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[Meta Schedule][M3c] Schedule Rules, Mutator & Postprocs (apache#485)

[Meta Schedule][M3c] PostOrderApply (apache#486)

Fix Post Order Apply (apache#490)

[MetaSchedule] Relay Integration (apache#489)

[M3c][Meta Schedule] Add Trace Correctness Test for PostOrderApply (apache#492)

Fix replay trace. (apache#493)

[M3c][Meta Schedule] Implement the Replay Func class. (apache#495)

[PR] Test script for meta-schedule task extraction. Interface to load… (apache#494)

[Meta Schedule Refactor] Get child blocks (apache#500)

Read-at && Write-at (apache#497)

[M3c][Meta Schedule] Measure Callbacks (apache#498)

[Bug] Fix Infinite Loop Caused When Calling Methods Not Overrided In PyClass (apache#496)

[MetaSchedule] Sample-Perfect-Tile (apache#501)

[MetaSchedule] TE Workloads (apache#502)

[TensorIR] GetProducer, GetConsumer (apache#506)

[MetaScheduleRefactor] Annotate&Unannotate (apache#505)

[MetaSchedule] Multi-Level-Tiling & Auto-Inline (apache#503)

[Tests] Add unittests for auto-inline and multi-level-tiling (apache#508)

[Meta Schedule] Minor Fixes (apache#507)

[MetaSchedule] Rewrite Cooperative-Fetching / Unbound-Block / Reduction-Block (apache#509)

[MetaSchedule] Rewrite Parallel-Vectorize-Unroll / Verify-GPU / Disallow-Dynamic-Loops (apache#499)

[Meta Schedule] Add Helper Function & Minor Modification (apache#512)

[MetaSchedule] Test for Rewrite Parallel-Vectorize-Unroll  (apache#513)

[Meta Schedule] Feature Extractor & Cost Model (apache#510)

Blockize & Tensorize (apache#514)

Layout Rewriting: Suggest-Index-Map (apache#520)

[MetaSchedule] Parallel-Vectorize-Unroll & Random-Compute-Location (apache#516)

[Meta Schedule] Per-Store-Feature (apache#521)

Add traced schedule for blockize & tensorize (apache#526)

[Meta Schedule] Add XGBoost Model & Random Model (apache#519)

User-Interface: Tune-TIR (apache#525)

User-Interface: Tune-TE (apache#527)

[Minor] More logging on python (apache#528)

Get CUDA tuning working (apache#529)

[MetaSchedule] TensorRT BYOC (apache#518)

[BugFix] LocalBuilder API (apache#531)

[Meta Schedule] Add Cost Model Update Measure Callback (apache#530)

[Bugfix] BuilderInput with default params (apache#532)

[MetaSchedule] Mutator-Tile-Size, Mutate-Parallel, Mutate-Unroll (apache#534)

[Meta Schedule] Evolutionary Search (apache#522)

[BugFix] Remove duplicated definition of MakeMultinomialSampler (apache#535)

[Meta Schedule] Fix some bugs (apache#537)

Initiate Experiments for CPU Performance Alignment with Ansor (apache#538)

[Meta Schedule] Tweak experiment scripts (apache#539)

[Meta Schedule] Initiate experiments on CUDA (apache#540)

[TIR][Schedule] Buffer transform (apache#523)

Auto Tensor Core (apache#524)

Working on Evo Search (apache#542)

[Meta Schedule] Add Replay Tuning Interface (apache#543)

Evolutionary Search on CPU (apache#544)

Misc improvement over the error message (apache#545)

[TIR][Schedule] Software pipelining (apache#533)

[Meta Schedule Refactor] fixing unit tests (apache#547)

[MetaSchedule] Mutator-Compute-Location (apache#548)

Misc Improvement of Evolutionary Search (apache#549)

Hotfix for software pipeline (apache#552)

Misc Improvement (apache#550)

[Cherry-Pick][TensorIR] Primitive "SetScope" (apache#9738) (apache#555)

Rule RFactor (apache#551)

[MemHammer] Rewrite Rules (apache#554)

[MetaSchedule] Schedule Rule: Cross-Thread Reduction (apache#556)

[MetaSchedule] Performance Alignment - NRM and SFM (CUDA) (apache#559)

[MetaSchedule] Perf Alignment - NRM on CUDA (apache#560)

[TIR] Reorder the block iters of the blocks generated by RFactor (apache#561)

Removing 2 unit tests for software pipelining (apache#562)

[MemHammer] Lower Pass + Unittests (apache#557)

