[CODEGEN] Add LoweredFunc, MakeAPI to build a C API function #23
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icemelon
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* override all the stuff * fix.
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…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>
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…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>
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…pache#23) * Test initialization * Fix a stupid bug of ReprPrinter * Add SparseBlockRV * Schedule: GetSparseBlock * Schedule: Reorder
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…pache#23) * Test initialization * Fix a stupid bug of ReprPrinter * Add SparseBlockRV * Schedule: GetSparseBlock * Schedule: Reorder
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…pache#23) * Test initialization * Fix a stupid bug of ReprPrinter * Add SparseBlockRV * Schedule: GetSparseBlock * Schedule: Reorder
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* call_dps lowering. * Improve shape lowering. * Support alloc_storage for dynamic shape. * implementt ToNonDF to transform program to non-dataflow format. * Fix the mutator issue. * Update build api, an issue occurred. * vm tests can pass. * Support shape tuple in executable seriablization. * Fix for test. * Minor fixes. * Address comments. * Add mutate binding var back. * Visit binding var and fix tests. Co-authored-by: YuchenJin <yuchenj@cs.washington.edu>
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* call_dps lowering. * Improve shape lowering. * Support alloc_storage for dynamic shape. * implementt ToNonDF to transform program to non-dataflow format. * Fix the mutator issue. * Update build api, an issue occurred. * vm tests can pass. * Support shape tuple in executable seriablization. * Fix for test. * Minor fixes. * Address comments. * Add mutate binding var back. * Visit binding var and fix tests. Co-authored-by: YuchenJin <yuchenj@cs.washington.edu>
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[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
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rebased [TIR][Schedule] fix reorder/buffer_flatten & finish CPU demo (apache#59) [CPU DEMO] Update cpu gemm demo and fix bug (apache#58) * [TIR][Schedule] introduce parallel and fix bugs for cpu demo * [TIR][Schedule] update cpu demo * [TIR][Schedule] fix lint * [TIR][Schedule] fix rebased [TIR][Schedule] introduce reduction block and CPU demo (apache#53) * [TIR] reduction : split_reduction * [TIR] reduction : split_reduction * [TIR] reduction : fuse_reduction * [TIR] reduction : cpu demo * [TIR] reduction : fix * [TIR] reduction : pattern detect remains * [TIR] reduction : pattern detect remains * [TIR] reduction : pattern match done * [TIR] reduction : fix lint * [TIR] reduction : fix * [TIR] reduction : fix * [TIR] reduction : fix * [TIR] reduction : fix * [TIR] reduction : rebased * [TIR] reduction : rebased [TIR][Schedule] introduce cache_read cache_write (apache#54) * [TIR][Schedule] introduce cache_read cache_write * [TIR][Schedule] add more comments * [TIR][Schedule] fix problem and add comments * [TIR][Schedule] address comments [TIR] schedule: introduce vectorize, unroll, loop validation (apache#47) * [TIR] vectorize : basically complete * [TIR] vectorize&unroll : update comments&unroll * [TIR] vectorize&unroll : rebased * [TIR] vectorize, unroll, cpu_demo: done * [TIR] vectorize, unroll, cpu_demo: simplify * [TIR] vectorize, unroll, cpu_demo: fix * [TIR] reduction : rebased * [TIR] reduction : fix [TIR][Schedule] fix sref and scopes problem during replace and compute_at (apache#50) * [TIR][Schedule] fix sref and scopes problem during replace and compute_at * [TIR][Schedule] fix * [TIR][Schedule] fix [TIR][Refactor] move function to ScheduleNode [TIR] Schedule: introduce primitive compute_at (apache#36) * [TIR] Schedule: introduce primitive compute_at * [TIR] Schedule: address comments * [TIR] Schedule: address comments * [TIR] Schedule: address comments * [TIR] Schedule: add check to compute_at * [TIR] Schedule: address comments * [TIR] Schedule: address comments [TIR] Schedule: introduce primitive reorder (apache#37) * [Schedule] debug * [TIR] Schedule: reorder, loop