[LANG] Enable json load/save and pickle #10
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
tqchen
added a commit
to tqchen/tvm
that referenced
this pull request
May 26, 2018
tqchen
added a commit
to tqchen/tvm
that referenced
this pull request
May 26, 2018
tqchen
added a commit
that referenced
this pull request
May 29, 2018
tqchen
added a commit
that referenced
this pull request
May 29, 2018
tqchen
added a commit
to tqchen/tvm
that referenced
this pull request
Jul 6, 2018
tqchen
added a commit
to tqchen/tvm
that referenced
this pull request
Jul 6, 2018
sergei-mironov
pushed a commit
to sergei-mironov/tvm
that referenced
this pull request
Aug 8, 2018
sergei-mironov
pushed a commit
to sergei-mironov/tvm
that referenced
this pull request
Aug 8, 2018
tmoreau89
added a commit
to tmoreau89/tvm
that referenced
this pull request
Jan 2, 2019
wweic
pushed a commit
to wweic/tvm
that referenced
this pull request
Mar 12, 2019
* add missed part of annotation * fix check_computation and slice_like * keep _build as before * fix vta failure
tmoreau89
added a commit
to tmoreau89/tvm
that referenced
this pull request
Mar 22, 2019
tmoreau89
added a commit
to tmoreau89/tvm
that referenced
this pull request
Mar 22, 2019
Merged
kevinthesun
added a commit
to kevinthesun/tvm
that referenced
this pull request
Feb 12, 2020
* Modify tests for bitserial_conv2d, bitserial_dense, bitserial_conv2d_rasp and bnn * Minor fix * More minor fix
merrymercy
pushed a commit
that referenced
this pull request
Feb 24, 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>
tqchen
pushed a commit
to tqchen/tvm
that referenced
this pull request
Mar 29, 2020
* relay op strategy fix lint bitpack strategy bitserial_dense (apache#6) * update strategy * address comments fix a few topi test Dense strategy (apache#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 (apache#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 (apache#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 (apache#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 (apache#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>
apivovarov
pushed a commit
to apivovarov/tvm
that referenced
this pull request
May 16, 2020
* relay op strategy fix lint bitpack strategy bitserial_dense (apache#6) * update strategy * address comments fix a few topi test Dense strategy (apache#5) * dense * add biforst; remove comments * address comment Refactor x86 conv2d_NCHWc (apache#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 (apache#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 (apache#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 (apache#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 (apache#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>
jcf94
added a commit
to jcf94/tvm
that referenced
this pull request
Jun 22, 2020
* Delete C++ UT hack since Python is ready * Add ndarray.non_empty * Update Serialization python API
7 tasks
tqchen
pushed a commit
that referenced
this pull request
Jul 15, 2020
…generating (#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>
CloudManX
pushed a commit
to CloudManX/incubator-tvm
that referenced
this pull request
Sep 15, 2020
…generating (apache#5962) * Code migration Start (apache#1) * Init commit: Code migration Start * Add loop_state.cc/h * Add ComputeDAG basic test * Split transform_step out & Update more UTs (apache#3) * Split transform_step out * Update GetProducers & GetConsumers * Update UTs * Add UT for CacheReadWrite & Some bug fix * Add search_task, measure and serialization (apache#4) * Add FollowSplit & FollowFusedSplit tests * Update dag.InferBound & its UT * Add search_task, measure and serialization * Update Serialization UT * Add MetaTileRewritePolicy (apache#5) * Add feature * Add cost_model, meta_tile_rewrite_policy * Add MetaTileRewritePolicy basic UT * Basic Python API for State (apache#6) * Add Basic Python API for State * Add UTs for State * Add Python API: Measure & Task (apache#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(apache#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 (apache#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 (apache#11) * Update c++ code style and unit test * Update python State wrapper and test cases * fix unit tests * Add RPCRunner & OpenCL/CUDA test (apache#12) * Add RPCRunner & OpenCL search test * Add CUDA search test * Add RPCRunner test * rebase to upstream/master * Add Ansor basic tutorial (apache#13) * Add basic tutorial * migrate feature extraction (apache#14) * Add XGBModel & RPCRunnerWarpper (apache#15) * Add XGBModel & RPCRunnerWarpper * Revert "Add Parallel Granularity Mutation" * Migrate workload_registry.py (apache#16) * add workload registry * update * update * add task scheduler (apache#17) * Add conv2d cuda tutorial with workload registry (apache#18) * add tune_test.py (the old tune_wkl.py) (apache#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 (apache#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 (apache#21) * Add custom sketch rule * Bug fix * Ansor Relay Integration (without layout rewrite) (apache#22) * relay integration * Add tune_op_subgraph.py & Some code clean for tune_network.py (apache#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 (apache#25) * Add Index simplification & API update (apache#26) * Add vectorized cooperative_fetching test * Update math simplify for vectorized CF * File rename * Update tune_network * API update * Update PreLoadMeasuredStates & Some bug fix (apache#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 (apache#31) * Add tensorize step * State python api update (apache#33) * Start to update api * Add compute_dag to state * API update * kernel layout rewrite (apache#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 (apache#32) * Improve relay integration (apache#34) * tmp checkpoint * Improve relay integration * Improve relay integration * Fix xgb error & Simplify dispatcher (apache#35) * Rename "MetaTileRewritePolicy" to "SketchPolicy". (apache#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 (apache#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 (apache#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 (apache#40) * Add MutateComputeLocation and MutateParallel in evolutionary search * fix lint * Improve loop state python API (stage_tensors -> stage_ops) (apache#41) * improve loop state python API (stage_tensors -> stage_ops) * fix * ComputeDAG bug fix & Add Custom TensorCore Matmul Example (apache#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>
ZihengJiang
pushed a commit
to ZihengJiang/tvm
that referenced
this pull request
Nov 26, 2020
* Move scale handling from thresholds to quantize * Add clip requantization * minor * Comments
Closed
hypercubestart
pushed a commit
to hypercubestart/incubator-tvm
that referenced
this pull request
Mar 12, 2021
* Move scale handling from thresholds to quantize * Add clip requantization * minor * Comments
wjj19950828
pushed a commit
to wjj19950828/tvm
that referenced
this pull request
Aug 22, 2021
pylint check
MasterJH5574
added a commit
to MasterJH5574/tvm
that referenced
this pull request
Nov 6, 2021
* Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * [SparseTIR] Introduce SpIterVar (apache#6) * [SparseTIR] Introduce SpIterVar * Add conversion to PrimExpr * [BugFix] Fix binary search & SpIterVar (apache#7) * [BugFix] Add field `is_reduction` for SpIterVar (apache#9) * [BugFix] Add field `is_reduction` for SpIterVar * Formatting * upd * upd Co-authored-by: Ruihang Lai <lairuihangdongdong@qq.com>
MasterJH5574
added a commit
to MasterJH5574/tvm
that referenced
this pull request
Nov 10, 2021
* Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * [SparseTIR] Introduce SpIterVar (apache#6) * [SparseTIR] Introduce SpIterVar * Add conversion to PrimExpr * [BugFix] Fix binary search & SpIterVar (apache#7) * [BugFix] Add field `is_reduction` for SpIterVar (apache#9) * [BugFix] Add field `is_reduction` for SpIterVar * Formatting * upd * upd Co-authored-by: Ruihang Lai <lairuihangdongdong@qq.com>
MasterJH5574
added a commit
to MasterJH5574/tvm
that referenced
this pull request
Nov 20, 2021
* Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * [SparseTIR] Introduce SpIterVar (apache#6) * [SparseTIR] Introduce SpIterVar * Add conversion to PrimExpr * [BugFix] Fix binary search & SpIterVar (apache#7) * [BugFix] Add field `is_reduction` for SpIterVar (apache#9) * [BugFix] Add field `is_reduction` for SpIterVar * Formatting * upd * upd Co-authored-by: Ruihang Lai <lairuihangdongdong@qq.com>
MasterJH5574
added a commit
to MasterJH5574/tvm
