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Unstable branch sync with dmlc/tvm 20190309 #11

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@wweic wweic commented Mar 9, 2019

Pull all commits since last sync:

git cherry-pick aaad5f988fa729d456ef546b49242794fdc7eabd..master

jroesch and others added 30 commits March 9, 2019 15:17
… pass (apache#2646)

* check in

* fix typo

* fix typo

* change message

* change message

* typo

* lint
Recent pylint warngs about import renames with no effect.  Remove
them.
* Add arange op

* Update docs

* Fix bug

* add sanity check in relay and mxnet frontend mapping

* lint

* nits

* pylint

* don't allow empty output from arange

* Remove empty test for arange

* Fix bug and update doc
* i think it works for now?

* fix lint

* fix 2/3 compat

* fix py2 again

* fine, i gave up
* Add CONCATENATION to tflite frontend

* fix typo

* Fix codestyle

* Fix code style

* simplify convert map

* Update
@wweic wweic changed the title Unstable sync 20190309 Unstable branch sync with dmlc/tvm 20190309 Mar 9, 2019
@wweic wweic closed this Mar 12, 2019
@wweic wweic deleted the unstable-sync-20190309 branch March 12, 2019 00:43
alexwong pushed a commit to alexwong/tvm that referenced this pull request Feb 24, 2020
* relay op strategy

fix lint

bitpack strategy

bitserial_dense (neo-ai#6)

* update strategy

* address comments

fix a few topi test

Dense strategy (neo-ai#5)

* dense

* add biforst; remove comments

* address comment

Refactor x86 conv2d_NCHWc (neo-ai#4)

* Refactor x86 conv2d

* Add x86 depthwise_conv2d_NCHWc

* Add back topi x86 conv2d_nchw

* Merge x86 conv2d_nchw and conv2d_NCHWc

* Minor fix for x86 conv2d

fix more strategy

Add x86 conv2d_NCHWc_int8 strategy (neo-ai#8)

* Add x86 conv2d_NCHWc_int8 strategy

* Remove contrib_conv2d_nchwc_int8

* Fix generic conv2d_NCHWc for int8

* Fix topi arm_cpu conv2d_NCHWc_int8

update x86 conv2d

enable specify relay ops to be tuned for autotvm

add cuda conv2d strategy

add conv2d strategy for rocm

add conv2d strategy for hls

add conv2d strategy for arm cpu

add conv2d strategy for mali

add conv2d strategy for bifrost

add conv2d strategy for intel graphics

clean up and fix lint

remove template keys from autotvm

remove 2 in the func name

address comments

fix

* fix bugs

* lint

* address comments

* add name to op implement

* Modify topi tests (neo-ai#9)

* Add pooling, reorg, softmax and vision

* Add lrn

* fix topi test

* fix more topi test

* lint

* address comments

* x

* fix more tests & bugs

* Modify more tests (neo-ai#10)

* Modify tests for bitserial_conv2d, bitserial_dense, bitserial_conv2d_rasp and bnn

* Minor fix

* More minor fix

* fix more test

* try to update vta using strategy

* fix cpptest

* x

* fix rebase err

* Fix two tests (neo-ai#11)

* change autotvm log format

* lint

* minor fix

* try fix vta test

* fix rebase err

* tweak

* tmp hack for vta pass

* fix tutorial

* fix

* fix more tutorials

* fix vta tutorial

* minor

* address comments

* fix

* address comments

* fix cpptest

* fix docs

* change data structure name and api

* address comments

* lint

* fix rebase err

* updates

* fix winograd test

* fix doc

* rebase

* upgrade tophub version number

* fix bug

* re-enable vta tsim test after tophub is upgraded

* fix vta test to use the correct args so the config can be found in tophub

Co-authored-by: Yao Wang <kevinthesunwy@gmail.com>
alexwong pushed a commit to alexwong/tvm that referenced this pull request Feb 26, 2020
* relay op strategy

fix lint

bitpack strategy

bitserial_dense (neo-ai#6)

* update strategy

* address comments

fix a few topi test

Dense strategy (neo-ai#5)

* dense

* add biforst; remove comments

* address comment

Refactor x86 conv2d_NCHWc (neo-ai#4)

* Refactor x86 conv2d

* Add x86 depthwise_conv2d_NCHWc

* Add back topi x86 conv2d_nchw

* Merge x86 conv2d_nchw and conv2d_NCHWc

* Minor fix for x86 conv2d

fix more strategy

Add x86 conv2d_NCHWc_int8 strategy (neo-ai#8)

