* Update to support LLVM as of 7dcd0042
Fixes for upstream changes to mlir.
- New pass registration method from https://reviews.llvm.org/D85622
- Integer attributes are now C types when possible https://reviews.llvm.org/D86739
Signed-off-by: Nathaniel McVicar <namcvica@microsoft.com>
* Fix for checkclang
* Windows incremental build fix from @max-ku
* Remove MLIRShapeToSCF lib
* Missed a getSExtValue on now c type
* Rebuild prereq docker.
* Bump CircleCI cache version.
* Update hash for Windows build
Signed-off-by: Nathaniel McVicar <namcvica@microsoft.com>
* Bump CircieCI cache version again.
* Rebuild prereq docker.
* Update README.md
* Update README.md
* Undo edits to ONNXOps.td.inc.
* Undo changes to ONNXOps.td.inc.
* Fix cast op TableGen.
* Tweak tablegen definition of Cast.
* Use explicitly signed integer as attributes.
* Move all signless attribute to explicitly signed attribute.
* Import ONNX int attribute as SI64 attribute.
* Make Conv.group attr use SI64 attr.
* Fix conv test.
* Fix DocCheck complaint.
Co-authored-by: Tian Jin <tjingrant@gmail.com>
* Add shape inference and names
- Add shape inference for PRelu
- Fix shape inference for group conv
for ConvTranspose
- Add input and output names for
graphs (functions)
- Add support for (u)int8 tensor
attributes
* Fix format issues
* Revert formatting for gen_onnx_mlir.py
* Pads can have ArrayAttr and DenseElementsAttr so support both
* NumInputs is the number of graph inputs that don't have initializers
* Add test for 2D batchnorm
* Fix typo in define_loops in new 2d BN test
* Change 'name' to 'onnx_node_name'
* Fix Batchnorm for 2D I/O and add lowering test
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
* move scalerop to decompose
* change clang format
* change clang format
* add shape inference for scaler op
* fixing generated onnxop
* generate onnx.md
* redo get onnx.md and onnxop.td.inc using onnx 1.6
* Add shape inference for scaler op
* add benefit for scaler decompose and simplify scaler shape inference
* add scaler decompose benefit num and simplify shape inference
* add cast builder
* cast rewrite only for float
* add cast op same type rewrite rule
* working on cast lowering
* cast lowering working
* add cast lowering
* fix format
* Delete OpBuildTable.inc
* complete requested changes
Co-authored-by: chentong319 <chentong@us.ibm.com>
* Add shape inference for Ops used by BERT
* Erf
* Pow
* ReduceMean
* Dropout
* Expand
https://github.com/onnx/onnx/blob/master/docs/Operators.md#expand
Deduce the value of the shape operand by looking at the producer
of the operand.
Currently supported producers are: onnx.Constant and onnx.Shape.
* Add corresponding tests for each op.
* Sort the list of ops with shape inference in gen_onnx_mlir.py
in alphabetic order for clarity.
* Restart CI
Co-authored-by: Tian Jin <tjingrant@gmail.com>
* move scalerop to decompose
* change clang format
* change clang format
* add shape inference for scaler op
* fixing generated onnxop
* generate onnx.md
* Add shape inference for scaler op
* add benefit for scaler decompose and simplify scaler shape inference
* Lower Squeeze op to Krnl dialect
* Emit tensor size as a single constant; add a lit test for unknown dimensions
* Code style
* Speical case where the input is only used by this squeeze op
* Remove squeeze-in-place optimization
* Update ConvertONNXToKrnl.cpp
Twek to re-run tests.
* Trigger buildbot re-run.
* Re-run CI
Co-authored-by: Tian Jin <tjingrant@gmail.com>
* string type from tensorflow
* simplify type
* parser and print
* gen StringType for tablegen
* onnx to onnx-mlir type
* add namespace
* allow all integer type
* dialect document
* add test case
* format
* more precise type for ONNXOp
* format
* enable the failed test
* update comment
* update onnx.md
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
* 1. Add shape inference for the following ops:
- Atan
- Tan
- Sin
- Cast
- ConvTranspose
- Flatten
- DynamicQuantizeLinear
- QuantizeLinear
- DequantizeLinear
- ConvInteger
2. Import attributes for generic nodes
3. Fixes for cases where .cast<> should be .isa<> (ONNXConcat::inferShapes)
* Fix foormatting issues
* Address comments:
- SmallVector<> * -> SmallVectorImpl<> &
- switch-case -> helper function
- Inside helper function, preserve signed-ness
- add TODOs
* Can't use signed integers yet in convertONNXTypeToMLIRType, add TODO
Co-authored-by: Tian Jin <tjingrant@gmail.com>
* enable promote attr for pad
* use optional arguments for pad
* shape infereance for pad
* Lowering Pad
* format file
* use DenseTensor for the attribute
* use Pad in ONNXRewrite
* fix the merge conflict
* fix the attr given to constantOp
* handle ONNXConstantOp in attribute promotion
* Fix bug when AttributePromotion is called more than once
* update ONNXOps.td.inc with correct version of onnx
* update onnx.md
* responses to review
* fix the build error
* change the implementation of Pad
* delete commented out code
* clang format
Co-authored-by: Tian Jin <tjingrant@gmail.com>
* Support dilations and enable e2e tests
* Fix allocating memory for dynamic shape
* Edit comments
* Do dilation by computing an offset from kernel index
* Correct dilation formula, add an example of out-of-bound, and add a test for dilation
* Import optional outputs as NoneType
* Shape inference for ONNXLSTM
* Edit ONNXLSTM::inferShape()
* Shape inference for ONNXLSTMOp
* Create a common function for inferring shape for RNN ops
* CheckInsertDeallocation for a specific result
* Allocate memory for LSTM
* First round of lowering
* Allocate memory for hidden and cell states
* Test with custom Tanh
* Fix an error in Ct's formula
* Add E2E tests
* Return outputs
* Refactor the code
* Enable E2E tests
* Support reverse and bidirectional directions
* Minor revision
* Return all intermediate hidden states
* Call existing activation functions
* Structs for activation functions
* Call existing activations in ONNX
* Minor revision
* Compare strings ignoring case
* Use memreftype of rank 0 for calling activation functions
* Fix getActivationPack()
* Revise the code
* Add one MLIR test
* Add MLIR tests for reverse and bidirectional modes
* Make the order of emiting instructions deterministic
* Use OperandAdaptor instead of directly use an operand index
* Use literal assignments
* Change some variable names
* Use literal assignments
* Use literal assignments
* Format the code
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
* Implement shape inference for SplitOp
* Change spitOpt to SplitAttribute and check the axis range before updating the axis attribute
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
* implement shape inference for concat
* better checking of axis being concatenated: constant values only
* lowering of Concat with lit and backend tests
* fixes
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
* Fix reshape when a dynamic shape is given.
* Fix default attributes for ConvNoBias.
* Fix comment.
* Resolve comment.
* Improve checks.
* Handle zero dim case.
* Add helper to fetch constants. Add test for dynamic reshape.
* Add test for zero.
* Use shortcut method for size.
* add attributes of Op into parameters
* fix rewrite rule for GemmOp with attributes
* use I64Attr instead of I32Attr and modify test cases for the changes in attributes
* add output name (prefixed with o_) to Op definition
* update shape inference for the new attributes
NathanielMcVicar
chentong319
Aman LaChapelle
Anh Leu
albertomagni-ms
Tung D. Le
Alexandre Eichenberger
Gheorghe-Teodor Bercea
Gheorghe-Teodor Bercea