that referenced
this pull request
Nov 24, 2021
* Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * [SparseTIR] Introduce SpIterVar (apache#6) * [SparseTIR] Introduce SpIterVar * Add conversion to PrimExpr * [BugFix] Fix binary search & SpIterVar (apache#7) * [BugFix] Add field `is_reduction` for SpIterVar (apache#9) * [BugFix] Add field `is_reduction` for SpIterVar * Formatting * upd * upd Co-authored-by: Ruihang Lai <lairuihangdongdong@qq.com>
MasterJH5574
added a commit
to MasterJH5574/tvm
that referenced
this pull request
Dec 24, 2021
* Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * [SparseTIR] Introduce SpIterVar (apache#6) * [SparseTIR] Introduce SpIterVar * Add conversion to PrimExpr * [BugFix] Fix binary search & SpIterVar (apache#7) * [BugFix] Add field `is_reduction` for SpIterVar (apache#9) * [BugFix] Add field `is_reduction` for SpIterVar * Formatting * upd * upd Co-authored-by: Ruihang Lai <lairuihangdongdong@qq.com>
MasterJH5574
pushed a commit
to MasterJH5574/tvm
that referenced
this pull request
Feb 26, 2022
* ExprVisitor/ExprMutator for relax nodes. * Update Visitor & Mutator. * Update Mutator. * DataflowMutator interface. * EwiseFMARewriter. * Update fma rewrite and add test. * Update test. * Fix dataflow block dispatching. * Construct new dataflow block with IRBuilder. * VisitBinding return void and mutate internal IRBuilder. * Simplify. * Update emit dataflow output. * Explicit memeory allocation rewrite. * LazyIRBuilder. * Update ExplicitMemMutator. * Overload IRBuilder::Emit to have 3 styles. * Update IRBuilder/IRMutator interfaces and passes. * Add MatchShape binding to IRBuilder. * Improve IRMutator interface; add Normalize and CanProveShapeEqual to IRBuilder * Update EmitMatchShape. Co-authored-by: ZihengJiang <ziheng@apache.org>
MasterJH5574
pushed a commit
to MasterJH5574/tvm
that referenced
this pull request
Mar 3, 2022
* ExprVisitor/ExprMutator for relax nodes. * Update Visitor & Mutator. * Update Mutator. * DataflowMutator interface. * EwiseFMARewriter. * Update fma rewrite and add test. * Update test. * Fix dataflow block dispatching. * Construct new dataflow block with IRBuilder. * VisitBinding return void and mutate internal IRBuilder. * Simplify. * Update emit dataflow output. * Explicit memeory allocation rewrite. * LazyIRBuilder. * Update ExplicitMemMutator. * Overload IRBuilder::Emit to have 3 styles. * Update IRBuilder/IRMutator interfaces and passes. * Add MatchShape binding to IRBuilder. * Improve IRMutator interface; add Normalize and CanProveShapeEqual to IRBuilder * Update EmitMatchShape. Co-authored-by: ZihengJiang <ziheng@apache.org>
MasterJH5574
pushed a commit
to MasterJH5574/tvm
that referenced
this pull request
Mar 7, 2022
[SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> Fix AxisTree (apache#3) * fix axis tree * upd [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` [SparseTIR] Introduce SpIterVar (apache#6) * [SparseTIR] Introduce SpIterVar * Add conversion to PrimExpr [BugFix] Fix binary search & SpIterVar (apache#7) [BugFix] Add field `is_reduction` for SpIterVar (apache#9) * [BugFix] Add field `is_reduction` for SpIterVar * Formatting [SparseTIR] Index Lowering (apache#8) * Add StmtFunctor/ExprFunctor for SparseBufferStore/Load * Add basic index lowering * Finish index lowering (maybe) * Address comments * Convert CRLF to LF Frontend update, demo scripts. (apache#10) * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * fix axis tree * upd * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * Format and Buffer data structure (apache#1) * [SparseTIR] Constructors and Python Interface for `Axis` and `SparseBuffer` (apache#2) * add methods for Object * axis constructors * methods for SparseBuffer * put into registry * python interface * [CherryPick][Intrinsic] lower_bound and upper_bound for binary search in Sparse TIR. (apache#483) (apache#4) * upd * upd * fix * upd * upd * upd * upd * upd * fix * upd * upd * upd * upd * upd * upd * upd * codegen-rule * upd * upd * test * upd * fix * two arguments Co-authored-by: Zihao Ye <expye@outlook.com> * Fix AxisTree (apache#3) * fix axis tree * upd * [SparseTIR] Add SparseBufferLoad/SparseBufferStore (apache#5) * Add dtype for SparseBuffer * Add name for SparseBuffer. Remove `ndim` * Remove namespace