Commit Graph

254 Commits (82af44da2fbc701eddbcde4116259460bf483dd6)

Author SHA1 Message Date
Sean Silva 2af53ce434 torch_mlir.compile: Add OutputType.RAW
This can help with development and reporting bugs.
2022-05-19 03:41:43 -07:00
Sean Silva ef9e4c95f2 torch_mlir.compile: add support for dynamic sizes.
We do this by inroducing a TensorPlaceholder class, which can be used to
specify dynamic sizes. Internally, we canonicalize all example inputs
to TensorPlaceholder's.

This commit also adds some basic testing, which was missing before.
2022-05-17 07:02:32 -07:00
Ashay Rane bb52a460cb
mlir: bump llvm tag to 5380e3 (#856)
In addition to updating the llvm-project submodule, this patch also:

1. updates shape functions and tests so that `func` and `call`
   operations refer to the `func` dialect
2. avoid duplicate registration of dialects
2022-05-16 12:54:35 -07:00
Ramiro Leal-Cavazos 96f90efd16
Add shape info to `rand_like` + support for `dtype` flag (#851)
The op `aten.rand_like` was missing a shape function, unit tests, and
the `dtype` argument was being ignored in its decomposition. This
commit fixes all three things.
2022-05-12 16:00:59 -07:00
Vivek Khandelwal c69a1e5688 [MLIR][TORCH] Add E2E support for ScalarImplicit, Int.Scalar op
This commit adds lowering of `aten.ScalarImplicit` and `aten.Int.Scalar` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-05-10 22:40:49 +05:30
Prashant Kumar 12b3af70d3 [TORCH] Add folding of aten.detach op.
`aten.detach` op is folded and returns the first operand since it's an
identity function(kind of identity just remove the has_grad attribute).
2022-05-10 21:54:45 +05:30
yuhao 2e6a9c084e Update torch_mlir_tensor.py
typo
2022-05-07 21:46:10 -04:00
Yi Zhang 28be6511d2 Fix type promotion code for scalar only operations
Fix the type promotion code for scalar only operation to return
TorchType which is the type tracked in ValueKnowledge.scalarType.

- Fix `getPromotedResultScalarType` to return Torch type.
- Add `getBuiltInTypeForTorchScalar` helper to convert scalar type
to builtin type before passing to the next level type promotion
helper `updateResultTypeState`.
- Add `setScalarType` helper to make setting ValueKnowledge.scalarType
  easier.
2022-05-07 10:37:21 -04:00
Vivek Khandelwal b20679e1b8 [MLIR][TORCH] Modify aten::dropout op description
Signed-Off By: Vivek Khandelwal vivek@nod-labs.com
2022-05-06 11:15:52 +05:30
Vivek Khandelwal 96fabc0036 [MLIR][TORCH] E2E support for [ge|ceil].float, [ge|ne|gt].float_int op
This commit adds lowering of `aten.ge.float`, `aten.ge.float_int`,
`aten.ne.float_int`, `aten.gt.float_int` and `aten.ceil.float` op.
This commit also fixes formatting for the file scalar.py and scalar_comparison.py.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-05-05 21:48:35 +05:30
Yi Zhang 9f7264a7a4 Add support for scalar type propagation
The main changes are:
- Added `ValueKnowledge.scalarType` to track scalar type information.
- Added `ValueKnowledge.kind` to indicate the value kind.
- Modified the meet and join helper functions. The ValueKnowledge has
slightly more complicated state now so the meet and join function need
to look at the `kind` field in addition to just the type field.
2022-05-04 16:57:56 -04:00
Sean Silva ab5ad7af09 Add tracing suport to `torch_mlir.compile`.
This also has a fix for the adjustment of types of TupleConstruct
inputs, which I found when using this new functionality on a model.

Some scenarios in tracing create situations where the output of
TupleConstruct has a more refined type than the inputs.

This introduces a helper `adjustStaticInformationForValues` which
subsumes the `derefineValues` helper and the tensor static information
adjustment we were doing.
2022-05-03 09:08:40 -07:00
Vivek Khandelwal c0634bc996 [MLIR][TORCH] Add E2E support for aten.to.dtype_layout op
This commit decomposes `aten.to.dtype_layout` op into `aten.to.dtype` op.
This commit also fixes the formatting for the file type_conversion.py.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-05-03 12:48:58 +05:30
gpetters94 c4dcdd1e34
Add aten.flip (#817) 2022-05-02 16:01:15 -04:00
Vivek Khandelwal 8a06419980 [MLIR][TORCH] Add E2E support for aten.masked_fill.Scalar op
This commit adds lowering of `aten.masked_fill.Scalar` op.
This commit also fixes the formatting of the file constant_alloc.py.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-05-02 22:27:33 +05:30
Vivek Khandelwal 4b11284440 [MLIR][TORCH] Add E2E support for aten.avg_pool2d op
This commit adds lowering of `aten.avg_pool2d` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-05-02 12:31:44 +05:30
Prateek Gupta 81ee5bb58c [TORCH][MLIR] Fix ConstantPad2dStaticModule test.
This commit fixes the `ConstantPad2dStaticModule` test case by adding
the lowering of `aten.pad` operation. Previously the test case
mapped to `aten.constant_pad_nd` operation.
The `aten.pad` now decomposes into `aten.constant_pad_nd` operation.

