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[NNVM] Error handling message #14

Merged
merged 7 commits into from
Mar 12, 2019
Merged

[NNVM] Error handling message #14

merged 7 commits into from
Mar 12, 2019

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wweic
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@wweic wweic commented Mar 12, 2019

porting @yongwww 's code.

@wweic wweic requested a review from yongwww March 12, 2019 17:24
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LGTM

@wweic wweic merged commit cdbabd6 into neo-ai:unstable Mar 12, 2019
@wweic wweic deleted the wweic-fix-tf branch March 12, 2019 20:00
wweic pushed a commit that referenced this pull request Aug 16, 2019
* uTVM interfaces (#14)

* some minor interface changes

* implemented HostLowLevelDevice

* added MicroDeviceAPI

* implemented micro_common and added Python interfaces

* current status, semi implemented micro session

* added micro_common implementation and python interfaces (#18)

* added micro_common implementation and python interfaces (#18)

* current status, semi implemented

* host test working

* updated interfaces for MicroSession arguments allocation

* make somewhat lint compatible

* fix based on comments

* added rounding macro

* fix minor bug

* improvements based on comments

* Clean up `binutil.py` and make Python-3-compatible

* Change argument allocation design

* Address feedback and lint errors

* Improve binutil tests

* Simplify allocator (per @tqchen's suggestions)

* Doc/style fixes

* farts

* mcgee

* rodata section werks

(and so does `test_runtime_micro_workspace.py`)

* simple graph runtime werk

* TEMP

* ResNet works, yo

* First round of cleanup

* More cleanup

* runs a dyson over the code

* Another pass

* Fix `make lint` issues

* ready to pr... probably

* final

* Undo change

* Fix rebase resolution

* Minor fixes

* Undo changes to C codegen tests

* Add `obj_path` in `create_micro_lib`

* TEMP

* Address feedback

* Add missing TODO

* Partially address feedback

* Fix headers

* Switch to enum class for `SectionKind`

* Add missing ASF header

* Fix lint

* Fix lint again

* Fix lint

* Kill lint warnings

* Address feedback

* Change Python interface to MicroTVM

All interaction with the device is now through `Session` objects, which
are used through Python's `with` blocks.

* Reorder LowLevelDevice interface

* Store shared ptr to session in all alloced objects

* Move helper functions out of `tvm.micro`

* Switch static char arr to vector

* Improve general infra and code quality

Does not yet address all of tqchen's feedback

* Forgot a rename

* Fix lint

* Add ASF header

* Fix lint

* Partially address MarisaKirisame's feedback

* Lint

* Expose `MicroSession` as a node to Python

* Revert to using `Session` constructor

* Fix compiler error

* (Maybe) fix CI error

* Debugging

* Remove

* Quell lint

* Switch to stack-based session contexts

* Make uTVM less intrusive to host codegen

And use SSA for operands of generated ternary operators

* Inline UTVMArgs into UTVMTask struct

* Remove `HostLowLevelDevice` header

* Remove `BaseAddr` class

* Address feedback

* Add "utvm" prefix to global vars in runtime

* Fix lint

* Fix CI

* Fix `test_binutil.py`

* Fix submodules

* Remove ResNet tests

* Make `test_binutil.py` work with nose

* Fix CI

* I swear this actually fixes the binutil tests

* lint

* lint

* Add fcompile-compatible cross-compile func

* Add docs for uTVM runtime files

* Move pointer patching into `MicroSession`

* Fix lint

* First attempt at unifying cross-compile APIs

* Fix lint

* Rename `cross_compile` back to `cc`

* Address feedback

* Remove commented code

* Lint

* Figure out failing function

* Remove debugging code

* Change "micro_dev" target to "micro"

* Add checks in tests for whether uTVM is enabled

* Add TODO for 32-bit support

* Rename more "micro_dev" to "micro"

* Undo rename

We already have `tvm.micro` as a namespace.  Can't have it as a method
as well.

* Fix failing CI

Thanks to @tqchen for finding this bug.  Emitting ternary operators for
`min` and `max` causes concurrency bugs in CUDA, so we're moving the
ternary op emissions from `CodeGenC` to `CodeGenCHost`.

* Address feedback

* Fix lint
wweic pushed a commit that referenced this pull request Sep 6, 2019
* uTVM interfaces (#14)

* some minor interface changes

* implemented HostLowLevelDevice

* added MicroDeviceAPI

* implemented micro_common and added Python interfaces

* current status, semi implemented micro session

* added micro_common implementation and python interfaces (#18)

* added micro_common implementation and python interfaces (#18)

* current status, semi implemented

* host test working

* updated interfaces for MicroSession arguments allocation

* make somewhat lint compatible

* fix based on comments

* added rounding macro

* fix minor bug

* improvements based on comments

* Clean up `binutil.py` and make Python-3-compatible

* Change argument allocation design

* Address feedback and lint errors

* Improve binutil tests

* Simplify allocator (per @tqchen's suggestions)

* Doc/style fixes

* farts

* mcgee

* rodata section werks

(and so does `test_runtime_micro_workspace.py`)

* simple graph runtime werk

* TEMP

* ResNet works, yo

* First round of cleanup

* More cleanup

* runs a dyson over the code

* Another pass

* Fix `make lint` issues

* ready to pr... probably

* final

* Undo change

* Fix rebase resolution

* Minor fixes

* Undo changes to C codegen tests

* Add `obj_path` in `create_micro_lib`

* TEMP

* Address feedback

* Add missing TODO

* Partially address feedback

* Fix headers

* Switch to enum class for `SectionKind`

* Add missing ASF header

* Fix lint

* Fix lint again

* Fix lint

* Kill lint warnings

* Address feedback

* Change Python interface to MicroTVM

All interaction with the device is now through `Session` objects, which
are used through Python's `with` blocks.