type detect remains * [TIR] reorder complete * [TIR] reorder complete * [TIR] fix * [TIR] reorder : rebased complete * [TIR] reorder : fix container.h * [TIR] reorder : fix * [TIR] reorder : fix * [TIR] reorder : fix * [TIR] reorder : simplify * [TIR] reorder : simplify * [TIR] reorder : simplify * [TIR] reorder : fix * [TIR] reorder : fix * [TIR] reorder : rebased * [TIR] reorder : rebased rebase [TIR] Schedule: introduce BlockRealize and Block SRef reuse(apache#39) * [TIR] BlockRealize: schedule refactor * [TIR] BlockRealize: debug * [TIR] BlockRealize finish * [TIR] BlockRealize finish * [TIR] BlockRealize fix * [TIR] BlockRealize update test * [TIR] BlockRealize: add loop var reuse * [TIR] BlockRealize: add loop var reuse * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix * [TIR] BlockRealize: fix [TIR] compare for module (apache#38) * [TIR] compare for module * [TIR] fix * [TIR] fix * [TIR] fix * [TIR] fix * [TIR] fix * [TIR] fix [Hybrid] Module init [Hybrid] Module print [Hybrid] Module print with meta [Hybrid] adjust [Hybrid] finished but without lint and comment check [Hybrid] fix lint [Hybrid] comments [Hybrid] fix script decoration API [Hybrid] using IRModule [Hybrid] fix [Hybrid] adjust API [Hybrid] fix [Hybrid] fix [Hybrid] fix [Hybrid] fix symbol table, adjust API, introduce meta_mutator and resolve import issue [Hybrid] fix lint [TIR] introduce pass BufferFlatten (apache#32) * [TIR] introduce pass BufferFlatten * [Tir] add comments & remove old TeLower * [TIR] split GatherRegion and BufferFlatten to two Visitor/Mutator * [TIR] address comments: Only consider stmt scope * [TIR] BufferFlatten: address comments * [TIR] BufferFlatten: fold BlockFlattener into BufferFlattener * [TIR] BufferFlatten: add asserts * [TIR] BufferFlatten: use Equal in testcase * [TIR] Equal Pass: Enhanced the pass * [TIR] Equal Pass: add comments [Hybrid] refactor using Doc, introduce annotation, enhance parser (apache#28) * [Hybrid] refactor printer, enhance parser * [Hybrid] refactor * [Hybrid] fix * [Hybrid] fix * [Hybrid] fix namespace issue * [Hybrid] compare using Equal [TIR] rebased [TE] fix replace again and add primitive fuse and split (apache#27) * [TE] add: schedule primitive fuse * [TE] add: schedule primitive split * [TE] address comments: add IRSubstitueInScope and other minor fix * [TE] address comments: Enhance Equal api and fix split by nparts * [TE] address comments [Hybrid] introduce printer (apache#25) * [Hybrid] substitute Block with SeqStmt, change block() syntax * [Hybrid] add printer, type declare intrin * [Hybrid] refactor * [Hybrid] meta * [Hybrid] refactor * [Hybrid] macro [TE] fix replace (apache#23) * [TE] fix replace * [TE] fix replace: add more tests * [TE] fix replace: add more tests [TE] rebased [Hybrid] python syntax parser (apache#20) * [Hybrid] python syntax parser * [Hybrid] add a testcase * [Hybrid] improve comments and fix bugs * [Hybrid] improve comments, refactor __internal_assert, add new testcases * [Hybrid] improve error report message, refactor intrin * [Hybrid] separate ScopeEmitter from parser * [Hybrid] refactor type check * [Hybrid] refactor intrin * [Hybrid] refactor intrin, allow register external functions with argument type checking, add a testcase * [Hybrid] address comments, fix a bug in te/ir.h * [Hybrid] remove type check * [Hybrid] python syntax parser * [Hybrid] add a testcase * [Hybrid] improve comments and fix bugs * [Hybrid] improve comments, refactor __internal_assert, add new testcases * [Hybrid] improve error report message, refactor intrin * [Hybrid] separate ScopeEmitter from parser * [Hybrid] refactor type check * [Hybrid] refactor intrin * [Hybrid] refactor intrin, allow register external functions with argument type checking, add a testcase * [Hybrid] address comments, fix a bug in te/ir.h * [Hybrid] remove type check * [Hybrid] refactor intrin, scope_handler, special_stmt * [Hybrid] address comments * [Hybrid] clean code, improve error reporting & testcase * [Hybrid] clean code * [Hybrid] clean code [IR] introduce dependency graph and write map [TE] refactor and clean codebase [TE] refactor IR [TE] introduce schedule, dependency graph and support fuse and split (apache#17) * fix lint * introduce dependency graph * enable create schedule * support get axes * fix lint * revert Set * add schedule primitive fuse * address comment * support split [IR] Introduce SeqStmt add TeLower pass and enable to run Te IR (apache#15) * add function data structure add TeLower pass to transform Te to current IR enable to run Te IR * address comments * unify terminology TensorIR data structure init (apache#14) * init te data structure * finish printer and enhanced ir_builder * address the comments Co-authored-by: Bohan Hou <32121147+spectrometerHBH@users.noreply.github.com>