Signed-Off-By: Prateek Gupta <prateek@nod-labs.com>
2022-04-29 21:57:01 +05:30
Ashay Rane 809f240f01
importer: add initial support for loading BFloat16 tensors (#761)
This patch updates the `torch_mlir::convertTensorToMlirElementsAttr()`
method to enable the creation of tensors whose base type is BFloat16.
This patch also adds a test to validate the IR generation, and it
updates the test for importing tensors of various types.
2022-04-29 09:01:49 -07:00
Sean Silva 44c7b181d3 Revert "[MLIR][TORCH] Add E2E support for aten.ge.float op"
This reverts commit 564734b2d7.
2022-04-28 07:49:58 -07:00
Sean Silva eff144c0b7 Revert "[MLIR][TORCH] Add E2E support for aten.ge.float_int op"
This reverts commit 1f102cc400.
2022-04-28 07:49:58 -07:00
Sean Silva 7669ee4e4a Revert "[MLIR][TORCH] Add E2E support for aten.ne.float_int op"
This reverts commit 51dd462592.
2022-04-28 07:49:58 -07:00
Sean Silva 5ef9f501fa Revert "[MLIR][TORCH] Add E2E support for aten.ceil.float op"
This reverts commit 78f5747568.
2022-04-28 07:49:58 -07:00
Vivek Khandelwal e57e1968bc [MLIR][TORCH] Add E2E support for aten.index_put.hacked_twin op
This commit decomposes `aten.index_put.hacked_twin` op into
`valsem.aten.index_put_impl` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-04-28 13:41:47 +05:30
Vivek Khandelwal 78f5747568 [MLIR][TORCH] Add E2E support for aten.ceil.float op
This commit adds lowering of `aten.ceil.float` op.
This commit also fixes formatting for the file scalar.py.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-04-28 11:49:35 +05:30
Yi Zhang 86eb493a44 Change to AnyTorch* except for Torch_X ones 2022-04-27 14:18:52 -04:00
Bob Adolf 0667a5b3ae
Expand checks against PyTorch C++ ABI settings. (#777)
Compiling torch-mlir against a source version of PyTorch or an official
wheel compiled with the new C++ stdlib ABI fails, as torch-mlir doesn't
know how to set compiler flags to remain compatible. This changes the
way torch-mlir looks at PyTorch and tries to more closely match the ABI
settings, regardless of whether it's the common official wheel or some
other version.
2022-04-27 10:44:46 -07:00
Vivek Khandelwal 51dd462592 [MLIR][TORCH] Add E2E support for aten.ne.float_int op
This commit adds lowering of `aten.ne.float_int` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-04-27 21:16:48 +05:30
Vivek Khandelwal 1f102cc400 [MLIR][TORCH] Add E2E support for aten.ge.float_int op
This commit adds lowering of `aten.ge.float_int` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-04-27 21:16:48 +05:30
Vivek Khandelwal 564734b2d7 [MLIR][TORCH] Add E2E support for aten.ge.float op
This commit adds lowering of `aten.ge.float` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-04-27 21:16:48 +05:30
Vivek Khandelwal f5b6c4b601 [MLIR][TORCH] Add E2E support for aten.div.float op
This commit adds lowering of `aten.div.float` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-04-27 21:16:48 +05:30
Sean Silva 73cc2ac152 Ensure that imported function input type and block arg types are consistent.
I wasn't able to find exactly what frontend situation created it, but
`torch.jit.trace` will sometimes create functions where the
`jit::Block`'s param node has refined tensor types. So we need to adjust
the function's formal param types to those refined types.
2022-04-27 08:01:23 -07:00
Ashay Rane 9208bf0eb6
llvm: bump tag to e1318078 (#781)
The updated LLVM code includes a patch to create bfloat16 array
attributes, thus enabling a different patch to torch-mlir to flesh out
support for the bfloat16 type.
2022-04-26 12:27:51 -07:00
Maksim Levental 693f79a2b6
Fix test fails due to upstream PyTorch change (#793)
* Add to eager tests to xfail while they are fixed.

Also XFAIL ConstantPad2dStaticModule_basic.

* Fix test fails due to upstream PyTorch change.
2022-04-25 12:34:32 -07:00
powderluv cc3a4a58ef
Add oneshot release snapshot for test/ondemand (#768)
* Add oneshot release snapshot for test/ondemand

Add some build scripts to test new release flow based on IREE.
Wont affect current builds, once this works well we can plumb it
in.