* Reorder LowLevelDevice interface

* Store shared ptr to session in all alloced objects

* Move helper functions out of `tvm.micro`

* Switch static char arr to vector

* Improve general infra and code quality

Does not yet address all of tqchen's feedback

* Forgot a rename

* Fix lint

* Add ASF header

* Fix lint

* Partially address MarisaKirisame's feedback

* Lint

* Expose `MicroSession` as a node to Python

* Revert to using `Session` constructor

* Fix compiler error

* (Maybe) fix CI error

* Debugging

* Remove

* Quell lint

* Switch to stack-based session contexts

* Make uTVM less intrusive to host codegen

And use SSA for operands of generated ternary operators

* Inline UTVMArgs into UTVMTask struct

* Remove `HostLowLevelDevice` header

* Remove `BaseAddr` class

* Address feedback

* Add "utvm" prefix to global vars in runtime

* Fix lint

* Fix CI

* Fix `test_binutil.py`

* Fix submodules

* Remove ResNet tests

* Make `test_binutil.py` work with nose

* Fix CI

* I swear this actually fixes the binutil tests

* lint

* lint

* Add fcompile-compatible cross-compile func

* Add docs for uTVM runtime files

* Move pointer patching into `MicroSession`

* Fix lint

* First attempt at unifying cross-compile APIs

* Fix lint

* Rename `cross_compile` back to `cc`

* Address feedback

* Remove commented code

* Lint

* Figure out failing function

* Remove debugging code

* Change "micro_dev" target to "micro"

* Add checks in tests for whether uTVM is enabled

* Add TODO for 32-bit support

* Rename more "micro_dev" to "micro"

* Undo rename

We already have `tvm.micro` as a namespace.  Can't have it as a method
as well.

* Fix failing CI

Thanks to @tqchen for finding this bug.  Emitting ternary operators for
`min` and `max` causes concurrency bugs in CUDA, so we're moving the
ternary op emissions from `CodeGenC` to `CodeGenCHost`.

* Address feedback

* Fix lint
zhiics pushed a commit that referenced this pull request Oct 11, 2019
* uTVM interfaces (#14)

* some minor interface changes

* implemented HostLowLevelDevice

* added MicroDeviceAPI

* implemented micro_common and added Python interfaces

* current status, semi implemented micro session

* added micro_common implementation and python interfaces (#18)

* added micro_common implementation and python interfaces (#18)

* current status, semi implemented

* host test working

* updated interfaces for MicroSession arguments allocation

* make somewhat lint compatible

* fix based on comments

* added rounding macro

* fix minor bug

* improvements based on comments

* Clean up `binutil.py` and make Python-3-compatible

* Change argument allocation design

* Address feedback and lint errors

* Improve binutil tests

* Simplify allocator (per @tqchen's suggestions)

* Doc/style fixes

* farts

* mcgee

* rodata section werks

(and so does `test_runtime_micro_workspace.py`)

* simple graph runtime werk

* TEMP

* ResNet works, yo

* First round of cleanup

* More cleanup

* runs a dyson over the code

* Another pass

* Fix `make lint` issues

* ready to pr... probably

* final

* Undo change

* Fix rebase resolution

* Minor fixes

* Undo changes to C codegen tests

* Add `obj_path` in `create_micro_lib`

* TEMP

* Address feedback

* Add missing TODO

* Partially address feedback

* Fix headers

* Switch to enum class for `SectionKind`

* Add missing ASF header

* Fix lint

* Fix lint again

* Fix lint

* Kill lint warnings

* Address feedback

* Change Python interface to MicroTVM

All interaction with the device is now through `Session` objects, which
are used through Python's `with` blocks.

* Reorder LowLevelDevice interface

* Store shared ptr to session in all alloced objects

* Move helper functions out of `tvm.micro`

* Switch static char arr to vector

* Improve general infra and code quality

Does not yet address all of tqchen's feedback

* Forgot a rename

* Fix lint

* Add ASF header

* Fix lint

* Partially address MarisaKirisame's feedback

* Lint

* Expose `MicroSession` as a node to Python

* Revert to using `Session` constructor

* Fix compiler error

* (Maybe) fix CI error

* Debugging

* Remove

* Quell lint

* Switch to stack-based session contexts

* Make uTVM less intrusive to host codegen

And use SSA for operands of generated ternary operators

* Inline UTVMArgs into UTVMTask struct

* Remove `HostLowLevelDevice` header

* Remove `BaseAddr` class

* Address feedback

* Add "utvm" prefix to global vars in runtime

* Fix lint

* Fix CI

* Fix `test_binutil.py`

* Fix submodules

* Remove ResNet tests

* Make `test_binutil.py` work with nose

* Fix CI

* I swear this actually fixes the binutil tests

* lint

* lint

* Add fcompile-compatible cross-compile func

* Add docs for uTVM runtime files

* Move pointer patching into `MicroSession`

* Fix lint

* First attempt at unifying cross-compile APIs

* Fix lint

* Rename `cross_compile` back to `cc`

* Address feedback

* Remove commented code

* Lint

* Figure out failing function

* Remove debugging code

* Change "micro_dev" target to "micro"

* Add checks in tests for whether uTVM is enabled

* Add TODO for 32-bit support

* Rename more "micro_dev" to "micro"

* Undo rename

We already have `tvm.micro` as a namespace.  Can't have it as a method
as well.