Perf Align: Remove Auto-inline before Multi-level-tiling (apache#564)

Fix Sketch Generation Unittests (apache#565)

speed up VerifyGpuCode (apache#568)

[Performance Align] fixing codegen problems (apache#569)

[Meta schedule] improve search space (apache#1)

Hot fix for bound predicate (apache#3)

[Meta Schedule] Update Tune Relay (apache#4)

[Performance Align] fixing codegen problems (apache#5)

[PerfAlign] NRM & SFM on Raspi Aligned (apache#6)

[BugFix] Apply bound predicate directly to loops when possible (apache#12)

[BugFix] Fix CrossThreadReduction on CUDA (apache#13)

[MetaSchedule] Enable BertTuning with MetaScheduler (apache#11)

[Minor][MemHammer] Minor tweaks in code review (apache#14)

[Meta Schedule] Add customizable search space to PostOrderApply. (apache#16)

Fix cooperative fetching (apache#17)

Fixes for codegen (apache#18)

[Hotfix] A unittest (apache#19)

Fix for GRP sketch gen (apache#21)

Add threadIdx filtering in Multi-Level-Tiling and Verify-GPU-Code (apache#20)

[BugFix][TIR] Fix cross-thread reduction when single reduction loop with predicate (apache#10016) (apache#22)

[MemHammer][Refactor] Code Review (apache#15)

[Meta Schedule] Add Winograd Test for Customizable Search Space (apache#24)

Co-authored-by: Siyuan Feng <Hzfengsy@sjtu.edu.cn>
Co-authored-by: Bohan Hou <32121147+spectrometerHBH@users.noreply.github.com>
Co-authored-by: Hongyi Jin <3231950289@qq.com>
Co-authored-by: Ruihang Lai <lairuihangdongdong@qq.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Wuwei Lin <wuwei@apache.org>
Co-authored-by: Sunghyun Park <49998730+sunggg@users.noreply.github.com>
Co-authored-by: Xiyou Zhou <xiyou@octoml.ai>
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.

# Github code owners file
# This file is used as a convenient tool to map
# committers' areas of expertise and faciliate the review process.
#
# This may not be the non-comprehensive list and is meant to be
# updated over time.

# Per ASF policy, committer have global write permission.
# We normally recommend committers to shepherd code in their area of expertise.
* @apache/tvm-committers

# Order is important; the last matching pattern takes the most precedence.
# The sub modules should be ordered first by depth.
# Making sure we append new sub-module rules after exisiting modules rules.

##############################
# Top-level Fallbacks
##############################
include/** @tqchen @jroesch @yzhliu @icemelon @junrushao1994 @comaniac @zhiics
src/** @tqchen @jroesch @yzhliu @icemelon @junrushao1994 @comaniac @zhiics
apps/** @tqchen @jroesch @yzhliu @icemelon @junrushao1994 @comaniac @zhiics
python/** @tqchen @jroesch @yzhliu @icemelon @junrushao1994 @comaniac @zhiics

# Thirdparty license audit
3rdparty/** @tqchen @jroesch
licenses/** @tqchen @jroesch

# JVM language
jvm/** @yzhliu

# Golang
golang/** @srkreddy1238

# WASM
web/** @tqchen @jroesch

# Docker
docker/** @areusch @leandron @jroesch

# Conda
conda/** @tqchen @junrushao1994 @comaniac

# CMake
cmake/** @jroesch @tqchen @areusch @junrushao1994 @comaniac

# rust bindings
rust/** @jroesch @nhynes @nhynes

# vta
vta/** @tmoreau89 @vegaluisjose

# docs
docs/** @comaniac @junrushao1994 @tqchen @jroesch @areusch @yzhliu @merrymercy @icemelon
tutorials/** @comaniac @junrushao1994 @tqchen @jroesch @areusch @yzhliu @merrymercy @icemelon

# tests
tests/** @comaniac @junrushao1994 @tqchen @jroesch @areusch @yzhliu @merrymercy @icemelon

##############################
# Specific modules
##############################

# automation related
src/auto_scheduler/** @merrymercy @jcf94 @comaniac @junrushao1994 @vinx13 @Hzfengsy
include/tvm/auto_scheduler/** @merrymercy @jcf94 @comaniac @junrushao1994 @vinx13 @Hzfengsy
python/tvm/auto_scheduler/** @merrymercy @jcf94 @comaniac @junrushao1994 @vinx13 @Hzfengsy

python/tvm/autotvm/** @merrymercy @jcf94 @comaniac @junrushao1994 @vinx13

# node system and reflection
src/node/** @junrushao1994 @vinx13 @tqchen @jroesch @comaniac
include/tvm/node/** @junrushao1994 @vinx13 @tqchen @jroesch @comaniac