Build with manylinux docker

* Fixes a few issues found when debugging powderluv's setup.

* It is optional to link against Python3_LIBRARIES. Check that and don't do it if they don't exist for this config.
* Clean and auditwheel need to operate on sanitized package names. So "torch_mlir" vs "torch-mlir".
* Adds a pyproject.toml file that pins the build dependencies needed to detect both Torch and Python (the MLIR Python build was failing to detect because Numpy wasn't in the pip venv).
* Commented out auditwheel: These wheels are not PyPi compliant since they weak link to libtorch at runtime. However, they should be fine to deploy to users.
* Adds the --extra-index-url to the pip wheel command, allowing PyTorch to be found.
* Hack setup.py to remove the _mlir_libs dir before building. This keeps back-to-back versions from accumulating in the wheels for subsequent versions. IREE has a more principled way of doing this, but what I have here should work.

Co-authored-by: Stella Laurenzo <stellaraccident@gmail.com>
2022-04-21 02:19:12 -07:00
Sean Silva 075464fa74 Add a new `torch_mlir.compile` method.
This makes it much easier to convert models and hides all the
ClassAnnotator complexity.

This also adds a new example `torchscript_resnet18_all_output_types.py`
which shows the ResNet18 IR for all output types.

Also,

- This moves `run_pipeline_with_repro_report` to
  `torch_mlir.compiler_utils`.
2022-04-20 10:06:01 -07:00
Vivek Khandelwal 769f3a8870 [MLIR][TORCH] Add E2E support for max_pool2d_with_indices op
This commit adds lowering of `max_pool2d_with_indices` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-04-18 21:05:19 +05:30
Ashay Rane a893c7d5cf
Add shape transfer function and lowering to linalg for aten.neg (#759)
* shape: add shape transfer function for aten.neg

Prior to this patch, the list of shape transfer functions did not
include `aten.neg`, which resulted in errors like below.

```
error: unsupported by backend lowering: tensor with unknown rank or dtype
note: see current operation: %0 = "torch.aten.neg"(%arg0) :
  (!torch.vtensor<[256,256],f32>) -> !torch.vtensor<*,f32>
note: this is likely due to a missing shape transfer function in shape_lib_gen.py
```

This patch fixes the problem by adding a shape transfer function to
reflect the point-wise nature of this operation.

* linalg: add translation of aten.neg operation

This patch adds a translation rule to lower `aten.neg` operations on
tensors to an `arith.negf` operation wrapped inside a `linalg.generic`
operation.  This patch also adds a rudimentary test.
2022-04-15 11:11:22 -07:00
Vivek Khandelwal 1bccb4fc8a [MLIR][TORCH] Add E2E support for aten::max_pool2d_with_indices_backward op
This commit adds lowering of `aten::max_pool2d_with_indices_backward` op.

This commit also fixes formatting issues in basic.py.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-04-14 21:46:47 +05:30
Maksim Levental d46f169c1a
Fix kwarg annotation in eager (#747) 2022-04-11 17:35:42 -05:00
Maksim Levental 66de821eaf
small framework plus build_script_function (#745) 2022-04-11 16:53:52 -05:00
Maksim Levental 18ef40acaf
Fixes a bug in use of upstream `normalize_function` in our `normalize_args_kwargs` (in eager mode) and introduces unit tests. (#740)
NB: `shouldnt_normalize2` and `shouldnt_normalize3` currently XPASS i.e., args *will* successfully normalize despite being incorrect due to an [upstream bug](https://github.com/pytorch/pytorch/issues/75342).
2022-04-11 16:17:44 -05:00
gpetters94 9ec0683e92
Add 2D case for convolution (#693) 2022-04-08 00:47:57 -04:00
gpetters94 fa0b24a73c
Rename optional list types (#643) 2022-04-07 18:15:51 -04:00
Sean Silva 14cf87633c
Add link to forum post describing `__torch_dispatch__` 2022-04-01 10:10:43 -07:00
Sean Silva c17c0a6ba2 Fix for 0-size dim inferred incorrectly.
The issue was in the canonicalizer for torch.aten.ge.int -- in cases
where the operands were swapped, it would miscompile. This issue is
fixed and folding support generalized to `torch.aten.size.int < 0` as
well.

Fixes #716
2022-03-30 16:36:15 -07:00
Gaurav Shukla 969785d1b6 [LINALG] Add E2E support for `aten.where.[Scalar|ScalarSelf|ScalarOther]` ops
This commit decomposes different variants of `aten.where.*` op into
`aten.where.Self` op. It covers `aten.where.Scalar`,
`aten.where.ScalarSelf` and `aten.where.ScalarOther` ops.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-03-30 20:36:48 +05:30
Vivek Khandelwal 2597c481f6 [MLIR][TORCH] Add E2E support for aten.new_empty op
This commit decomposes `aten.new_empty` op into `aten.empty.memory_format` op.