sparse * Add SparseBufferLoad/Store * Add method `ndim()` * [SparseTIR] Introduce SpIterVar (apache#6) * [SparseTIR] Introduce SpIterVar * Add conversion to PrimExpr * [BugFix] Fix binary search & SpIterVar (apache#7) * [BugFix] Add field `is_reduction` for SpIterVar (apache#9) * [BugFix] Add field `is_reduction` for SpIterVar * Formatting * upd * upd Co-authored-by: Ruihang Lai <lairuihangdongdong@qq.com> [SparseTIR] SparseBlock on C++/Python side (apache#11) * Fix a bug in the last commit * SparseBlock on C++ & Python side [BugFix][SparseTIR] TVMScript Parser for Axis & SpIterVar (apache#12) * Update `cord` and `pos` * Fix `idtype` * Formatting.. * Bug fix 1 * Move new special stmts * Parser for Axis and SpIterVar * Fix context_maintainer.py [SparseTIR] Enhance SparseBlock to contain enough PrimFunc information (apache#13) * Enhance SparseBlock to have enough PrimFunc info * Remove `func_sparse_buffer_map_` * Don't print the map uh-huh [SparseTIR] Parser, Printer, Roundtrip (apache#14) * SparseBlock scope handler (part 1) * SparseBlock scope handler (part 2) * SparseBlock scope handler (part 3) * SparseBlock scope handler (fix 1) * Add SparseBufferLoad/Store on Python side * Parser for SparseBufferLoad/Store * Add SparseBlock to Python __init__ * StmtFunctor for SparseBlock * Ensure at least one dimension for SparseBuffer * Make `axis` field of SpIterVar mandatory * SparseBlock scope handler (fix 2) * Update Axis syntax by removing `name` parameter * Move to intrin.py * Add filed `from_sparse` to DenseFixedAxis * SparseTIR script printer * Roundtrip test * `update_symbol` bug fix * Fix attr visit in SparseBuffer * Define then compare in SparseBlock * Fix printer bug for SparseBuffer * Enable graph match for Axis and SparseBuffer * Complete HashReduce and EqualReduce for AxisTree and SparseBuffer * Fix typo * Rename test * Bug fix 1 * Bug fix 2 * Add more tests Move tests (apache#15) [SparseTIR] ReprPrinter for Axis and SpIterVar (apache#16) upd (apache#17) flatten (apache#18) ELL and BSR correctness test scripts (apache#19) [SparseTIR] SparseTIR Lowering (apache#20) * Fix a previous bug of sparse-fixed SpIterVar creation * Fix a previous bug in `GetDenseValue` * Refactor Collector and IndexTransformer * Construct block and loops * Fix a previous bug which rejects DV iters in collector * Update buffer map * Create root block * Fix bug of sparse-fixed SpIterVar creation * Fix bug on SpIterVar conversion (with refactor) * Fix bug when getting dependent SpIterVars * Fix bug on dependency map and index lowering * Full block read/write region * Test version 1 * Fix bug of loop order * Fix bug of batch-mm iterator ordering * Update PrimFunc args to use symbolic params * Fix bug of test "csr_element_wise" * Fix bug of index accumulation for sparse-fixed axis * Update correctness test * Test structural equality * Refactor and use Array fix nnz cols Add docstring for sparse tir lowering (apache#21) * add docstring * upd Add more examples part 1 (sddmm) (apache#22) * upd * upd * upd [SparseTIR][Schedule] SparseBlockRV, GetSparseBlock, SparseReorder (apache#23) * Test initialization * Fix a stupid bug of ReprPrinter * Add SparseBlockRV * Schedule: GetSparseBlock * Schedule: Reorder [SparseTIR][Schedule] GetSpIters (apache#24) remove hybrid script for successful compilation Add atomic intrinsic for output nonzero inference. (apache#25) * upd * upd Add "sparse" block attribute. (apache#26) Revert "remove hybrid script for successful compilation" This reverts commit eebd7c1. [SparseTIR] Hack `IsAffineBinding` check (apache#27) * [TensorIR][Schedule] Inherit block anotation upon creating new blocks * Fix SDDMM test * Hack IsAffineBinding for sparse blocks Axis Dependency Tree aware code-gen and bmm example (apache#28) * upd * upd * upd * upd * upd * upd * upd * upd * remove redundancy * fix * upd * upd Re-design Indices lowering (apache#29) * upd * upd * upd * upd * upd * init * format * fix * revise coding-style * format Complete indices lowering (apache#30) * upd * upd * upd * done * upd * passed test * upd Add more docstrings and depress warnings for new lowering algorithm. (apache#31) Refactor derived axis, frontend support of fusion. (apache#32) * upd * upd * fix Fatal bugfix and change the signature of