* Fix failing CI

Thanks to @tqchen for finding this bug.  Emitting ternary operators for
`min` and `max` causes concurrency bugs in CUDA, so we're moving the
ternary op emissions from `CodeGenC` to `CodeGenCHost`.

* Address feedback

* Fix lint
trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jul 27, 2020
…generating (apache#5962)

* Code migration Start (neo-ai#1)

* Init commit: Code migration Start

* Add loop_state.cc/h

* Add ComputeDAG basic test

* Split transform_step out & Update more UTs (neo-ai#3)

* Split transform_step out

* Update GetProducers & GetConsumers

* Update UTs

* Add UT for CacheReadWrite & Some bug fix

* Add search_task, measure and serialization (neo-ai#4)

* Add FollowSplit & FollowFusedSplit tests

* Update dag.InferBound & its UT

* Add search_task, measure and serialization

* Update Serialization UT

* Add MetaTileRewritePolicy (neo-ai#5)

* Add feature

* Add cost_model, meta_tile_rewrite_policy

* Add MetaTileRewritePolicy basic UT

* Basic Python API for State (neo-ai#6)

* Add Basic Python API for State

* Add UTs for State

* Add Python API: Measure & Task (neo-ai#7)

* Update the return value of state operation

* Add task

* Copy measure.py & utils.py

* Fix LocalBuilder

* Fix LocalRunner

* Add ansor.auto_schedule() API; First AutoSchedule working version(neo-ai#8)

* Add basic Python support for ansor.auto_schedule

* Update AutoSchedule API

* Bug fix for get the attach point of a fused iter

* Update UT after infer bug fix

* Bug fix & Add python serialization API (neo-ai#10)

* Delete C++ UT hack since Python is ready

* Add ndarray.non_empty

* Update Serialization python API

* Improve code style, python wrapper and test cases (neo-ai#11)

* Update c++ code style and unit test

* Update python State wrapper and test cases

* fix unit tests

* Add RPCRunner & OpenCL/CUDA test (neo-ai#12)

* Add RPCRunner & OpenCL search test

* Add CUDA search test

* Add RPCRunner test

* rebase to upstream/master

* Add Ansor basic tutorial (neo-ai#13)

* Add basic tutorial

* migrate feature extraction (neo-ai#14)

* Add XGBModel & RPCRunnerWarpper (neo-ai#15)

* Add XGBModel & RPCRunnerWarpper

* Revert "Add Parallel Granularity Mutation"

* Migrate workload_registry.py (neo-ai#16)

* add workload registry

* update

* update

* add task scheduler (neo-ai#17)

* Add conv2d cuda tutorial with workload registry (neo-ai#18)

* add tune_test.py (the old tune_wkl.py) (neo-ai#19)

* add tune_test.py (the old tune_wkl.py)

* update

* fix measure

* fix for gpu

* Code refine for tune_test.py & Add a pre load callback (neo-ai#20)

* Bug fix for tutorials

* Add PreLoadMeasuredStates

* Add search_callback support for task tuner

* Code refine for tune_test.py

* Update

* Update

* Update

* Update

* Bug fix

* Add python custom sketch rule (neo-ai#21)

* Add custom sketch rule

* Bug fix

* Ansor Relay Integration (without layout rewrite) (neo-ai#22)

* relay integration

* Add tune_op_subgraph.py & Some code clean for tune_network.py (neo-ai#23)

* Add single op tune scripts

* Add tune subgraph support

* Merge all op & all subgraph to one file

* Rename file

* add explicit_unroll_max_extent (neo-ai#25)

* Add Index simplification & API update (neo-ai#26)

* Add vectorized cooperative_fetching test

* Update math simplify for vectorized CF

* File rename

* Update tune_network

* API update

* Update PreLoadMeasuredStates & Some bug fix (neo-ai#27)

* Add a threading wrapper to fix the test bug

* Set default TVM_USE_AUTO_SCHEDULER to false

* Update PreLoadMeasuredStates callback

* Add tensorize step for loop_state (neo-ai#31)

* Add tensorize step

* State python api update (neo-ai#33)

* Start to update api

* Add compute_dag to state

* API update

* kernel layout rewrite (neo-ai#28)

* kernel layout rewrite

* remove some hacks

* add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass

* set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite

* [cache flush] port cache flush to ansor (neo-ai#32)

* Improve relay integration (neo-ai#34)

* tmp checkpoint

* Improve relay integration

* Improve relay integration

* Fix xgb error & Simplify dispatcher (neo-ai#35)

* Rename "MetaTileRewritePolicy" to "SketchPolicy". (neo-ai#36)

* Rename "MetaTileRewritePolicy" to "SketchPolicy".