This commit also made a dtype fix to the constant tensor allocation like ops.
Earlier the dtype for the result was inferred from the result type; now, it's
being evaluated as per the original definition of the op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-30 13:21:01 +05:30
Sean Silva 140babd952 Add minimal support for Union types.
A recent PyTorch commit made ConstantPad2d call a helper function with a
`Union[int, float]` type annotated. This commit adds minimal support for
representing and dealing with that.
https://github.com/pytorch/pytorch/pull/73287

Changes:
- Adding support for `!torch.union<T1, T2, T3>`/`Torch::UnionType`,
  along with the importer and CAPI code.
- Add support in isValidSubtype for union types.
- Adding a canonicalizer for `torch.derefine` to help simplify some code
  that derefines to a UnionType (this also fixes #664).

There is still more work to do for really supporting UnionType well,
such as canonicalizing UnionType's so that they can be compared with
pointer equality.
2022-03-29 17:45:48 -07:00
Maksim Levental 25ba51b2af
This commit decomposes aten._reshape_alias op into aten.view op. (#690) 2022-03-28 23:54:28 -05:00
Maksim Levental 3e999beaea
Small bug fixes in eager mode (#691) 2022-03-28 13:31:07 -05:00
Gaurav Shukla 02b6d04eb4 [LINALG] Add E2E support for `aten.zero_` op
This commit adds decomposition of `aten.zero_` op.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-03-25 12:46:50 +05:30
Sean Silva 94df096c11
Add note to not edit upstream_shape_helpers.py 2022-03-24 09:32:19 -07:00
Qiang Fu f7c7bb800c
Add non-default dtype support for a few elementwise math ops. (#687)
* fix type inference
* fix Torch2Linalg conversion
* add test cases
2022-03-23 13:35:43 -07:00
max fe8ac57e6d This PR implements an eager mode backend for PyTorch through the torch-mlir framework. This is accomplished by overriding the `__torch_dispatch__` class method on wrapper subclass `TorchMLIRTensor(torch.Tensor)`.
Effectively, this mode works by compiling op by op as the NN is eagerly executed by PyTorch. Entailed in that compilation is building a representation of the op that can be `torch.jit.script`ed, importing using `ModuleBuilder`, and then executing (e.g., with `RefBackendLinalgOnTensorsBackend`). This mode includes a fallback to conventional PyTorch if anything in the torch-mlir compilation process fails (e.g., unsupported op).

Currently, all e2e tests pass execpt for two that involve an upstream PyTorch bug (https://github.com/pytorch/pytorch/issues/74400).

High priority next steps:

1. A compile cache in order to speed up reruns of the same NN.
2. Integration with IREE (though not in this repo).
3. Integration with `torch.distributed`.
2022-03-22 14:42:57 -07:00
Gaurav Shukla 7c3ba25238 [LINALG] Add decomposition of `aten.dropout` op
- This commit adds decomposition of `aten.dropout` op. It also covers the
  training mode of the same op.
- It also adds lowering of `aten.sub.float` op.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-03-22 13:14:49 +05:30
Sean Silva 729402c3f4 Reduce compilation time for TorchOps.cpp.inc
The `assemblyFormat` stuff (which generates unrolled, per-op C++ code)
was taking up a lot of compile time, and all the ops are essentially
printed with the same logic. So this PR makes them all call the same
helper function. This is done by using
`let hasCustomAssemblyFormat = 1` and then implementing `FooOp::parse`
and `FooOp::print`.

Additionally, the `Generated*Ops.td` files are all collapsed into just
`GeneratedTorchOps.td` (there is no reason to have the files separate,
since the files are very large anyway so one is always having to search
within them -- editors don't care that the file to search is now a bit
bigger :) ).

This reduces TorchOpsODSGenerated.cpp compile time (which is now
GeneratedTorchOps.cpp) from 39 to 31 seconds on my machine. This is
actually less than I expected, but this PR is an overall cleanup to the
code anyway. The next step will be to introduce (better) functionality
upstream for sharding the TorchOps.cpp.inc file, so that we can truly
parallelize the O(#ops) costs. This is also necessary, because after
this PR, TorchDialect.cpp is now the slowest file to compile, due to the
`addOperations<... all the ops ...>` call, which needs to be shareded
too.
2022-03-21 14:42:26 -07:00
Vivek Khandelwal 5b9bdfaf3f [MLIR][TORCH] Add E2E support for aten._to_copy op
This commit decomposes `aten._to_copy` op into
`valsem.aten.copy` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-21 19:12:37 +05:30
Vivek Khandelwal 13383b03b8 [MLIR][TORCH] Add value tensor variant to aten::copy_ op
This commit adds the op `ValsemVariantAtenCopyOp` that represents
`AtenCopy_Op` without the underscore. This is needed to make sure
that the `ReduceOpVariants` pass turns the in-place op into an op
that takes value tensors as inputs, otherwise the
`MaximizeValueSemantics` pass will not be able to add value
semantics correctly.