DenseVariableAxis. (apache#33) Syntax simplification (apache#34) Change the order of generated blocks for block isolation. (apache#35) * upd * upd * upd Syntax of AttachAxis for BMM (apache#36) * upd * upd * upd [SparseTIR] Add "square sum" lowering test (apache#37) * Add square sum test * Remove pylint comment [BugFix] Fix offset caching in lowering (apache#38) * Hack compact dataflow check in a dirty way * Add two-K square sum test * Mark skipped tests * Fix offset saving in lowering Fusion syntax fix + SDDMM example. (apache#39) Some structure change on update offsets. (apache#40) [Refactor] SparseTIR Lowering (apache#41) * Take out methods in Scope * Refactor * Refactor "match" * Tweak scope contents * Refactor ViewIndexInAxis * Refactor Scope * SDDMM tests under implementation * Refactor block stack * Use Map for var_map * Extract NeedCreateNewBlock * Simplify SpIterVarToIterVar via GetIterExtent * Refactor NeedCreateNewBlock * Add docstring * Use "auto" correctly * Minor refactor and use some move Remove redundant analyzers (apache#42) Support indices lowering for attach and fuse. (apache#43) * upd * upd * upd Fix irregular BMM example. (apache#44) * upd * upd * upd * upd RGCN forward and butterfly pattern example. (apache#45) Fused SDDMM example. (apache#46) * upd * wip * fix Fix sparse reorder after refactor (apache#47) [Refactor] Refactor Unittest (apache#48) * upd * remove redundancy [Unittest] Correctness test for benchmarking scripts (apache#49) Bugfix and more test for axis fusion, new workload (apache#50) * upd * upd upd
prateek9623
pushed a commit
to prateek9623/tvm
that referenced
this pull request
May 1, 2022
disable a warning for now
jinhongyii
pushed a commit
to jinhongyii/tvm
that referenced
this pull request
Jun 20, 2022
* ExprVisitor/ExprMutator for relax nodes. * Update Visitor & Mutator. * Update Mutator. * DataflowMutator interface. * EwiseFMARewriter. * Update fma rewrite and add test. * Update test. * Fix dataflow block dispatching. * Construct new dataflow block with IRBuilder. * VisitBinding return void and mutate internal IRBuilder. * Simplify. * Update emit dataflow output. * Explicit memeory allocation rewrite. * LazyIRBuilder. * Update ExplicitMemMutator. * Overload IRBuilder::Emit to have 3 styles. * Update IRBuilder/IRMutator interfaces and passes. * Add MatchShape binding to IRBuilder. * Improve IRMutator interface; add Normalize and CanProveShapeEqual to IRBuilder * Update EmitMatchShape. Co-authored-by: ZihengJiang <ziheng@apache.org>
Hzfengsy
pushed a commit
to Hzfengsy/tvm
that referenced
this pull request
Jul 30, 2022
* ExprVisitor/ExprMutator for relax nodes. * Update Visitor & Mutator. * Update Mutator. * DataflowMutator interface. * EwiseFMARewriter. * Update fma rewrite and add test. * Update test. * Fix dataflow block dispatching. * Construct new dataflow block with IRBuilder. * VisitBinding return void and mutate internal IRBuilder. * Simplify. * Update emit dataflow output. * Explicit memeory allocation rewrite. * LazyIRBuilder. * Update ExplicitMemMutator. * Overload IRBuilder::Emit to have 3 styles. * Update IRBuilder/IRMutator interfaces and passes. * Add MatchShape binding to IRBuilder. * Improve IRMutator interface; add Normalize and CanProveShapeEqual to IRBuilder * Update EmitMatchShape. Co-authored-by: ZihengJiang <ziheng@apache.org>
areusch
pushed a commit
to areusch/tvm
that referenced
this pull request
Sep 20, 2022
* ExprVisitor/ExprMutator for relax nodes. * Update Visitor & Mutator. * Update Mutator. * DataflowMutator interface. * EwiseFMARewriter. * Update fma rewrite and add test. * Update test. * Fix dataflow block dispatching. * Construct new dataflow block with IRBuilder. * VisitBinding return void and mutate internal IRBuilder. * Simplify. * Update emit dataflow output. * Explicit memeory allocation rewrite. * LazyIRBuilder. * Update ExplicitMemMutator. * Overload IRBuilder::Emit to have 3 styles. * Update IRBuilder/IRMutator interfaces and passes. * Add MatchShape binding to IRBuilder. * Improve IRMutator interface; add Normalize and CanProveShapeEqual to IRBuilder * Update EmitMatchShape. Co-authored-by: ZihengJiang <ziheng@apache.org>
gigiblender
pushed a commit
to gigiblender/tvm
that referenced
this pull request
Nov 3, 2022