# ir: Common IR
src/ir/** @junrushao1994 @vinx13 @tqchen @jroesch @comaniac
include/tvm/ir/** @junrushao1994 @vinx13 @tqchen @jroesch @comaniac
python/tvm/ir/** @junrushao1994 @vinx13 @tqchen @jroesch @comaniac

# tir
src/tir/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi @were @Hzfengsy
include/tvm/tir/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi @were @Hzfengsy
python/tvm/tir/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi @were @Hzfengsy

# te
src/te/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi @were
include/tvm/te/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi @were
python/tvm/te/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi @were

# target
src/target/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi
include/tvm/target/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi
python/tvm/target/** @junrushao1994 @vinx13 @tqchen @kparzysz-quic @ZihengJiang @masahi

# arith: Arithmetic module and simplifiers
src/arith/** @tqchen @junrushao1994 @vinx13
include/tvm/arith/** @tqchen @junrushao1994 @vinx13
python/tvm/arith/** @tqchen @junrushao1994 @vinx13

# parser
src/parser/** @jroesch @slyubomirsky

# runtime
src/runtime/** @vinx13 @tqchen @FronzenGene @liangfu @areusch @tmoreau89 @ajtulloch @masahi @kazum @ZihengJiang @junrushao1994
include/tvm/runtime/** @vinx13 @tqchen @FronzenGene @liangfu @areusch @tmoreau89 @ajtulloch @masahi @kazum @ZihengJiang @junrushao1994
python/tvm/runtime/** @vinx13 @tqchen @FronzenGene @liangfu @areusch @tmoreau89 @ajtulloch @masahi @kazum @ZihengJiang @junrushao1994

# runtime/micro
src/runtime/micro/** @areusch @liangfu @tmoreau89 @manupa-arm
src/runtime/crt/** @areusch @liangfu @tmoreau89 @manupa-arm
include/tvm/runtime/crt/** @areusch @liangfu @tmoreau89 @manupa-arm
include/tvm/runtime/micro/** @areusch @liangfu @tmoreau89 @manupa-arm
python/tvm/micro/** @areusch @liangfu @tmoreau89 @manupa-arm

# relay
src/relay/** @jroesch @slyubomirsky @icemelon @MarisaKirisame @ZihengJiang @yzhliu @vinx13 @mbrookhart @jwfromm @zhiics @anijain2305 @wweic @eqy @junrushao1994
include/tvm/relay/** @jroesch @slyubomirsky @icemelon @MarisaKirisame @ZihengJiang @yzhliu @vinx13 @mbrookhart @jwfromm @zhiics @anijain2305 @wweic @eqy @junrushao1994
python/tvm/relay/** @jroesch @slyubomirsky @icemelon @MarisaKirisame @ZihengJiang @yzhliu @vinx13 @mbrookhart @jwfromm @zhiics @anijain2305 @wweic @eqy @junrushao1994


# relay/qnn
src/relay/qnn/** @jwfromm @anijain2305 @ZihengJiang
inlcude/tvm/relay/qnn/** @jwfromm @anijain2305 @ZihengJiang
python/tvm/relay/qnn/** @jwfromm @anijain2305 @ZihengJiang

# relay/backend/contrib: BYOC
src/relay/backend/contrib/** @zhiics @trevor-m @comaniac @mbaret @manupa-arm

# relay/frontends
python/tvm/relay/frontend/** @jwfromm @mbrookhart @srkreddy1238 @siju-samuel @Huyuwei @hlu1 @kazum @PariksheetPinjari909

# topi: Operator definitions
src/topi/** @Laurawly @Huyuwei @kevinthesun @jwfromm @vinx13 @masahi @FronzenGene @yzhliu @mbrookhart @ZihengJiang @jcf94
include/tvm/topi/** @Laurawly @Huyuwei @kevinthesun @jwfromm @vinx13 @masahi @FronzenGene @yzhliu @mbrookhart @ZihengJiang @jcf94
python/tvm/topi/** @Laurawly @Huyuwei @kevinthesun @jwfromm @vinx13 @masahi @FronzenGene @yzhliu @mbrookhart @ZihengJiang @jcf94