This commit also adds the lowering of `ValsemVariantAtenCopyOp`.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-21 19:12:37 +05:30
Vivek Khandelwal 4c0cd5c23d [MLIR][TORCH] Add E2E support for aten.expand_as op
This commit decomposes `aten.expand_as` op into `aten.broadcast_to` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-21 12:47:39 +05:30
Vigilans 63fb1e5aad Bump LLVM at 8361c5da30588d3d4a48eae648f53be1feb5cfad 2022-03-18 13:16:14 -04:00
Prateek Gupta 7256c9e395 [TORCH][MLIR] Fix the return types of `aten.native_layer_norm`.
This commit fixes the 2nd and 3rd return types of the `aten.native_layer_norm`.
Previously the mean and rSTD were returned with reduction dims removed.
This commit fixes this and keeps the reduction dims of the results.

Signed-Off-By: Prateek Gupta <prateek@nord-labs.com>
2022-03-17 12:08:32 +05:30
Vivek Khandelwal 8da7d90611 [MLIR][TORCH] Add E2E support for aten.index_put op
This commit decomposes `aten.index_put` op into
`valsem.aten.index_put_impl` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-16 22:02:02 +05:30
Vivek Khandelwal 3d95c3d6c9 [MLIR][TORCH] Add value tensor variant to aten::_index_put_impl_
This commit adds the op `ValsemVariantAtenIndexPutImplOp` that represents
`Aten_IndexPutImpl_Op` without the underscore. This is needed to
make sure that the `ReduceOpVariants` pass turns the in-place op
into an op that takes value tensors as inputs, otherwise the
`MaximizeValueSemantics` pass will not be able to add value
semantics correctly.

This commit also adds the lowering of `ValsemVariantAtenIndexPutImplOp` op.

This commit also updates the `torch.bincount` op test cases.
2022-03-16 22:02:02 +05:30
Ramiro Leal-Cavazos 0bcc6d1075
Add maximize-value-semantics support for multiple non-value tensor inputs (#659)
This commit adds value semantics support for ops such as
`aten.view_as` and `aten.expand_as` that take two non-value 
tensors as input.
2022-03-15 18:13:45 -07:00
Sean Silva 92da4988f0 Improve "pseudo" op terminology.
The term "pseudo" is very vague and was getting confusing (I felt I had
to explain it in every comment referencing it). Instead, rework the
"pseudo" ops to instead be named:

- MLIR Syntax: `torch.valsem.*`
- C++ / ODS: `ValsemVariant*Op`

This makes it clear what the concept is, and avoids confusion with other
things that might be called "pseudo", since these are very specific and
should be 100% consistently named w.r.t. the non-valsem-variant ops that
they correspond to.
2022-03-15 17:57:52 -07:00
Sean Silva a5fe0cf063 Introduce new shape library design.
See the documentation in `docs/shape_lib.md` and
`docs/adding_a_shape_function.md` for an overview of the system.

This completely overhauls how we represent shape functions. In
particular, RefineTypes does not infer shapes anymore (only dtypes).
Shape functions are now written in (TorchScript'able) Python.

Recommended review order:

1. Read `docs/shape_lib.md` and `docs/adding_a_shape_function.md`.
1. Code and tests for ReifyShapeCalculations, DropShapeCalculations.
1. Code and tests for SimplifyShapeCalculations.
1. shape_lib_gen.py
1. Code and tests for new RefineTypes pass.
1. Random folders/canonicalizers in TorchOps.cpp and associated test in
   `canonicalize.mlir`.
1. New ReadOnly trait inferred from the registry.
1. Any miscellaneous remaining stuff.

Example `-print-ir-after-all` for ElementwiseUnaryModule:
[IR lowering dump](https://gist.github.com/silvasean/e4dc8cbc8d00aac7819602e3cbd8e212).

Example `-print-ir-after-all` for ElementwiseBinaryModule:
[IR lowering dump](https://gist.github.com/silvasean/daf6860ecced732af3568af6b1899113).
2022-03-15 12:41:58 -07:00
Prashant Kumar b6d13301fc [TORCH] Fix the location of packed_params.
The location of packed_params.h is changed in aten src.
2022-03-14 17:52:19 +05:30
Prateek Gupta 3d9ba5e525 [MLIR][TORCH] Add E2E support for aten.erf op.
Signed-Off-By: Prateek Gupta <prateek@nod-labs.com>
2022-03-09 22:22:03 +05:30
Vivek Khandelwal 1a2a9e066f [MLIR][TORCH] Add TorchToTMTensor pass
This pass is added to lower ops, which can not be lowered
via the TorchToLinalg pass, such as `torch.bincount` op.
This pass also uses torch-mlir's TMTensor Dialect to lower the
complex ops.