* Add a new class for auto_unroll_max_step, storage_offset in StageNode

* fix tune_op_subgraph.py

* rebase

* Migrate all node::make to noderef's construct function (neo-ai#37)

* Start to move xxxnode::make to noderef()

* Update

* Update

* Finish transform_step

* Finish comute dag & auto schedule

* Update

* Update

* Update

* Update

* Update

* Code refine

* Code refine

* Code refine

* Update

* Update

* Some lint fix & Recover the double constructor of tvm::PrimExpr (neo-ai#39)

* lint fix

* clang-format-fix

* pylint fix

* Update

* Recover the double constructor of tvm::PrimExpr

* Fix pylint

* pylint fix

* pylint fix

* Add MutateComputeLocation and MutateParallel in evolutionary search (neo-ai#40)

* Add MutateComputeLocation and MutateParallel in evolutionary search

* fix lint

* Improve loop state python API (stage_tensors -> stage_ops) (neo-ai#41)

* improve loop state python API (stage_tensors -> stage_ops)

* fix

* ComputeDAG bug fix & Add Custom TensorCore Matmul Example (neo-ai#42)

* Bug Fix

* Sample example of Custom TensorCore Matmul

* Rever Commits, Start to build minimum Ansor system

* Code clean for minimum Ansor system

* Bug fix & Delete AccessAnalyzer

* Delete attachmap & Code clean

* Doc update

Update statenode::stages from vector to Array

* Headfile update & Python doc update

* clang-format fix

* pylint fix

* Update

* Doc update

* Update

* Bug fix after code merge to the new master

* clang-format fix

* Update

* Update

* Update std::vector to Array; Update verbosity setting; Some commemts
addressed

* std::vector->Array & std::string->String

* Add init_state to ComputeDAG

* Update

* Update some unordered_map to Map

* clang-format fix

* Comments addressed
Delete ReplayAndInferBound
Delete ReplaySteps & InferBoundCommon

* Lint fix

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Rename ansor namespace to auto_schedule

* Update

* Rename ThreadPool to ParallelFor

* Add parallel_for

* Remove ThreadPool

* Update python/tvm/auto_schedule/auto_schedule.py

* trigger CI

Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com>
Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com>
Co-authored-by: Zhao Wu <zhaowu@apache.org>
trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Aug 26, 2020
…generating (apache#5962)

* Code migration Start (neo-ai#1)

* Init commit: Code migration Start

* Add loop_state.cc/h

* Add ComputeDAG basic test

* Split transform_step out & Update more UTs (neo-ai#3)

* Split transform_step out

* Update GetProducers & GetConsumers

* Update UTs

* Add UT for CacheReadWrite & Some bug fix

* Add search_task, measure and serialization (neo-ai#4)

* Add FollowSplit & FollowFusedSplit tests

* Update dag.InferBound & its UT

* Add search_task, measure and serialization

* Update Serialization UT

* Add MetaTileRewritePolicy (neo-ai#5)

* Add feature

* Add cost_model, meta_tile_rewrite_policy

* Add MetaTileRewritePolicy basic UT

* Basic Python API for State (neo-ai#6)

* Add Basic Python API for State

* Add UTs for State

* Add Python API: Measure & Task (neo-ai#7)

* Update the return value of state operation

* Add task

* Copy measure.py & utils.py

* Fix LocalBuilder

* Fix LocalRunner

* Add ansor.auto_schedule() API; First AutoSchedule working version(neo-ai#8)

* Add basic Python support for ansor.auto_schedule

* Update AutoSchedule API

* Bug fix for get the attach point of a fused iter

* Update UT after infer bug fix

* Bug fix & Add python serialization API (neo-ai#10)

* Delete C++ UT hack since Python is ready

* Add ndarray.non_empty

* Update Serialization python API

* Improve code style, python wrapper and test cases (neo-ai#11)

* Update c++ code style and unit test

* Update python State wrapper and test cases

* fix unit tests

* Add RPCRunner & OpenCL/CUDA test (neo-ai#12)

* Add RPCRunner & OpenCL search test

* Add CUDA search test

* Add RPCRunner test

* rebase to upstream/master

* Add Ansor basic tutorial (neo-ai#13)

* Add basic tutorial

* migrate feature extraction (neo-ai#14)

* Add XGBModel & RPCRunnerWarpper (neo-ai#15)

* Add XGBModel & RPCRunnerWarpper

* Revert "Add Parallel Granularity Mutation"

* Migrate workload_registry.py (neo-ai#16)

* add workload registry

* update

* update

* add task scheduler (neo-ai#17)

* Add conv2d cuda tutorial with workload registry (neo-ai#18)

* add tune_test.py (the old tune_wkl.py) (neo-ai#19)

* add tune_test.py (the old tune_wkl.py)

* update

* fix measure

* fix for gpu

* Code refine for tune_test.py & Add a pre load callback (neo-ai#20)

* Bug fix for tutorials

* Add PreLoadMeasuredStates

* Add search_callback support for task tuner

* Code refine for tune_test.py

* Update

* Update

* Update

* Update

* Bug fix

* Add python custom sketch rule (neo-ai#21)

* Add custom sketch rule

* Bug fix

* Ansor Relay Integration (without layout rewrite) (neo-ai#22)

* relay integration

* Add tune_op_subgraph.py & Some code clean for tune_network.py (neo-ai#23)

* Add single op tune scripts

* Add tune subgraph support

* Merge all op & all subgraph to one file

* Rename file

* add explicit_unroll_max_extent (neo-ai#25)

* Add Index simplification & API update (neo-ai#26)

* Add vectorized cooperative_fetching test

* Update math simplify for vectorized CF

* File rename

* Update tune_network

* API update

* Update PreLoadMeasuredStates & Some bug fix (neo-ai#27)

* Add a threading wrapper to fix the test bug

* Set default TVM_USE_AUTO_SCHEDULER to false

* Update PreLoadMeasuredStates callback

* Add tensorize step for loop_state (neo-ai#31)

* Add tensorize step

* State python api update (neo-ai#33)

* Start to update api

* Add compute_dag to state

* API update

* kernel layout rewrite (neo-ai#28)

* kernel layout rewrite

* remove some hacks

* add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass

* set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite

* [cache flush] port cache flush to ansor (neo-ai#32)

* Improve relay integration (neo-ai#34)

* tmp checkpoint

* Improve relay integration

* Improve relay integration

* Fix xgb error & Simplify dispatcher (neo-ai#35)

* Rename "MetaTileRewritePolicy" to "SketchPolicy". (neo-ai#36)

* Rename "MetaTileRewritePolicy" to "SketchPolicy".