jinhongyii
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Jun 20, 2022
* call_dps lowering. * Improve shape lowering. * Support alloc_storage for dynamic shape. * implementt ToNonDF to transform program to non-dataflow format. * Fix the mutator issue. * Update build api, an issue occurred. * vm tests can pass. * Support shape tuple in executable seriablization. * Fix for test. * Minor fixes. * Address comments. * Add mutate binding var back. * Visit binding var and fix tests. Co-authored-by: YuchenJin <yuchenj@cs.washington.edu>
Hzfengsy
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Jul 30, 2022
* call_dps lowering. * Improve shape lowering. * Support alloc_storage for dynamic shape. * implementt ToNonDF to transform program to non-dataflow format. * Fix the mutator issue. * Update build api, an issue occurred. * vm tests can pass. * Support shape tuple in executable seriablization. * Fix for test. * Minor fixes. * Address comments. * Add mutate binding var back. * Visit binding var and fix tests. Co-authored-by: YuchenJin <yuchenj@cs.washington.edu>
areusch
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Sep 20, 2022
* call_dps lowering. * Improve shape lowering. * Support alloc_storage for dynamic shape. * implementt ToNonDF to transform program to non-dataflow format. * Fix the mutator issue. * Update build api, an issue occurred. * vm tests can pass. * Support shape tuple in executable seriablization. * Fix for test. * Minor fixes. * Address comments. * Add mutate binding var back. * Visit binding var and fix tests. Co-authored-by: YuchenJin <yuchenj@cs.washington.edu>
gigiblender
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Nov 3, 2022
* call_dps lowering. * Improve shape lowering. * Support alloc_storage for dynamic shape. * implementt ToNonDF to transform program to non-dataflow format. * Fix the mutator issue. * Update build api, an issue occurred. * vm tests can pass. * Support shape tuple in executable seriablization. * Fix for test. * Minor fixes. * Address comments. * Add mutate binding var back. * Visit binding var and fix tests. Co-authored-by: YuchenJin <yuchenj@cs.washington.edu>
MasterJH5574
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Nov 20, 2022
* call_dps lowering. * Improve shape lowering. * Support alloc_storage for dynamic shape. * implementt ToNonDF to transform program to non-dataflow format. * Fix the mutator issue. * Update build api, an issue occurred. * vm tests can pass. * Support shape tuple in executable seriablization. * Fix for test. * Minor fixes. * Address comments. * Add mutate binding var back. * Visit binding var and fix tests. Co-authored-by: YuchenJin <yuchenj@cs.washington.edu>
jinhongyii
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Nov 28, 2022
* [BugFix] Normalize in mutator when visiting VarBinding and MatchShape * Graph memory planning * Fixes * Translate memory op to vm builtin op * Naive test * Fix importer, use no `iterable`
yelite
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Feb 17, 2023
* call_dps lowering. * Improve shape lowering. * Support alloc_storage for dynamic shape. * implementt ToNonDF to transform program to non-dataflow format. * Fix the mutator issue. * Update build api, an issue occurred. * vm tests can pass. * Support shape tuple in executable seriablization. * Fix for test. * Minor fixes. * Address comments. * Add mutate binding var back. * Visit binding var and fix tests. Co-authored-by: YuchenJin <yuchenj@cs.washington.edu>
vinx13
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Mar 27, 2023
…dels (apache#23) * Add a batch of new operators to support new high priority models. * Drop import. * Some cleanup. * Switched as much as possible to relax opset.
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…cks.