Also add torch.bincount op lowering with the help of TMTensor dialect

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-08 22:52:34 +05:30
Gaurav Shukla e57d3f9774 [LINALG] Fix `aten.bernoulli` op lowering
- This commit adds E2E support for `aten.rand_like` and
  `aten.bernoulli_.Tensor` ops.
- The `aten.bernoulli(x)` was implemented as:
  `aten.bernoulli(x) = rand_like(x) < 0.5`, assuming 0.5 as default
  probability, whereas according to the pytorch documentation:
  https://pytorch.org/docs/stable/generated/torch.bernoulli.html#torch.bernoulli
  the input x in `aten.bernoulli(x)` is itself a tensor containing
  probabilities to be used for drawing the binary random number.
- So this commit fixes the `aten.bernoulli(x)` implementation as:
  `aten.bernoulli(x) = rand_like(x) < x`.
- It also fixes the case where the input to `aten.bernoulli_.float` is
  an integer tensor. In this case the input must be casted to float type
  before passing it as operand to `aten.rand_like` op.
  `aten.bernoulli_.float(x, p) = rand_like(float(x)) < p`.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-03-05 09:38:22 +05:30
Vivek Khandelwal af551bd9cd [MLIR][TORCH] Add E2E support for aten.full_like op
This commit decomposes `aten.full_like` op into `aten.empty_like`
and `aten.fill` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-04 21:58:23 +05:30
Vivek Khandelwal d61ae92eee [MLIR][TORCH] Add E2E support for aten.full op
This commit decomposes `aten.full` op into `aten.empty` and
`aten.fill` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-04 21:58:23 +05:30
Yi Zhang 1d285f0153 Add aten.hardtanh e2e support. 2022-03-02 12:28:06 -05:00
Prashant Kumar 819f29316f Decompose aten.silu op
Decomposition of aten.silu.op is added as silu(x) = x * sigmoid(x).
2022-03-01 23:24:19 +05:30
Vivek Khandelwal ddd45d6068 [MLIR][TORCH] Add E2E support for aten.new_zeros, aten.new_ones op
This commit adds lowering of `aten.new_zeros` and `aten.new_ones` op

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-03-01 22:09:47 +05:30
Prashant Kumar 7c637eebc3 [LINALG] Decompose aten_hardswish op.
`aten.hardswish` op is decomposed into (x/6) * Relu6(x+3).
2022-02-25 21:59:27 +05:30
Prashant Kumar abbde7d439 [TORCH] The torch definition related to aten.gelu has changed.
New str argument approximation is added.
2022-02-18 21:57:46 +05:30
Gaurav Shukla cd21dda867 [LINALG] Add E2E support for `aten.Hardsigmoid` op
This commit adds lowering of `aten.Hardsigmoid` op.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-02-16 02:35:18 +05:30
Ramiro Leal-Cavazos 00a6e9c1bb
[LINALG] Add value tensor variant to `fill_.Scalar` (#600)
This commit adds the op `PseudoAtenFillScalarOp` that represents
`AtenFill_ScalarOp` without the underscore. The approach is the same
as in commit dd998fa4d4.

Adding this op allows for a simpler and more consistent version of the
`empty` and `empty_like` op e2e tests.
2022-02-15 11:58:03 -08:00
Gaurav Shukla 41acde599b [LINALG] Add E2E support for `aten.[le|ge].Scalar` ops
- This commit adds lowering of `aten.le.Scalar` and `aten.ge.Scalar` ops
  as a part of `convert-torch-to-linalg` pass.
- It also creates a new test script `elementwise_comparison.py` for all
  element-wise comparison ops.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-02-15 12:21:09 +05:30
Gaurav Shukla f00d1686c8 [LINALG] Add E2E support for `aten.[Bool.Tensor|Float.Tensor]` op
- This commit adds lowering of `aten.Bool.Tensor` and
  `aten.Float.Tensor` op as a part of `convert-torch-to-linalg` pass.
- It also adds support for returning bool types.
- It also fixes lowering of the `aten.Int.Tensor` op for non-zero rank
  input tensors.
- If a scalar number is converted to a 0-d tensor and passed on to the
  `aten.Float.Tensor` op, it folds to the scalar number.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-02-14 23:09:20 +05:30
Yi Zhang 9e7b6cab08 Add folder for aten.gt/lt.float 2022-02-14 12:34:01 -05:00
Henry Tu 73ac9a7e2e Added support for importing node prim::Constant with list type
Prior to this commit, importing a `prim::Constant` node with list type would result in an error since it was not supported. `ivalue_importer::importIValue` was modified to return the MlirValue corresponding to the root so its parent operation could be extracted.
2022-02-11 20:54:06 -05:00
Prashant Kumar 258660deb6 Add aten.bernoulli decomposition.
aten.bernoulli is decomposed to aten.gtTensor(aten.uniform(x), x).
2022-02-11 00:35:33 +05:30
Prashant Kumar 102c497c4c Add decomposition of _log_softmax op.
Decompose _log_softmax into log(softmax(x)).
2022-02-10 23:17:26 +05:30
Prateek Gupta 318946a650 [TORCH][MLIR] Add E2E support for `aten._unsafe_view` op.
This commit adds decomposition of `aten._unsafe_view` op into
`aten.view` op.

