64_t> targetShape = llvm::to_vector(sourceShape.getShape());
targetShape[sourceTensorAxis] =
unshardDimension(targetShape[sourceTensorAxis], splitCount);
targetShape[targetTensorAxis] =
shardDimension(targetShape[targetTensorAxis], splitCount);
return sourceShape.cloneWith(targetShape, sourceShape.getElementType());
}
static std::tuple<TypedValue<ShapedType>, MeshShardingAttr>
moveLastSplitAxisInResharding(ImplicitLocOpBuilder &builder, ClusterOp mesh,
MeshShardingAttr sourceSharding,
ShapedType sourceUnshardedShape,
TypedValue<ShapedType> sourceShard,
int64_t sourceTensorAxis,
int64_t targetTensorAxis, MeshAxis meshAxis) {
MLIRContext *ctx = builder.getContext();
builder.setInsertionPointAfterValue(sourceShard);
MeshShardingAttr targetSharding = targetShardingInMoveLastAxis(
ctx, sourceSharding, sourceTensorAxis, targetTensorAxis);
ShapedType allToAllResultShape = allToAllResultShapeInMoveLastAxis(
sourceShard.getType(), mesh.getShape()[meshAxis], sourceTensorAxis,
targetTensorAxis);
Value allToAllResult = builder.create<AllToAllOp>(
RankedTensorType::get(allToAllResultShape.getShape(),
allToAllResultShape.getElementType()),
mesh.getSymName(), SmallVector<MeshAxis>({meshAxis}), sourceShard,
APInt(64, targetTensorAxis), APInt(64, sourceTensorAxis));
ShapedType targetShape =
shardShapedType(sourceUnshardedShape, mesh, targetSharding);
TypedValue<ShapedType> targetShard =
builder.create<tensor::CastOp>(targetShape, allToAllResult)
.getResult()
.cast<TypedValue<ShapedType>>();
return {targetShard, targetSharding};
}
static std::optional<std::tuple<TypedValue<ShapedType>, MeshShardingAttr>>
tryMoveLastSplitAxisInResharding(ImplicitLocOpBuilder &builder, ClusterOp mesh,
MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding,
ShapedType sourceUnshardedShape,
TypedValue<ShapedType> sourceShard) {
if (auto detectRes =
detectMoveLastSplitAxisInResharding(sourceSharding, targetSharding)) {
auto [sourceTensorAxis, targetTensorAxis, meshAxis] = detectRes.value();
return moveLastSplitAxisInResharding(
builder, mesh, sourceSharding, sourceUnshardedShape, sourceShard,
sourceTensorAxis, targetTensorAxis, meshAxis);
}
return std::nullopt;
}
// Handles only resharding on a 1D mesh.
// Currently the sharded tensor axes must be exactly divisible by the single
// mesh axis size.
static TypedValue<ShapedType>
reshardOn1DMesh(ImplicitLocOpBuilder &builder, ClusterOp mesh,
MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding,
TypedValue<ShapedType> sourceUnshardedValue,
TypedValue<ShapedType> sourceShard) {
assert(sourceShard.getType() ==
shardShapedType(sourceUnshardedValue.getType(), mesh, sourceSharding));
[[maybe_unused]] ShapedType targetShardType =
shardShapedType(sourceUnshardedValue.getType(), mesh, targetSharding);
assert(sourceShard.getType().getRank() == targetShardType.getRank());
assert(mesh.getRank() == 1 && "Only 1D meshes are currently supported.");
auto [reducedSourceShard, reducedSourceSharding] =
handlePartialAxesDuringResharding(builder, sourceSharding, targetSharding,
sourceShard);
if (reducedSourceSharding == targetSharding) {
return reducedSourceShard;
}
TypedValue<ShapedType> targetShard;
MeshShardingAttr actualTargetSharding;
if (auto tryRes = tryMoveLastSplitAxisInResharding(
builder, mesh, reducedSourceSharding, targetSharding,
sourceUnshardedValue.getType(), reducedSourceShard)) {
std::tie(targetShard, actualTargetSharding) = tryRes.value();
} else if (auto tryRes = trySplitLastAxisInResharding(
builder, mesh, reducedSourceSharding, targetSharding,
reducedSourceShard)) {
std::tie(targetShard, actualTargetSharding) = tryRes.value();
} else if (auto tryRes = tryUnsplitLastAxisInResharding(
builder, mesh, reducedSourceSharding, targetSharding,
sourceUnshardedValue.getType(), reducedSourceShard)) {
std::tie(targetShard, actualTargetSharding) = tryRes.value();
} else {
assert(false && "Did not find any pattern to apply.");
}
assert(actualTargetSharding == targetSharding);
assert(targetShard.getType() == targetShardType);
return targetShard;
}
TypedValue<ShapedType> reshard(ImplicitLocOpBuilder &builder, ClusterOp mesh,
MeshShardingAttr sourceSharding,
MeshShardingAttr targetSharding,
TypedValue<ShapedType> sourceUnshardedValue,
TypedValue<ShapedType> sourceShard) {
// Resort to handling only 1D meshes since the general case is complicated if
// it needs to be communication efficient in terms of minimizing the data
// transfered between devices.
return reshardOn1DMesh(builder, mesh, sourceSharding, targetSharding,
sourceUnshardedValue, sourceShard);
}
TypedValue<ShapedType> reshard(OpBuilder &builder, ClusterOp mesh,
ShardOp source, ShardOp target,
TypedValue<ShapedType> sourceShardValue) {
assert(!source.getAnnotateForUsers());
assert(target.getAnnotateForUsers());
assert(source.getResult() == target.getOperand());
ImplicitLocOpBuilder implicitLocOpBuilder(target->getLoc(), builder);
return reshard(
implicitLocOpBuilder, mesh, source.getShard(), target.getShard(),
source.getSrc().cast<TypedValue<ShapedType>>(), sourceShardValue);
}
void reshardingRegisterDependentDialects(DialectRegistry &registry) {
registry.insert<arith::ArithDialect, mesh::MeshDialect, tensor::TensorDialect,
cf::ControlFlowDialect>();
}
} // namespace mesh
} // namespace mlir