* Add a new class for auto_unroll_max_step, storage_offset in StageNode

* fix tune_op_subgraph.py

* rebase

* Migrate all node::make to noderef's construct function (neo-ai#37)

* Start to move xxxnode::make to noderef()

* Update

* Update

* Finish transform_step

* Finish comute dag & auto schedule

* Update

* Update

* Update

* Update

* Update

* Code refine

* Code refine

* Code refine

* Update

* Update

* Some lint fix & Recover the double constructor of tvm::PrimExpr (neo-ai#39)

* lint fix

* clang-format-fix

* pylint fix

* Update

* Recover the double constructor of tvm::PrimExpr

* Fix pylint

* pylint fix

* pylint fix

* Add MutateComputeLocation and MutateParallel in evolutionary search (neo-ai#40)

* Add MutateComputeLocation and MutateParallel in evolutionary search

* fix lint

* Improve loop state python API (stage_tensors -> stage_ops) (neo-ai#41)

* improve loop state python API (stage_tensors -> stage_ops)

* fix

* ComputeDAG bug fix & Add Custom TensorCore Matmul Example (neo-ai#42)

* Bug Fix

* Sample example of Custom TensorCore Matmul

* Rever Commits, Start to build minimum Ansor system

* Code clean for minimum Ansor system

* Bug fix & Delete AccessAnalyzer

* Delete attachmap & Code clean

* Doc update

Update statenode::stages from vector to Array

* Headfile update & Python doc update

* clang-format fix

* pylint fix

* Update

* Doc update

* Update

* Bug fix after code merge to the new master

* clang-format fix

* Update

* Update

* Update std::vector to Array; Update verbosity setting; Some commemts
addressed

* std::vector->Array & std::string->String

* Add init_state to ComputeDAG

* Update

* Update some unordered_map to Map

* clang-format fix

* Comments addressed
Delete ReplayAndInferBound
Delete ReplaySteps & InferBoundCommon

* Lint fix

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Rename ansor namespace to auto_schedule

* Update

* Rename ThreadPool to ParallelFor

* Add parallel_for

* Remove ThreadPool

* Update python/tvm/auto_schedule/auto_schedule.py

* trigger CI

Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com>
Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com>
Co-authored-by: Zhao Wu <zhaowu@apache.org>
trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Aug 26, 2020
…generating (apache#5962)

* Code migration Start (neo-ai#1)

* Init commit: Code migration Start

* Add loop_state.cc/h

* Add ComputeDAG basic test

* Split transform_step out & Update more UTs (neo-ai#3)

* Split transform_step out

* Update GetProducers & GetConsumers

* Update UTs

* Add UT for CacheReadWrite & Some bug fix

* Add search_task, measure and serialization (neo-ai#4)

* Add FollowSplit & FollowFusedSplit tests

* Update dag.InferBound & its UT

* Add search_task, measure and serialization

* Update Serialization UT

* Add MetaTileRewritePolicy (neo-ai#5)

* Add feature

* Add cost_model, meta_tile_rewrite_policy

* Add MetaTileRewritePolicy basic UT

* Basic Python API for State (neo-ai#6)

* Add Basic Python API for State

* Add UTs for State

* Add Python API: Measure & Task (neo-ai#7)

* Update the return value of state operation

* Add task

* Copy measure.py & utils.py

* Fix LocalBuilder

* Fix LocalRunner

* Add ansor.auto_schedule() API; First AutoSchedule working version(neo-ai#8)

* Add basic Python support for ansor.auto_schedule

* Update AutoSchedule API

* Bug fix for get the attach point of a fused iter

* Update UT after infer bug fix

* Bug fix & Add python serialization API (neo-ai#10)

* Delete C++ UT hack since Python is ready

* Add ndarray.non_empty

* Update Serialization python API

* Improve code style, python wrapper and test cases (neo-ai#11)

* Update c++ code style and unit test

* Update python State wrapper and test cases

* fix unit tests

* Add RPCRunner & OpenCL/CUDA test (neo-ai#12)

* Add RPCRunner & OpenCL search test

* Add CUDA search test

* Add RPCRunner test

* rebase to upstream/master

* Add Ansor basic tutorial (neo-ai#13)

* Add basic tutorial

* migrate feature extraction (neo-ai#14)

* Add XGBModel & RPCRunnerWarpper (neo-ai#15)

* Add XGBModel & RPCRunnerWarpper

* Revert "Add Parallel Granularity Mutation"

* Migrate workload_registry.py (neo-ai#16)

* add workload registry

* update

* update

* add task scheduler (neo-ai#17)

* Add conv2d cuda tutorial with workload registry (neo-ai#18)

* add tune_test.py (the old tune_wkl.py) (neo-ai#19)

* add tune_test.py (the old tune_wkl.py)

* update

* fix measure

* fix for gpu

* Code refine for tune_test.py & Add a pre load callback (neo-ai#20)

* Bug fix for tutorials

* Add PreLoadMeasuredStates

* Add search_callback support for task tuner

* Code refine for tune_test.py

* Update

* Update

* Update

* Update

* Bug fix

* Add python custom sketch rule (neo-ai#21)

* Add custom sketch rule

* Bug fix

* Ansor Relay Integration (without layout rewrite) (neo-ai#22)