Signed-Off-By: Prateek Gupta<prateek@nod-labs.com>
2022-02-10 22:28:58 +05:30
Ramiro Leal-Cavazos 9b89f8eb3f
[TORCH][MLIR] Add E2E support for aten.clone (#571)
This commit adds support for the aten.clone op.
2022-02-09 19:31:03 -08:00
Gaurav Shukla 2fefe68ffd [TORCH][MLIR] Add E2E support for `aten.native_batch_norm` op
- This commit adds support for `aten.native_batch_norm` operation.
- The current implementation only supports inference mode of
  `aten.native_batch_norm` op.

Signed-Off-By: Gaurav Shukla <gaurav@nod-labs.com>
2022-02-08 02:54:03 +05:30
Prashant Kumar ccf546f14c Add aten::nll_loss_backward op
The lowering of aten::nll_loss_backward op has been added
from torch to linalg dialect. The changes has been made as
a part of -torch-convert-to-linalg pass.

Signed-off-by: Prashant Kumar prashant@nod-labs.com
2022-02-04 21:57:53 +05:30
Yi Zhang 0cb216a1ad [Torch][Linalg] Add basic support for RNG
This PR include the following pieces:
- Add torch `Generator` type. `Generator` type is converted to i64 in
refbackend type converter.
- Add seed managment support for the default global generator.
`torch_c.getNextSeed` op is used to get the seed. On refbackend, the
`torch_c.getNextSeed` is lowered to load/store from [0] of global
variable `default_generator` memref<i64> in `InsertRngGlobals` pass.
- Add `aten.uniform_` and testing as an example op for RNG ops. Add
`torch.pseudo.aten.uniform` op. It has the same operands and return as
the `aten.uniform_` from the op registry except for value semantics.
2022-01-31 18:56:42 -05:00
Yi Zhang 5d9a15263a [TORCH] Add aten.std e2e support 2022-01-31 15:17:49 -05:00
Prashant Kumar e58b66bc3b Add lowering of `aten.max.dim` op.
Lowering of `aten.max.dim` op has been added.
2022-01-31 21:41:22 +05:30
Liam Fitzpatrick 8bc028af05 Fold __is__ and unchecked_cast of derefine
The added e2e maxpool testcase from #545 was not getting a static shape
due to an unfolded prim.If when RefineTypes was called. This was because
of unfolded torch.iaten.__is__ and torch.prim.unchecked_cast operators
with torch.derefine operands.
2022-01-28 17:54:40 -05:00
Yi Zhang e1b3e5bc92 Fix build failure 2022-01-28 13:21:36 -05:00
stephenneuendorffer 3fd9b7789e
Bump LLVM to 881ff4e4ebe8cc0cc045c7c167cffb01f94f27f8 (#539) 2022-01-25 22:16:30 -08:00
Yi Zhang ad4b9e0369 Minor fixes 2022-01-24 19:21:15 -05:00
dan 3745f54489 Update external/llvm-project
- Add `qualified` to ods because of
https://reviews.llvm.org/D113873 and https://reviews.llvm.org/D116905
- Needed to revert https://github.com/llvm/torch-mlir/pull/520 as it
was based on an old torch version.
https://github.com/llvm/torch-mlir/pull/527 will bring this back with
a better design.
- Change ConvertAtenCatOp to use more accurate tensor shape info and
as much static info as possible to pass `tensor.insert_slice`
verification code added by https://reviews.llvm.org/D114715
- Other minor fixes
2022-01-18 13:25:42 -05:00
Yi Zhang 40efd2cb8e Revert "Add non-RNG aten ops to aten dialect."
This reverts commit c9a343267c.
2022-01-18 13:25:42 -05:00
Prateek Gupta c9a343267c Add non-RNG aten ops to aten dialect.
This commit adds the aten ops which do not require random number
support to aten dialect. This commit also adds some of the missing
torch types.

Signed-Off-By: Prateek Gupta <prateek@nod-labs.com>
2022-01-14 14:20:33 +05:30
Liam Fitzpatrick 077e55d756 Add support for constant_pad_nd
Note that to enable folding of the code coming from an example
like the ConstantPad2dStaticModule e2e test, support for other
operations had to be added/improved:
- aten::neg.int
- aten::eq.float
- aten::eq.str
- prim::Uninitialized
2022-01-11 10:25:25 -05:00
Vivek Khandelwal ca662dc9cc [MLIR][TORCH] Add E2E support for aten.threshold, aten.threshold_backward op
This commit adds lowering of `aten.threshold` op
This commit adds lowering of `aten.threshold_backward` op

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-01-10 11:56:56 +05:30
Gaurav Shukla 3c40539b34 [TORCH][MLIR] Add E2E support for `aten.[ones_like|zeros_like]`
- This commit adds E2E support for `aten.ones_like` and
  `aten.zeros_like` ops.
- Adds support for non-None `dtype` argument of `aten.empty_like` op.
- All the unit test cases related to constant tensor allocation like ops
  are moved to a different file named `constant_alloc.py`.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-01-06 20:24:40 +05:30
Ramiro Leal-Cavazos 9afaacedbd Fix build error regarding missing types in torch::jit
This commit adds include statements of the file
`torch/csrc/jit/ir/ir.h` for files that use types from torch::jit.

