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[LANG] Introduce Scan, bugfix Canonical #43

Merged
merged 1 commit into from
Feb 14, 2017
Merged

[LANG] Introduce Scan, bugfix Canonical #43

merged 1 commit into from
Feb 14, 2017

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tqchen
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@tqchen tqchen commented Feb 13, 2017

Introduce the scan operator

The following code compute the cumsum of X

def my_cumsum():
   m = tvm.Var("m")
    n = tvm.Var("n")
    t = tvm.IterVar((1, m), name="t")
    X = tvm.placeholder((m, n), name="X")
    s_state = tvm.placeholder((m, n))
    s_init = tvm.compute((1, n), lambda _, i: X[0, i])
    s_update = tvm.compute((n,), lambda i: s_state[t-1, i] + X[t, i])
    res = tvm.scan(t, s_init, s_update, s_state)

Known Limitations to be Improved

  • There is no checking yet on the scan reference to state, should always ensure only refer to previous timestamp
  • Do not yet allow subslice result of scan, need to add fix point detection to allow subslice axis that are simple(only refers to itself during recursion)

Bug Fix in Canonical

Previously did not multiple constant by -1 during sub, making m-1 to m+1, added a regression test.

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lgtm

@tqchen tqchen merged commit 820a859 into master Feb 14, 2017
@tqchen tqchen mentioned this pull request Feb 24, 2017
4 tasks
tqchen pushed a commit to tqchen/tvm that referenced this pull request May 26, 2018
* ApplyPass -> ApplyPasses; Refactored infer pass;

* lint fix
tqchen added a commit to tqchen/tvm that referenced this pull request May 26, 2018
tqchen pushed a commit that referenced this pull request May 29, 2018
* ApplyPass -> ApplyPasses; Refactored infer pass;

* lint fix
tqchen added a commit that referenced this pull request May 29, 2018
tqchen pushed a commit to tqchen/tvm that referenced this pull request Jul 6, 2018
* ApplyPass -> ApplyPasses; Refactored infer pass;

* lint fix
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
* ApplyPass -> ApplyPasses; Refactored infer pass;

* lint fix
sergei-mironov pushed a commit to sergei-mironov/tvm that referenced this pull request Aug 8, 2018
wjj19950828 pushed a commit to wjj19950828/tvm that referenced this pull request Sep 22, 2021
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
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2 participants