* relay integration

* Add tune_op_subgraph.py & Some code clean for tune_network.py (neo-ai#23)

* Add single op tune scripts

* Add tune subgraph support

* Merge all op & all subgraph to one file

* Rename file

* add explicit_unroll_max_extent (neo-ai#25)

* Add Index simplification & API update (neo-ai#26)

* Add vectorized cooperative_fetching test

* Update math simplify for vectorized CF

* File rename

* Update tune_network

* API update

* Update PreLoadMeasuredStates & Some bug fix (neo-ai#27)

* Add a threading wrapper to fix the test bug

* Set default TVM_USE_AUTO_SCHEDULER to false

* Update PreLoadMeasuredStates callback

* Add tensorize step for loop_state (neo-ai#31)

* Add tensorize step

* State python api update (neo-ai#33)

* Start to update api

* Add compute_dag to state

* API update

* kernel layout rewrite (neo-ai#28)

* kernel layout rewrite

* remove some hacks

* add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass

* set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite

* [cache flush] port cache flush to ansor (neo-ai#32)

* Improve relay integration (neo-ai#34)

* tmp checkpoint

* Improve relay integration

* Improve relay integration

* Fix xgb error & Simplify dispatcher (neo-ai#35)

* Rename "MetaTileRewritePolicy" to "SketchPolicy". (neo-ai#36)

* Rename "MetaTileRewritePolicy" to "SketchPolicy".

* Add a new class for auto_unroll_max_step, storage_offset in StageNode

* fix tune_op_subgraph.py

* rebase

* Migrate all node::make to noderef's construct function (neo-ai#37)

* Start to move xxxnode::make to noderef()

* Update

* Update

* Finish transform_step

* Finish comute dag & auto schedule

* Update

* Update

* Update

* Update

* Update

* Code refine

* Code refine

* Code refine

* Update

* Update

* Some lint fix & Recover the double constructor of tvm::PrimExpr (neo-ai#39)

* lint fix

* clang-format-fix

* pylint fix

* Update

* Recover the double constructor of tvm::PrimExpr

* Fix pylint

* pylint fix

* pylint fix

* Add MutateComputeLocation and MutateParallel in evolutionary search (neo-ai#40)

* Add MutateComputeLocation and MutateParallel in evolutionary search

* fix lint

* Improve loop state python API (stage_tensors -> stage_ops) (neo-ai#41)

* improve loop state python API (stage_tensors -> stage_ops)

* fix

* ComputeDAG bug fix & Add Custom TensorCore Matmul Example (neo-ai#42)

* Bug Fix

* Sample example of Custom TensorCore Matmul

* Rever Commits, Start to build minimum Ansor system

* Code clean for minimum Ansor system

* Bug fix & Delete AccessAnalyzer

* Delete attachmap & Code clean

* Doc update

Update statenode::stages from vector to Array

* Headfile update & Python doc update

* clang-format fix

* pylint fix

* Update

* Doc update

* Update

* Bug fix after code merge to the new master

* clang-format fix

* Update

* Update

* Update std::vector to Array; Update verbosity setting; Some commemts
addressed

* std::vector->Array & std::string->String

* Add init_state to ComputeDAG

* Update

* Update some unordered_map to Map

* clang-format fix

* Comments addressed
Delete ReplayAndInferBound
Delete ReplaySteps & InferBoundCommon

* Lint fix

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Rename ansor namespace to auto_schedule

* Update

* Rename ThreadPool to ParallelFor

* Add parallel_for

* Remove ThreadPool

* Update python/tvm/auto_schedule/auto_schedule.py

* trigger CI

Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com>
Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com>
Co-authored-by: Zhao Wu <zhaowu@apache.org>
trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Sep 2, 2020
…generating (apache#5962)

* Code migration Start (neo-ai#1)

* Init commit: Code migration Start

* Add loop_state.cc/h

* Add ComputeDAG basic test

* Split transform_step out & Update more UTs (neo-ai#3)

* Split transform_step out

* Update GetProducers & GetConsumers

* Update UTs

* Add UT for CacheReadWrite & Some bug fix

* Add search_task, measure and serialization (neo-ai#4)

* Add FollowSplit & FollowFusedSplit tests

* Update dag.InferBound & its UT

* Add search_task, measure and serialization

* Update Serialization UT

* Add MetaTileRewritePolicy (neo-ai#5)

* Add feature

* Add cost_model, meta_tile_rewrite_policy

* Add MetaTileRewritePolicy basic UT

* Basic Python API for State (neo-ai#6)

* Add Basic Python API for State

* Add UTs for State

* Add Python API: Measure & Task (neo-ai#7)

* Update the return value of state operation

* Add task

* Copy measure.py & utils.py

* Fix LocalBuilder

* Fix LocalRunner

* Add ansor.auto_schedule() API; First AutoSchedule working version(neo-ai#8)

* Add basic Python support for ansor.auto_schedule

* Update AutoSchedule API

* Bug fix for get the attach point of a fused iter

* Update UT after infer bug fix

* Bug fix & Add python serialization API (neo-ai#10)

* Delete C++ UT hack since Python is ready

* Add ndarray.non_empty

* Update Serialization python API

* Improve code style, python wrapper and test cases (neo-ai#11)

* Update c++ code style and unit test

* Update python State wrapper and test cases

* fix unit tests

* Add RPCRunner & OpenCL/CUDA test (neo-ai#12)

* Add RPCRunner & OpenCL search test

* Add CUDA search test

* Add RPCRunner test

* rebase to upstream/master

* Add Ansor basic tutorial (neo-ai#13)

