Add aten.unflatten.int op
Add its torch-to-tosa lowering
Update the TorchToTosa/basic.mlir tests
To test e2e tosa lowering:
`python -m e2e_testing.main -v -c=tosa`
---------
Co-authored-by: Ze Zhang <ze.zhang@getcruise.com>
Add linspace/cumprod/roll ops to ODS and add shape inference functions
to make it work with LTC.
Also, add some tensor utils to LTC library for searching for non-detach
copy nodes.
Set PyTorch and TorchVision version to nightly release 2023-09-28.
aten.baddbmm changes done because upstream PyTorch has now added
support for fp16 gemm on CPU.
Refer: 9399e0b1ff
Set PyTorch and TorchVision version to nightly release 2023-09-26.
aten._convolution.deprecated changes done because upstream PyTorch has
now added support for fp16 native convolution on CPU.
Refer: 7c9052165a
Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
Making the same PR with #2457, as I accidentally thought the review was already made and merged it (reverted).
Add decompose empty_strided op.
Referring to #1776, this decomposition op only supports default stride values, because accessing the tensor or indexing over that, the indices are determined by the strides.
In MLIR, this is not implicitly supported but assumes that the strides are default while iterating over the tensor.
* view_as_real test case, allow dtype in testutils.randn
* abstract python upstream func implemented
* fixed upstream dtype func, implemented view_as_real backend op
* formatted AtenViewAsRealOp, removed change in e2etest/framework
* removed test suit from reshape_like.py, because it's moved to basic.py
* implemented C-API wrapper for mlirComplexF128 type
* fixed torch.complex dtype width in MLIR and Torch MLIR, deleted float16 dtype dict
* Changed IR input of aten fft_fft unit test
* code refactored
* code refactored and fixed ci test
* refactored: removed white spaces, and rolled back to having both input/output affine expr
* refactored: deleted output affine expr to reduce redundancy
* xfail ltc backend
* removed ComplexImag and ComplexReal from torchdynamo xfail set
* copied and pasted from main branch as there's no change to be made in this file
* refactored abstract_interp_lib_gen.py
* refactored: torchtypes.td, formatted, removed commented out code
* Tensor[]? support operands type support using partial codegen
* aten.index.Tensor support via partial codegen
* Add torch.index_put tracing support
* Added optional tensor list type support for LTC/TorchMLIR lowering
* Added comments
Co-authored-by: Gleb Kazantaev <gleb.kazantaev@cerebras.net>
* LTC/TorchMLIR multi-output operations support
* Update torch-mlir jit lowering to support ops with dynamic number of outputs
* Added support for aten::split_copy, aten::split_with_sizes_copy
* Fix native function for aten::split; cleanup code
* Fix TorchMlirTensorList lowering
* Remove xfails
When using custom ops, sometimes PyTorch will insert namespaces to the
abstract interpretation function name in the format:
`__torch__.{namespace_1}.{namespace_2}...{op_name}`. The extra
namespaces are not part of the abstract interpretation function name,
so it needs to be removed before generating the library of MLIR
snippets of abstract interpretation functions. This commit adds
support for removing the namespace information.
* [MLIR][TORCH] Fix aten.cumsum lowering for int32 input (#2351)
Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
[Stablehlo] Add converter to stablehlo for aten.(Int,Float,Bool).Tensor op (#2340)
[Stablehlo] Add converter to stablehlo for aten.(Int,Float,Bool).Tensor op and configure crashing e2e sets for stablehlo backend.
update PyTorch version to 2.1.0.dev20230729 (#2354)
- torch version: 2.1.0.dev20230729
- torch commit hash: b638df0afb83572724032c824c64e481bb4499a0
- torchvision version: 0.16.0.dev20230729
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
update PyTorch version to 2.1.0.dev20230730 (#2356)
- torch version: 2.1.0.dev20230730
- torch commit hash: 0ff243ff350268cc98fe03fa6364375ee2824742
- torchvision version: 0.16.0.dev20230730
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
update PyTorch version to 2.1.0.dev20230731 (#2359)
- torch version: 2.1.0.dev20230731
- torch commit hash: 6298ac688f8caafe30d71ff2ea2e20fbb32065c7
- torchvision version: 0.16.0.dev20230731
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
LTC->MLIR Debug Info support (#1922)
* LTC->MLIR Debug Info support
* SW-95317 Propagate Lazy->Jit->MLIR scope name.
* Enhance location information based on op names
Currently, the location information attached to the ops just considers
the filename, line number and column number. Attaching operation name
would help identify the type of computation by just looking at the
profile of execution.