* ExprVisitor/ExprMutator for relax nodes. * Update Visitor & Mutator. * Update Mutator. * DataflowMutator interface. * EwiseFMARewriter. * Update fma rewrite and add test. * Update test. * Fix dataflow block dispatching. * Construct new dataflow block with IRBuilder. * VisitBinding return void and mutate internal IRBuilder. * Simplify. * Update emit dataflow output. * Explicit memeory allocation rewrite. * LazyIRBuilder. * Update ExplicitMemMutator. * Overload IRBuilder::Emit to have 3 styles. * Update IRBuilder/IRMutator interfaces and passes. * Add MatchShape binding to IRBuilder. * Improve IRMutator interface; add Normalize and CanProveShapeEqual to IRBuilder * Update EmitMatchShape. Co-authored-by: ZihengJiang <ziheng@apache.org>
MasterJH5574
pushed a commit
to MasterJH5574/tvm
that referenced
this pull request
Nov 20, 2022
* ExprVisitor/ExprMutator for relax nodes. * Update Visitor & Mutator. * Update Mutator. * DataflowMutator interface. * EwiseFMARewriter. * Update fma rewrite and add test. * Update test. * Fix dataflow block dispatching. * Construct new dataflow block with IRBuilder. * VisitBinding return void and mutate internal IRBuilder. * Simplify. * Update emit dataflow output. * Explicit memeory allocation rewrite. * LazyIRBuilder. * Update ExplicitMemMutator. * Overload IRBuilder::Emit to have 3 styles. * Update IRBuilder/IRMutator interfaces and passes. * Add MatchShape binding to IRBuilder. * Improve IRMutator interface; add Normalize and CanProveShapeEqual to IRBuilder * Update EmitMatchShape. Co-authored-by: ZihengJiang <ziheng@apache.org>
MasterJH5574
pushed a commit
to MasterJH5574/tvm
that referenced
this pull request
Nov 20, 2022
gigiblender
pushed a commit
to gigiblender/tvm
that referenced
this pull request
Jan 31, 2023
* Add squeeze. * Add Constant. * Add sub.
mbaret
pushed a commit
to mbaret/tvm
that referenced
this pull request
Feb 13, 2023
* Add squeeze. * Add Constant. * Add sub.
adstraw
pushed a commit
to adstraw/tvm
that referenced
this pull request
Feb 16, 2023
* e2e relax tuning * translation when qnn.Legalization is disabled. and Allow scalar tensors to have null shape during allocation. * micro kernerl update * fix
areusch
pushed a commit
to areusch/tvm
that referenced
this pull request
Feb 24, 2023
* ExprVisitor/ExprMutator for relax nodes. * Update Visitor & Mutator. * Update Mutator. * DataflowMutator interface. * EwiseFMARewriter. * Update fma rewrite and add test. * Update test. * Fix dataflow block dispatching. * Construct new dataflow block with IRBuilder. * VisitBinding return void and mutate internal IRBuilder. * Simplify. * Update emit dataflow output. * Explicit memeory allocation rewrite. * LazyIRBuilder. * Update ExplicitMemMutator. * Overload IRBuilder::Emit to have 3 styles. * Update IRBuilder/IRMutator interfaces and passes. * Add MatchShape binding to IRBuilder. * Improve IRMutator interface; add Normalize and CanProveShapeEqual to IRBuilder * Update EmitMatchShape. Co-authored-by: ZihengJiang <ziheng@apache.org>
vinx13
referenced
this pull request
in vinx13/tvm
Mar 27, 2023
* Initial importer and testing scaffolding. * Implement matmul operator and tests. * Add a bunch of new operators. * Add new ops * [Relax][Onnx] Implement Div, Sigmoid, Softmax, Transpose and Unsqueeze ops * skip test_reshape * [Relax][ONNX] Implement BiasGelu and Gelu ops * [Relax][ONNX] Implement Where op * [Relax][ONNX] Add Multiple ONNX Frontend Support for Clip / Equal / Shape / Not / Tanh (#3) * Rebase w/ Equal, Not, Tanh, Sqrt, Relu, Clip, Conv, Pow, Erf. * Fix cumsum but still needs work. * Fix initializer for CumSum. (#9) * Add Constant, Squeeze & Sub (#10) * Add squeeze. * Add Constant. * Add sub. * Support reusing Relay ONNX operator convertors in the Relax ONNX frontend (#8) * [WIP] Support using Relay ops in the Relax ONNX frontend Co-authored-by: Matthew Barrett <mbarrett@octoml.ai> Co-authored-by: Michalis Papadimitriou <mpapadimitriou@octoml.ai> * [WIP] small fixes Co-authored-by: Matthew Barrett <mbarrett@octoml.ai> Co-authored-by: Michalis Papadimitriou <mpapadimitriou@octoml.ai> * [WIP] Support dynamic matmul and reshape Co-authored-by: Matthew Barrett <mbarrett@octoml.ai> Co-authored-by: Michalis Papadimitriou <mpapadimitriou@octoml.ai> * Address PR comments --------- Co-authored-by: Matthew Barrett <mbarrett@octoml.ai> Co-authored-by: Michalis Papadimitriou <mpapadimitriou@octoml.ai> * Add more ops (including all Reduce ops) using the relay frontend (apache#11) * [WIP] add more ops. Some fail at the moment * skip some tests * Remove duplicate tests for squeeze * Add Split op in the Relax ONNX frontend (apache#12) * [Relax][ONNX] Add Split op * Remove tmp * Fix layer normalizations and Shape operator. * Replace main loop with tvm testing. * Simplify Slice for opset 13. * [Relax][ONNX] Implement pad op * Incorporate pad op, add static constantofshape op. * Changes to shape to temporarily enable constantofshape in our models. * Add initial tensor_to_shape implementation. * Implemented dynamic broadcast_to to support expand and constantofshape. * Changes sufficient for vortex end to end run. * Formatting. * Format tests. * Re-add broadcast_to shape checking. * Fix formatting. * Remove overly strict manipulate check. * Fix typing * [Relax][Onnx] Implement Tile operator * Switch to native relax attention importer. * Address some of the PR comments * Check for the imported model IR version * switch from torch to numpy due to some incompatibility * Fix make format. * Clean up typing issues. * Clarify variable name. * Remove unneeded comprehension. * Remove circular dependency. * Add name sanitization for inputs * Disable reshape rewrite pass until fixed. * Fix long comment * Update cpu image. --------- Co-authored-by: Florin Blanaru <fblanaru@octoml.ai> Co-authored-by: Xiyou Zhou <xiyou@octoml.ai> Co-authored-by: Matthew Barrett <mbarrett@octoml.ai> Co-authored-by: Michalis Papadimitriou <mpapadimitriou@octoml.ai> Co-authored-by: Florin Blanaru <florin.blanaru96@gmail.com> Co-authored-by: sung <sunggg@umich.edu>
mikeseven
pushed a commit
to mikeseven/tvm
that referenced
this pull request
Sep 27, 2023
SIM-3140: Add TOPI Approved-by: Jeffrey Uong
masahi
pushed a commit
to masahi/tvm
that referenced
this pull request
Jan 9, 2024
* wip * done * done
neigh80
added a commit
to Cloud-AutoVe-SWPlatform/tvm
that referenced
this pull request
Jan 22, 2024
micro TVM 데모 코드 정리 Closes apache#10 See merge request RTST_AI/tvm!8
LeiWang1999
added a commit
to LeiWang1999/tvm
that referenced
this pull request
Nov 8, 2024
* base tuner * gpu schedule * matmul ops * initial commit * refactor fast dlight to bit blas * support i8 swizzle * int8xint2 gemm * update keep * update lop3 cpp test * all low int to float16 convert * int8 fast decoding * float16with scale * annotate tc layout propa * impl tir interleve test * impl interleave weight. * weight only propagation * support layout propagate recover schedule of dequantize. * refactor testing * enhance gemv schedule for dynamic * dequantize matmul initilization * [refactor] move comments to BitBLAS * evaluate pytorch integeration * evaluate correctness of weight only decode * annotate mit license * annotate apache/mit lisence * init logger * refactor ops test with pytest * ladder_permutate implementation * append tvm third party lisence * scaling ladder permutate impl * add storage dtype test * implement lop3 permutation ops and related test * support with propagate layout. * update tvm lisence * disable fmt in pytest * implement cpu arch for consistency * seperate gemv schedule and gemv_dequantize schedule. * fix typo * refactor quantization * init testing. * refactor matmul and operators * append dequantize and test items * reslove lisence related items * refactor implementation * init read me. * integration with faster transform imp * integerate bug fix. * update ignore * improve code structure. * update mit lisence * remove gitkeep file * provide simple tir benchmark result. * enhance build * auto layout deduce * fix default tensorize. * update ReadMe * update readme * update read me * update readme * simple fix * readme fix * update codeql * update depenabot pipeline * update codeql * fix uint32 zero issue * initial transparency. * enhance transparency. * rename transparency * dependabot fix * update transparency. * update plugin * remove redundant transparency * dsl benchmark scirpts * update submodule. * remove redundant code. * remove transparency * fix propagate map issue * implement in register dequantize config * optimize target * fix tag. * fix some issues on ampere game device * finetune