* Add basic tutorial

* migrate feature extraction (neo-ai#14)

* Add XGBModel & RPCRunnerWarpper (neo-ai#15)

* Add XGBModel & RPCRunnerWarpper

* Revert "Add Parallel Granularity Mutation"

* Migrate workload_registry.py (neo-ai#16)

* add workload registry

* update

* update

* add task scheduler (neo-ai#17)

* Add conv2d cuda tutorial with workload registry (neo-ai#18)

* add tune_test.py (the old tune_wkl.py) (neo-ai#19)

* add tune_test.py (the old tune_wkl.py)

* update

* fix measure

* fix for gpu

* Code refine for tune_test.py & Add a pre load callback (neo-ai#20)

* Bug fix for tutorials

* Add PreLoadMeasuredStates

* Add search_callback support for task tuner

* Code refine for tune_test.py

* Update

* Update

* Update

* Update

* Bug fix

* Add python custom sketch rule (neo-ai#21)

* Add custom sketch rule

* Bug fix

* Ansor Relay Integration (without layout rewrite) (neo-ai#22)

* relay integration

* Add tune_op_subgraph.py & Some code clean for tune_network.py (neo-ai#23)

* Add single op tune scripts

* Add tune subgraph support

* Merge all op & all subgraph to one file

* Rename file

* add explicit_unroll_max_extent (neo-ai#25)

* Add Index simplification & API update (neo-ai#26)

* Add vectorized cooperative_fetching test

* Update math simplify for vectorized CF

* File rename

* Update tune_network

* API update

* Update PreLoadMeasuredStates & Some bug fix (neo-ai#27)

* Add a threading wrapper to fix the test bug

* Set default TVM_USE_AUTO_SCHEDULER to false

* Update PreLoadMeasuredStates callback

* Add tensorize step for loop_state (neo-ai#31)

* Add tensorize step

* State python api update (neo-ai#33)

* Start to update api

* Add compute_dag to state

* API update

* kernel layout rewrite (neo-ai#28)

* kernel layout rewrite

* remove some hacks

* add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass

* set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite

* [cache flush] port cache flush to ansor (neo-ai#32)

* Improve relay integration (neo-ai#34)

* tmp checkpoint

* Improve relay integration

* Improve relay integration

* Fix xgb error & Simplify dispatcher (neo-ai#35)

* Rename "MetaTileRewritePolicy" to "SketchPolicy". (neo-ai#36)

* Rename "MetaTileRewritePolicy" to "SketchPolicy".

* Add a new class for auto_unroll_max_step, storage_offset in StageNode

* fix tune_op_subgraph.py

* rebase

* Migrate all node::make to noderef's construct function (neo-ai#37)

* Start to move xxxnode::make to noderef()

* Update

* Update

* Finish transform_step

* Finish comute dag & auto schedule

* Update

* Update

* Update

* Update

* Update

* Code refine

* Code refine

* Code refine

* Update

* Update

* Some lint fix & Recover the double constructor of tvm::PrimExpr (neo-ai#39)

* lint fix

* clang-format-fix

* pylint fix

* Update

* Recover the double constructor of tvm::PrimExpr

* Fix pylint

* pylint fix

* pylint fix

* Add MutateComputeLocation and MutateParallel in evolutionary search (neo-ai#40)

* Add MutateComputeLocation and MutateParallel in evolutionary search

* fix lint

* Improve loop state python API (stage_tensors -> stage_ops) (neo-ai#41)

* improve loop state python API (stage_tensors -> stage_ops)

* fix

* ComputeDAG bug fix & Add Custom TensorCore Matmul Example (neo-ai#42)

* Bug Fix

* Sample example of Custom TensorCore Matmul

* Rever Commits, Start to build minimum Ansor system

* Code clean for minimum Ansor system

* Bug fix & Delete AccessAnalyzer

* Delete attachmap & Code clean

* Doc update

Update statenode::stages from vector to Array

* Headfile update & Python doc update

* clang-format fix

* pylint fix

* Update

* Doc update

* Update

* Bug fix after code merge to the new master

* clang-format fix

* Update

* Update

* Update std::vector to Array; Update verbosity setting; Some commemts
addressed

* std::vector->Array & std::string->String

* Add init_state to ComputeDAG

* Update

* Update some unordered_map to Map

* clang-format fix

* Comments addressed
Delete ReplayAndInferBound
Delete ReplaySteps & InferBoundCommon

* Lint fix

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Rename ansor namespace to auto_schedule

* Update

* Rename ThreadPool to ParallelFor

* Add parallel_for

* Remove ThreadPool

* Update python/tvm/auto_schedule/auto_schedule.py

* trigger CI

Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com>
Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com>
Co-authored-by: Zhao Wu <zhaowu@apache.org>
trevor-m pushed a commit that referenced this pull request Sep 3, 2020
…generating (apache#5962)

* Code migration Start (#1)

* Init commit: Code migration Start

* Add loop_state.cc/h

* Add ComputeDAG basic test

* Split transform_step out & Update more UTs (#3)

* Split transform_step out

* Update GetProducers & GetConsumers

* Update UTs

* Add UT for CacheReadWrite & Some bug fix

* Add search_task, measure and serialization (#4)

* Add FollowSplit & FollowFusedSplit tests

* Update dag.InferBound & its UT

* Add search_task, measure and serialization

* Update Serialization UT

* Add MetaTileRewritePolicy (#5)