* Update locations logic; updated debug-info.py test
* Use {scope}/{op_name} format to track names by default
---------
Co-authored-by: Gleb Kazantaev <gleb.kazantaev@cerebras.net>
Co-authored-by: Mark Browning <mark@cerebras.net>
Co-authored-by: Vimal Patel <vimal@polymagelabs.com>
build: update llvm tag to 41895843
Summary of changes:
- Update tags
llvm: 41895843b5915bb78e9d02aa711fa10f7174db43
mhlo: 4726d31f7025da66de0dea709bd56c462edb83c2
Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
update PyTorch version to 2.1.0.dev20230802 (#2366)
- torch version: 2.1.0.dev20230802
- torch commit hash: c89b16917755c2abbef7b6420e340baf9ae8089e
- torchvision version: 0.16.0.dev20230802
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
Change Python version from 3.10 to 3.11 in installation instructions (#2370)
Add CITATION file (#2371)
Add packaging as an install dependency (#2369)
Needed by `torch_mlir._version`. Resolves#2368.
[Torch Dialect] emit aten.masked_scatter and aten.masked_scatter_ op (#2358)
* [Torch Dialect] emit aten.masked_scatter and aten.masked_scatter_ op
update PyTorch version to 2.1.0.dev20230803 (#2372)
- torch version: 2.1.0.dev20230803
- torch commit hash: f89c73be3a3e8274d025ac46a33a780853841c9e
- torchvision version: 0.16.0.dev20230803
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
Prevent failed stable CI job from cancelling nightly jobs (#2373)
The CI jobs that use stable PyTorch are currently not required to pass
in order for a patch to get merged in `main`. This commit makes sure
that if a CI job for stable PyTorch fails, it does not cancel the
other required jobs.
[Torch Dialect] emit aten.tile op and decompose it into aten.repeat (#2355)
update
update xfail sets
update xfail_sets
update
fix xfail_sets
update:
update
update:
update
parent 22e88d523b1970b2e904eb5421d49d987a3d255e
author jianzhe.xiao <jianzhe.xiao@bytedance.com> 1691114110 +0800
committer jianzhe.xiao <jianzhe.xiao@bytedance.com> 1691114119 +0800
[Stablehlo] Add converter to stablehlo for aten.(Int,Float,Bool).Tensor op (#2340)
[Stablehlo] Add converter to stablehlo for aten.(Int,Float,Bool).Tensor op and configure crashing e2e sets for stablehlo backend.
update PyTorch version to 2.1.0.dev20230729 (#2354)
- torch version: 2.1.0.dev20230729
- torch commit hash: b638df0afb83572724032c824c64e481bb4499a0
- torchvision version: 0.16.0.dev20230729
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
update PyTorch version to 2.1.0.dev20230730 (#2356)
- torch version: 2.1.0.dev20230730
- torch commit hash: 0ff243ff350268cc98fe03fa6364375ee2824742
- torchvision version: 0.16.0.dev20230730
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
update PyTorch version to 2.1.0.dev20230731 (#2359)
- torch version: 2.1.0.dev20230731
- torch commit hash: 6298ac688f8caafe30d71ff2ea2e20fbb32065c7
- torchvision version: 0.16.0.dev20230731
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
LTC->MLIR Debug Info support (#1922)
* LTC->MLIR Debug Info support
* SW-95317 Propagate Lazy->Jit->MLIR scope name.
* Enhance location information based on op names
Currently, the location information attached to the ops just considers
the filename, line number and column number. Attaching operation name
would help identify the type of computation by just looking at the
profile of execution.
* Update locations logic; updated debug-info.py test
* Use {scope}/{op_name} format to track names by default
---------
Co-authored-by: Gleb Kazantaev <gleb.kazantaev@cerebras.net>
Co-authored-by: Mark Browning <mark@cerebras.net>
Co-authored-by: Vimal Patel <vimal@polymagelabs.com>
build: update llvm tag to 41895843
Summary of changes:
- Update tags
llvm: 41895843b5915bb78e9d02aa711fa10f7174db43
mhlo: 4726d31f7025da66de0dea709bd56c462edb83c2
Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
update PyTorch version to 2.1.0.dev20230802 (#2366)
- torch version: 2.1.0.dev20230802
- torch commit hash: c89b16917755c2abbef7b6420e340baf9ae8089e
- torchvision version: 0.16.0.dev20230802
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
Change Python version from 3.10 to 3.11 in installation instructions (#2370)
Add CITATION file (#2371)
Add packaging as an install dependency (#2369)
Needed by `torch_mlir._version`. Resolves#2368.