* Add x86 conv2d_NCHWc_int8 strategy

* Remove contrib_conv2d_nchwc_int8

* Fix generic conv2d_NCHWc for int8

* Fix topi arm_cpu conv2d_NCHWc_int8

update x86 conv2d

enable specify relay ops to be tuned for autotvm

add cuda conv2d strategy

add conv2d strategy for rocm

add conv2d strategy for hls

add conv2d strategy for arm cpu

add conv2d strategy for mali

add conv2d strategy for bifrost

add conv2d strategy for intel graphics

clean up and fix lint

remove template keys from autotvm

remove 2 in the func name

address comments

fix

* fix bugs

* lint

* address comments

* add name to op implement

* Modify topi tests (neo-ai#9)

* Add pooling, reorg, softmax and vision

* Add lrn

* fix topi test

* fix more topi test

* lint

* address comments

* x

* fix more tests & bugs

* Modify more tests (neo-ai#10)

* Modify tests for bitserial_conv2d, bitserial_dense, bitserial_conv2d_rasp and bnn

* Minor fix

* More minor fix

* fix more test

* try to update vta using strategy

* fix cpptest

* x

* fix rebase err

* Fix two tests (neo-ai#11)

* change autotvm log format

* lint

* minor fix

* try fix vta test

* fix rebase err

* tweak

* tmp hack for vta pass

* fix tutorial

* fix

* fix more tutorials

* fix vta tutorial

* minor

* address comments

* fix

* address comments

* fix cpptest

* fix docs

* change data structure name and api

* address comments

* lint

* fix rebase err

* updates

* fix winograd test

* fix doc

* rebase

* upgrade tophub version number

* fix bug

* re-enable vta tsim test after tophub is upgraded

* fix vta test to use the correct args so the config can be found in tophub

Co-authored-by: Yao Wang <kevinthesunwy@gmail.com>
alexwong pushed a commit to alexwong/tvm that referenced this pull request Feb 28, 2020
* relay op strategy

fix lint

bitpack strategy

bitserial_dense (neo-ai#6)

* update strategy

* address comments

fix a few topi test

Dense strategy (neo-ai#5)

* dense

* add biforst; remove comments

* address comment

Refactor x86 conv2d_NCHWc (neo-ai#4)

* Refactor x86 conv2d

* Add x86 depthwise_conv2d_NCHWc

* Add back topi x86 conv2d_nchw

* Merge x86 conv2d_nchw and conv2d_NCHWc

* Minor fix for x86 conv2d

fix more strategy

Add x86 conv2d_NCHWc_int8 strategy (neo-ai#8)

* Add x86 conv2d_NCHWc_int8 strategy

* Remove contrib_conv2d_nchwc_int8

* Fix generic conv2d_NCHWc for int8

* Fix topi arm_cpu conv2d_NCHWc_int8

update x86 conv2d

enable specify relay ops to be tuned for autotvm

add cuda conv2d strategy

add conv2d strategy for rocm

add conv2d strategy for hls

add conv2d strategy for arm cpu

add conv2d strategy for mali

add conv2d strategy for bifrost

add conv2d strategy for intel graphics

clean up and fix lint

remove template keys from autotvm

remove 2 in the func name

address comments

fix

* fix bugs

* lint

* address comments

* add name to op implement

* Modify topi tests (neo-ai#9)

* Add pooling, reorg, softmax and vision

* Add lrn

* fix topi test

* fix more topi test

* lint

* address comments

* x

* fix more tests & bugs

* Modify more tests (neo-ai#10)

* Modify tests for bitserial_conv2d, bitserial_dense, bitserial_conv2d_rasp and bnn

* Minor fix

* More minor fix

* fix more test

* try to update vta using strategy

* fix cpptest

* x

* fix rebase err

* Fix two tests (neo-ai#11)

* change autotvm log format

* lint

* minor fix

* try fix vta test

* fix rebase err

* tweak

* tmp hack for vta pass

* fix tutorial

* fix

* fix more tutorials

* fix vta tutorial

* minor

* address comments

* fix

* address comments

* fix cpptest

* fix docs

* change data structure name and api

* address comments

* lint

* fix rebase err

* updates

* fix winograd test

* fix doc

* rebase

* upgrade tophub version number

* fix bug

* re-enable vta tsim test after tophub is upgraded

* fix vta test to use the correct args so the config can be found in tophub

Co-authored-by: Yao Wang <kevinthesunwy@gmail.com>
zhiics pushed a commit that referenced this pull request Mar 2, 2020
* relay op strategy

fix lint

bitpack strategy

bitserial_dense (#6)

* update strategy

* address comments

fix a few topi test

Dense strategy (#5)

* dense

* add biforst; remove comments

* address comment

Refactor x86 conv2d_NCHWc (#4)

* Refactor x86 conv2d

* Add x86 depthwise_conv2d_NCHWc

* Add back topi x86 conv2d_nchw

* Merge x86 conv2d_nchw and conv2d_NCHWc

* Minor fix for x86 conv2d

fix more strategy

Add x86 conv2d_NCHWc_int8 strategy (#8)