with data distribution. * fill matmul benchmarking scripts * refactor use_async_copy to bool value * support af format * format fix * support propagate input transform for dequantization. * update requirements * update requirements.txt * update af4 related tests. * clean test * naive support for dynamic zeros * move to bitdistiller * implement lop3 with zeros cpp test * implement fast decoding with zeros * update zero generation support. * Bump transformers from 4.29.2 to 4.36.0 Bumps [transformers](https://github.com/huggingface/transformers) from 4.29.2 to 4.36.0. - [Release notes](https://github.com/huggingface/transformers/releases) - [Commits](huggingface/transformers@v4.29.2...v4.36.0) --- updated-dependencies: - dependency-name: transformers dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * Bump pillow from 9.4.0 to 10.2.0 Bumps [pillow](https://github.com/python-pillow/Pillow) from 9.4.0 to 10.2.0. - [Release notes](https://github.com/python-pillow/Pillow/releases) - [Changelog](https://github.com/python-pillow/Pillow/blob/main/CHANGES.rst) - [Commits](python-pillow/Pillow@9.4.0...10.2.0) --- updated-dependencies: - dependency-name: pillow dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * Bump tornado from 6.2 to 6.3.3 Bumps [tornado](https://github.com/tornadoweb/tornado) from 6.2 to 6.3.3. - [Changelog](https://github.com/tornadoweb/tornado/blob/master/docs/releases.rst) - [Commits](tornadoweb/tornado@v6.2.0...v6.3.3) --- updated-dependencies: - dependency-name: tornado dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * Bump scipy from 1.5.3 to 1.11.1 Bumps [scipy](https://github.com/scipy/scipy) from 1.5.3 to 1.11.1. - [Release notes](https://github.com/scipy/scipy/releases) - [Commits](scipy/scipy@v1.5.3...v1.11.1) --- updated-dependencies: - dependency-name: scipy dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * Bump jinja2 from 3.1.2 to 3.1.3 Bumps [jinja2](https://github.com/pallets/jinja) from 3.1.2 to 3.1.3. - [Release notes](https://github.com/pallets/jinja/releases) - [Changelog](https://github.com/pallets/jinja/blob/main/CHANGES.rst) - [Commits](pallets/jinja@3.1.2...3.1.3) --- updated-dependencies: - dependency-name: jinja2 dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * Bump pygments from 2.2.0 to 2.15.0 Bumps [pygments](https://github.com/pygments/pygments) from 2.2.0 to 2.15.0. - [Release notes](https://github.com/pygments/pygments/releases) - [Changelog](https://github.com/pygments/pygments/blob/master/CHANGES) - [Commits](pygments/pygments@2.2.0...2.15.0) --- updated-dependencies: - dependency-name: pygments dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * Bump pygments from 2.13.0 to 2.15.0 Bumps [pygments](https://github.com/pygments/pygments) from 2.13.0 to 2.15.0. - [Release notes](https://github.com/pygments/pygments/releases) - [Changelog](https://github.com/pygments/pygments/blob/master/CHANGES) - [Commits](pygments/pygments@2.13.0...2.15.0) --- updated-dependencies: - dependency-name: pygments dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * update requirements and matmul. * support fast decode for int8 related items * improve pass context * update benchmark related figures. * update benchmark readme * reorganize readme * refactor readme * update benchmark readme * refactor quant linear for bisect * update tvm submodule * fix blockIdx related * update bitditiller related. * update zero type related test * implement zero types support * implement zero types support * fix lop3 permuteta issue. * fix weight executor bug. * improve typing * resolve performance related items * add implementation for dequantization with dynamic symbolic * fix ladder transform related issues. * improve ladder permutation for dequantization * enhance dynamic symbolic for matmul_impl * improve support for dynamic symbolic * update tvm dependency * implement operator cache. * refactor print to logging * append setup.py and remove tvm pythonpath dependency. * update ignore * improve installation scripts * update scaling benchmark of 1bit * int8xint1 lop3 support. * replace with to_torch_func * license related fix * update contributing.md * autogptq support. * refactor docs * refactor * refactor docs * typo fix --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.