# tvm/driver/
python/tvm/driver/** @leandron @jwfromm @tqchen @jroesch

# tvm/driver/tvmc
python/tvm/driver/tvmc/** @leandron @jwfromm
21 changes: 21 additions & 0 deletions include/tvm/arith/int_set.h
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Original file line number Diff line number Diff line change
Expand Up @@ -93,6 +93,10 @@ class IntSet : public ObjectRef {
bool CanProveNonPositive() const;
/*! \return Whether the set is proved to be larger than or equal to 0 */
bool CanProveNonNegative() const;
/*! \return Whether the set has upper bound. */
bool HasUpperBound() const;
/*! \return Whether the set has lower bound. */
bool HasLowerBound() const;
/*!
* \brief The single point value, call only if IsSinglePoint is true
* \return The point value.
Expand Down Expand Up @@ -164,6 +168,14 @@ Map<Var, IntSet> ConvertDomMap(const std::unordered_map<const VarNode*, IntSet>&
* \return An integer set that can cover all the possible values of e.
*/
IntSet EvalSet(PrimExpr e, const Map<IterVar, IntSet>& dom_map);
/*!
* \brief Same as EvalSet, but takes Map<Var, IntSet>
*
* \param e The expression to be evaluated.
* \param dom_map The domain of each variable.
* \return An integer set that can cover all the possible values of e.
*/
IntSet EvalSet(PrimExpr e, const Map<Var, IntSet>& dom_map);
/*!
* \brief Same as EvalSet, but takes unordered_map
*
Expand All @@ -172,6 +184,15 @@ IntSet EvalSet(PrimExpr e, const Map<IterVar, IntSet>& dom_map);
* \return An integer set that can cover all the possible values of e.
*/
IntSet EvalSet(PrimExpr e, const std::unordered_map<const tir::VarNode*, IntSet>& dom_map);
/*!
* \brief Same as EvalSet, but takes Array<PrimExpr>
*
* \param exprs The expressions to be evaluated.
* \param dom_map The domain of each variable.
* \return An array of integer sets that can cover all the possible values.
*/
Array<IntSet> EvalSet(const Array<PrimExpr>& exprs, const Map<Var, IntSet>& dom_map);

/*!
* \brief Find an symbolic integer set that contains is union over
* all the possible conditional values in dom_map.
Expand Down
2 changes: 2 additions & 0 deletions include/tvm/arith/iter_affine_map.h
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Original file line number Diff line number Diff line change
Expand Up @@ -350,6 +350,8 @@ Array<Array<IterMark>> SubspaceDivide(const Array<PrimExpr>& bindings,
bool require_bijective, arith::Analyzer* analyzer,
DiagnosticContext diag_ctx);

PrimExpr NormalizeIterMapToExpr(const IterMapExpr& expr);

} // namespace arith
} // namespace tvm
#endif // TVM_ARITH_ITER_AFFINE_MAP_H_
4 changes: 2 additions & 2 deletions include/tvm/meta_schedule/builder.h
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Expand Up @@ -32,7 +32,7 @@ class BuilderInputNode : public runtime::Object {
IRModule mod;
/*! \brief The target to be built for. */
Target target;
/*! \brief The optional parameters used for build */
/*! \brief Parameters for Relay build module. */
Optional<Map<String, runtime::NDArray>> params;

void VisitAttrs(tvm::AttrVisitor* v) {
Expand All @@ -55,7 +55,7 @@ class BuilderInput : public runtime::ObjectRef {
* \brief Constructor of BuilderInput.
* \param mod The IRModule to be built.
* \param target The target to be built for.
* \param params The optional parameters used for build
* \param params Parameters for Relay build module.
*/
TVM_DLL explicit BuilderInput(IRModule mod, Target target,
Optional<Map<String, runtime::NDArray>> params = NullOpt);
Expand Down
1 change: 1 addition & 0 deletions include/tvm/meta_schedule/database.h
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Original file line number Diff line number Diff line change
Expand Up @@ -237,6 +237,7 @@ class PyDatabaseNode : public DatabaseNode {
// PackedFuncs are all not visited, because the reflection system doesn't take care of them,
// so it cannot be accessible on the python side. If there is such need from the future,
// we can then add corresponding accessor methods to help access on python.
//
// `f_has_workload` is not visited
// `f_commit_workload` is not visited
// `f_commit_tuning_record` is not visited
Expand Down
146 changes: 146 additions & 0 deletions include/tvm/meta_schedule/mutator.h
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@@ -0,0 +1,146 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/

#ifndef TVM_META_SCHEDULE_MUTATOR_H_
#define TVM_META_SCHEDULE_MUTATOR_H_

#include <tvm/tir/schedule/schedule.h>

namespace tvm {
namespace meta_schedule {

class TuneContext;