[Torch Dialect] emit aten.masked_scatter and aten.masked_scatter_ op (#2358)
* [Torch Dialect] emit aten.masked_scatter and aten.masked_scatter_ op
update PyTorch version to 2.1.0.dev20230803 (#2372)
- torch version: 2.1.0.dev20230803
- torch commit hash: f89c73be3a3e8274d025ac46a33a780853841c9e
- torchvision version: 0.16.0.dev20230803
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
Prevent failed stable CI job from cancelling nightly jobs (#2373)
The CI jobs that use stable PyTorch are currently not required to pass
in order for a patch to get merged in `main`. This commit makes sure
that if a CI job for stable PyTorch fails, it does not cancel the
other required jobs.
[Torch Dialect] emit aten.tile op and decompose it into aten.repeat (#2355)
update
update xfail sets
update xfail_sets
update
fix xfail_sets
update:
update
update:
add support for adaptive_pool_id
update xfail sets
update xfail_sets
update
fix xfail_sets
update:
update:
* update
---------
Co-authored-by: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
* LTC->MLIR Debug Info support
* SW-95317 Propagate Lazy->Jit->MLIR scope name.
* Enhance location information based on op names
Currently, the location information attached to the ops just considers
the filename, line number and column number. Attaching operation name
would help identify the type of computation by just looking at the
profile of execution.
* Update locations logic; updated debug-info.py test
* Use {scope}/{op_name} format to track names by default
---------
Co-authored-by: Gleb Kazantaev <gleb.kazantaev@cerebras.net>
Co-authored-by: Mark Browning <mark@cerebras.net>
Co-authored-by: Vimal Patel <vimal@polymagelabs.com>
In PyTorch, the `NumberType` is equal to `Union[int, float,
complex]`. However, the abstract interpretation library was treating
the `NumberType` as `Union[int, float]`, resulting in type mismatches
when reifying certain dtype functions. This commit fixes the type
inconsistency by having the abstract interpretation functions take as
an input a `Union[int, float, complex]` for the ops that take
`!torch.number` inputs.
Single element tuples in Python need a comma after the
element. However, the `registry.py` file, which generates the expected
abstract interpretation function signatures, was not inserting the
comma. This commit changes the expected signature generator to add a
comma after the last element in any non-empty default tuple argument.
* add support for mhlo
* Add Test for torch.ne
* fix torch.ne shape/add static test case
* add support for static torch.ne
---------
Co-authored-by: root <root@n31-177-039.byted.org>
* feat: split pytorch requirements into stable and nightly
* fix: add true to tests to see full output
* refactor: add comments to explain true statement
* feat: move some tests to experimental mode
* refactor: refactor pipeline into more fine grained difference
* feat: add version differentiation for some tests
* feat: activate more configs
* refactor: change implementation to use less requirement files
* refactor: remove contraints used for testing
* fix: revert some requirement file names
* refactor: remove unnecessary ninja install
* fix: fix version parsing
* refactor: remove dependency on torchvision in main requirements file
* refactor: remove index url
* style: remove unnecesary line switch
* fix: readd index url
This commit adds dtype functions for all the torch ops that did not
previously have one and removes the pass `RefineTypes`, since the
abstract interpretation library now takes care of all the dtype
propagation.
All dtype functions added are tested except for
- `aten.embedding`
- `aten._embedding_bag`
- `aten.embedding_bag`
These functions need a change to the testing framework to allow
specifying the actual data inside the tensor used for testing. I will
fix this in a follow up patch.
Co-authored-by: Jiahao Li <liplus17@163.com>
Bool tensors are represented in TorchScript as an array of
`int8_t`s. However, when importing them into Torch-MLIR, the importer
was assuming the array had `int32_t` elements, leading to the importer
reading into memory that was out of bounds. This commit fixes the
casting of the bool tensor.
-- This commit adds e2e support for atend.sort op.
-- 1. Adds aten.sort op in torch dialect.
-- 2. Adds tm_tensor.sort op in TMTensor dialect.
-- 3. Adds lowering of aten.sort -> tm_tensor.sort.
Signed-off-by: Abhishek Varma <abhishek@nod-labs.com>
Ze Zhang
Jae Hoon (Antonio) Kim
Vivek Khandelwal
saienduri
Gleb Kazantaev
David Gens
Bruce Kim
Ramiro Leal-Cavazos
Arham Khan
Yuanqiang Liu
Jiawei Wu
Stella Laurenzo
Jerin Philip
Quinn Dawkins
JianzheXiao
Zhekun(Josh) Zhang
max
Matthias Gehre
nithinsubbiah
Jiawei Wu
Abhishek Varma
JianzheXiao
maxbartel
Gaurav Shukla
Prateek Gupta
gpetters94
Prashant Kumar
rahul shrivastava
Abhishek Varma