* Add x86 conv2d_NCHWc_int8 strategy

* Remove contrib_conv2d_nchwc_int8

* Fix generic conv2d_NCHWc for int8

* Fix topi arm_cpu conv2d_NCHWc_int8

update x86 conv2d

enable specify relay ops to be tuned for autotvm

add cuda conv2d strategy

add conv2d strategy for rocm

add conv2d strategy for hls

add conv2d strategy for arm cpu

add conv2d strategy for mali

add conv2d strategy for bifrost

add conv2d strategy for intel graphics

clean up and fix lint

remove template keys from autotvm

remove 2 in the func name

address comments

fix

* fix bugs

* lint

* address comments

* add name to op implement

* Modify topi tests (#9)

* Add pooling, reorg, softmax and vision

* Add lrn

* fix topi test

* fix more topi test

* lint

* address comments

* x

* fix more tests & bugs

* Modify more tests (#10)

* Modify tests for bitserial_conv2d, bitserial_dense, bitserial_conv2d_rasp and bnn

* Minor fix

* More minor fix

* fix more test

* try to update vta using strategy

* fix cpptest

* x

* fix rebase err

* Fix two tests (#11)

* change autotvm log format

* lint

* minor fix

* try fix vta test

* fix rebase err

* tweak

* tmp hack for vta pass

* fix tutorial

* fix

* fix more tutorials

* fix vta tutorial

* minor

* address comments

* fix

* address comments

* fix cpptest

* fix docs

* change data structure name and api

* address comments

* lint

* fix rebase err

* updates

* fix winograd test

* fix doc

* rebase

* upgrade tophub version number

* fix bug

* re-enable vta tsim test after tophub is upgraded

* fix vta test to use the correct args so the config can be found in tophub

Co-authored-by: Yao Wang <kevinthesunwy@gmail.com>
trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jul 2, 2020
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>
trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Oct 12, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (neo-ai#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
TusharKanekiDey pushed a commit to TusharKanekiDey/tvm that referenced this pull request Oct 13, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (neo-ai#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
TusharKanekiDey pushed a commit to TusharKanekiDey/tvm that referenced this pull request Oct 14, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (neo-ai#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
TusharKanekiDey pushed a commit to TusharKanekiDey/tvm that referenced this pull request Oct 15, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (neo-ai#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
TusharKanekiDey pushed a commit to TusharKanekiDey/tvm that referenced this pull request Oct 15, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (neo-ai#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
TusharKanekiDey pushed a commit to TusharKanekiDey/tvm that referenced this pull request Oct 16, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (neo-ai#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
TusharKanekiDey pushed a commit to TusharKanekiDey/tvm that referenced this pull request Oct 16, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (neo-ai#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
trevor-m pushed a commit that referenced this pull request Oct 19, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
trevor-m pushed a commit that referenced this pull request Oct 19, 2020
…odule, and use new diagnostics. (apache#6274)

* Refactor the type checker to use diagnostics

Although this patch is very large and seemingly disjoint the
fixes are required to get it working for the entire stack.
I started with first changing InferType to use the diagnostics,
these weren't yet in the pass manager so this required changes
to module and module pass. InferType wasn't actually written
correctly as a pass requring refactoring there, then in order
to add spans to AST it required turning on AnnotateSpans which
in term required changes to the parser, and module to make
it possible to use the errors. These changes to parse and module
required changes to diagnostics and InferType. Althought seemingly
disconnected there are hidden cycles between the components which
require simultaneous change in order to remove the old error
reporting.

A huge change due to this patch is that the module no longer
implicitly type checks functions which are added.

* Apply suggestions from code review

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>

* Apply suggestions from code review

Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>

* Clean up parser

* CR feedback

* Apply Bobs suggestions

* Fix up Python interface for diagnostics

* Fix test_ir_parser and formatting

* Fix cpplint

* Fix lint

* Fix format

* More lint

* Fix format

* Kill dead doc comment

* Fix documentation comment

* Rebase fixups

* Add docs for type.h

* Fix parser.cc

* Fix unittests

* Fix black

* Skip previously typechecked functions

* fix ACL

* Fix numerous issues

* Add repr method

* Fix issue with Pytest, I am ready to cry

* Fix the rest of tests

* Kill dead code

* Fix dignostic tests

* Fix more tests

* fix more tests (#11)

* Fix diagnostic.py deinit bug

* Fix deinit issue

* Format

* Tweak disabling of override

* Format

* Fix BYOC

* Fix TensorArray stuff

* Fix PyTorch

* Format

* Format

Co-authored-by: Robert Kimball <bobkimball@gmail.com>
Co-authored-by: Junru Shao <junrushao1994@gmail.com>
Co-authored-by: Tristan Konolige <tristan.konolige@gmail.com>
Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>
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