/*! \brief Mutator is designed to mutate the trace to explore the design space. */
class MutatorNode : public runtime::Object {
public:
/*! \brief Virtual destructor. */
virtual ~MutatorNode() = default;

void VisitAttrs(tvm::AttrVisitor* v) {}

/*!
* \brief Initialize the design space generator with tuning context.
* \param tune_context The tuning context for initialization.
* \note This method is supposed to be called only once before every other method.
*/
virtual void InitializeWithTuneContext(const TuneContext& context) = 0;

/*!
* \brief Apply the mutator function to the given trace.
* \param trace The given trace for mutation.
* \param rand_state The random state for mutation.
* \return None if mutator failed, otherwise return the mutated trace.
*/
virtual Optional<tir::Trace> Apply(const tir::Trace& trace,
support::LinearCongruentialEngine::TRandState* rand_state) = 0;

static constexpr const char* _type_key = "meta_schedule.Mutator";
TVM_DECLARE_BASE_OBJECT_INFO(MutatorNode, Object);
};

/*! \brief The mutator with customized methods on the python-side. */
class PyMutatorNode : public MutatorNode {
public:
/*!
* \brief The function type of `InitializeWithTuneContext` method.
* \param tune_context The tuning context for initialization.
*/
using FInitializeWithTuneContext = runtime::TypedPackedFunc<void(const TuneContext&)>;
/*!
* \brief Apply the mutator function to the given trace.
* \param trace The given trace for mutation.
* \return None if mutator failed, otherwise return the mutated trace.
*/
using FApply = runtime::TypedPackedFunc<Optional<tir::Trace>(
const tir::Trace&, support::LinearCongruentialEngine::TRandState rand_state)>;
/*!
* \brief Get the mutator as string with name.
* \return The string of the mutator.
*/
using FAsString = runtime::TypedPackedFunc<String()>;

/*! \brief The packed function to the `InitializeWithTuneContext` function. */
FInitializeWithTuneContext f_initialize_with_tune_context;
/*! \brief The packed function to the `Apply` function. */
FApply f_apply;
/*! \brief The packed function to the `AsString` function. */
FAsString f_as_string;

void VisitAttrs(tvm::AttrVisitor* v) {
// `f_initialize_with_tune_context` is not visited
// `f_apply` is not visited
// `f_as_string` is not visited
}

void InitializeWithTuneContext(const TuneContext& context) final {
ICHECK(f_initialize_with_tune_context != nullptr)
<< "PyMutator's InitializeWithTuneContext method not implemented!";
this->f_initialize_with_tune_context(context);
}

Optional<tir::Trace> Apply(const tir::Trace& trace,
support::LinearCongruentialEngine::TRandState* rand_state) final {
ICHECK(f_apply != nullptr) << "PyMutator's Apply method not implemented!";
return this->f_apply(trace, *rand_state);
}

static constexpr const char* _type_key = "meta_schedule.PyMutator";
TVM_DECLARE_FINAL_OBJECT_INFO(PyMutatorNode, MutatorNode);
};

/*!
* \brief Managed reference to MutatorNode
* \sa MutatorNode
*/
class Mutator : public runtime::ObjectRef {
public:
/*! \brief Create a Mutator that mutates the tile size. */
TVM_DLL static Mutator MutateTileSize();
/*!
* \brief Create a Mutator that mutates the parallel extent
* \param max_jobs_per_core The maximum number of parallel jobs per core.
* \return The created mutator.
*/
TVM_DLL static Mutator MutateParallel(int64_t max_jobs_per_core);
/*! \brief Create a Mutator that mutates auto unroll step */
TVM_DLL static Mutator MutateUnroll();
/*!
* \brief Create a Mutator that mutates the outcome of SampleComputeLocation
* \return The mutator created
*/
TVM_DLL static Mutator MutateComputeLocation();
/*!
* \brief Create a mutator with customized methods on the python-side.
* \param f_initialize_with_tune_context The packed function of `InitializeWithTuneContext`.
* \param f_apply The packed function of `Apply`.
* \param f_as_string The packed function of `AsString`.
* \return The mutator created.
*/
TVM_DLL static Mutator PyMutator(
PyMutatorNode::FInitializeWithTuneContext f_initialize_with_tune_context, //
PyMutatorNode::FApply f_apply, //
PyMutatorNode::FAsString f_as_string);
TVM_DEFINE_MUTABLE_OBJECT_REF_METHODS(Mutator, ObjectRef, MutatorNode);
};

} // namespace meta_schedule
} // namespace tvm

#endif // TVM_META_SCHEDULE_MUTATOR_H_
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