* Add feature

* Add cost_model, meta_tile_rewrite_policy

* Add MetaTileRewritePolicy basic UT

* Basic Python API for State (#6)

* Add Basic Python API for State

* Add UTs for State

* Add Python API: Measure & Task (#7)

* Update the return value of state operation

* Add task

* Copy measure.py & utils.py

* Fix LocalBuilder

* Fix LocalRunner

* Add ansor.auto_schedule() API; First AutoSchedule working version(#8)

* Add basic Python support for ansor.auto_schedule

* Update AutoSchedule API

* Bug fix for get the attach point of a fused iter

* Update UT after infer bug fix

* Bug fix & Add python serialization API (#10)

* Delete C++ UT hack since Python is ready

* Add ndarray.non_empty

* Update Serialization python API

* Improve code style, python wrapper and test cases (#11)

* Update c++ code style and unit test

* Update python State wrapper and test cases

* fix unit tests

* Add RPCRunner & OpenCL/CUDA test (#12)

* Add RPCRunner & OpenCL search test

* Add CUDA search test

* Add RPCRunner test

* rebase to upstream/master

* Add Ansor basic tutorial (#13)

* Add basic tutorial

* migrate feature extraction (#14)

* Add XGBModel & RPCRunnerWarpper (#15)

* Add XGBModel & RPCRunnerWarpper

* Revert "Add Parallel Granularity Mutation"

* Migrate workload_registry.py (#16)

* add workload registry

* update

* update

* add task scheduler (#17)

* Add conv2d cuda tutorial with workload registry (#18)

* add tune_test.py (the old tune_wkl.py) (#19)

* add tune_test.py (the old tune_wkl.py)

* update

* fix measure

* fix for gpu

* Code refine for tune_test.py & Add a pre load callback (#20)

* Bug fix for tutorials

* Add PreLoadMeasuredStates

* Add search_callback support for task tuner

* Code refine for tune_test.py

* Update

* Update

* Update

* Update

* Bug fix

* Add python custom sketch rule (#21)

* Add custom sketch rule

* Bug fix

* Ansor Relay Integration (without layout rewrite) (#22)

* relay integration

* Add tune_op_subgraph.py & Some code clean for tune_network.py (#23)

* Add single op tune scripts

* Add tune subgraph support

* Merge all op & all subgraph to one file

* Rename file

* add explicit_unroll_max_extent (#25)

* Add Index simplification & API update (#26)

* Add vectorized cooperative_fetching test

* Update math simplify for vectorized CF

* File rename

* Update tune_network

* API update

* Update PreLoadMeasuredStates & Some bug fix (#27)

* Add a threading wrapper to fix the test bug

* Set default TVM_USE_AUTO_SCHEDULER to false

* Update PreLoadMeasuredStates callback

* Add tensorize step for loop_state (#31)

* Add tensorize step

* State python api update (#33)

* Start to update api

* Add compute_dag to state

* API update

* kernel layout rewrite (#28)

* kernel layout rewrite

* remove some hacks

* add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass

* set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite

* [cache flush] port cache flush to ansor (#32)

* Improve relay integration (#34)

* tmp checkpoint

* Improve relay integration

* Improve relay integration

* Fix xgb error & Simplify dispatcher (#35)

* Rename "MetaTileRewritePolicy" to "SketchPolicy". (#36)

* Rename "MetaTileRewritePolicy" to "SketchPolicy".

* Add a new class for auto_unroll_max_step, storage_offset in StageNode

* fix tune_op_subgraph.py

* rebase

* Migrate all node::make to noderef's construct function (#37)

* Start to move xxxnode::make to noderef()

* Update

* Update

* Finish transform_step

* Finish comute dag & auto schedule

* Update

* Update

* Update

* Update

* Update

* Code refine

* Code refine

* Code refine

* Update

* Update

* Some lint fix & Recover the double constructor of tvm::PrimExpr (#39)

* lint fix

* clang-format-fix

* pylint fix

* Update

* Recover the double constructor of tvm::PrimExpr

* Fix pylint

* pylint fix

* pylint fix

* Add MutateComputeLocation and MutateParallel in evolutionary search (#40)

* Add MutateComputeLocation and MutateParallel in evolutionary search

* fix lint

* Improve loop state python API (stage_tensors -> stage_ops) (#41)

* improve loop state python API (stage_tensors -> stage_ops)

* fix

* ComputeDAG bug fix & Add Custom TensorCore Matmul Example (#42)

* Bug Fix

* Sample example of Custom TensorCore Matmul

* Rever Commits, Start to build minimum Ansor system

* Code clean for minimum Ansor system

* Bug fix & Delete AccessAnalyzer

* Delete attachmap & Code clean

* Doc update

Update statenode::stages from vector to Array

* Headfile update & Python doc update

* clang-format fix

* pylint fix

* Update

* Doc update

* Update

* Bug fix after code merge to the new master

* clang-format fix

* Update

* Update

* Update std::vector to Array; Update verbosity setting; Some commemts
addressed

* std::vector->Array & std::string->String

* Add init_state to ComputeDAG

* Update

* Update some unordered_map to Map

* clang-format fix

* Comments addressed
Delete ReplayAndInferBound
Delete ReplaySteps & InferBoundCommon

* Lint fix

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Rename ansor namespace to auto_schedule

* Update

* Rename ThreadPool to ParallelFor

* Add parallel_for

* Remove ThreadPool

* Update python/tvm/auto_schedule/auto_schedule.py

* trigger CI

Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com>
Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com>
Co-authored-by: Zhao Wu <zhaowu@apache.org>
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2 participants