Fixes https://github.com/llvm/torch-mlir/issues/506
2022-01-03 13:36:22 -06:00
Vivek Khandelwal 4486de5ef3 [MLIR][TORCH] Add E2E support for torch.arange op
This commit adds lowering of `aten.arange.start_step` op.
This commit decomposes `aten.arange` and `aten.arange.start` into
`aten.arange.start_step` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2021-12-27 22:45:48 +05:30
Gaurav Shukla a83004c806 [TORCH][MLIR] Fold trivial cases of `aten.to.dtype` and `aten.view` op
- It folds `aten.to.dtype` when the input tensor type and result type
  are exactly same.
- It folds `aten.view` when the rank of both the input tensor type and
  result type is unity.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2021-12-24 13:32:34 +05:30
Nirvedh 3cb46cecef Added aten::t() Op 2021-12-22 10:57:10 -05:00
Gaurav Shukla eddc09aa55 [TORCH][MLIR] Add E2E support for `aten.eq` and `aten.lt` ops
- Added E2E support for `aten.eq.Tensor` and `aten.lt.Tensor` ops. Both
  the operands are expected to be of the same type, i.e., type promotion
  is not addressed as a part of this commit.
- Added E2E support for `aten.eq.Scalar` and `aten.lt.Scalar` ops.
  Tensor operand type to Scalar operand type promotion has not been
  handled in this commit.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2021-12-16 18:47:22 +05:30
Ramiro Leal-Cavazos 707c113463 Fix naming of results in ODS generator
This commit fixes the naming of results in the torch ODS generator
when dealing with multiple results. In particular, this commit appends
an index to each result name to guarantee that they are all unique.
2021-12-15 13:53:15 -06:00
Gaurav Shukla a778f990e9 [TORCH][MLIR] Add E2E support for `aten.ceil` op
This commit adds lowering of `aten.ceil` op as a part of element-wise
ops lowering.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2021-12-12 01:15:47 +05:30
harsh 03b6edce68 Add where, gt, bucketize and reshape ops to Torch dialect
This patch adds the where, gt, bucketize and reshape
ops to the Torch dialect. These ops are present in the histogram
calibration module.

TEST: Successfully lowers ops to Torch dialect in histogram module.
2021-12-10 10:08:20 -08:00
Prateek Gupta cfc8de36f8
[MLIR][TORCH] Add E2E support for `aten.native_layer_norm`. (#470)
This commit adds support for aten.native_layer_norm operation. Here
the previous code for aten.layer_norm is tweaked a little bit to
accomodate both mean and variance values alongwith the layer norm
value. This commit also adds decomposition of aten.layer_norm into
aten.native_layer_norm, which was previously getting lowered directly
to linalg.

Signed-Off-By: Prateek Gupta<prateek@nod-labs.com>
2021-12-10 19:06:19 +05:30
Gaurav Shukla 5a47f92390 [TORCH][MLIR] Add E2E support for `aten.squeeze.dim` op
This commit adds lowering of `aten.squeeze.dim` op into
`linalg.TensorCollapseShape` op. Here, the dim(th) dimension of the
input tensor is not supposed to be dynamic.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2021-12-10 17:01:20 +05:30
Gaurav Shukla f34eb66124 [TORCH][MLIR] Add E2E support for [`aten.gt.Scalar`|`aten.where.self`]
This commit adds lowering of `aten.gt.Scalar` and `aten.where.self` as a
part of element-wise ops lowering.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2021-12-09 12:47:10 +05:30
Prashant Kumar 977b1b03ea Add aten::nll_loss_forward op lowering.
The op lowering has been added as a part of `torch-lower-to-linalg`
pass. This takes care of ignore_index but the weight and reduction
operand is still to be accounted for.

Signed-off-by: Prashant Kumar <prashant@nod-labs.com>
2021-12-07 17:11:08 +05:30
Vivek Khandelwal 46a2189a41 [MLIR][TORCH] Add E2E support for aten.bitwise_and.tensor op
This commit adds lowering of `aten.bitwise_and.tensor` op.

Signed-Off By: Vivek Khandelwal vivek@nod-labs.com
2021-12-02 21:06:15 +05:30
Vivek Khandelwal 46a0668b3b [MLIR][TORCH] Add E2E support for aten.mean and aten.numel op.
This commit adds lowering of `aten.mean` and `aten.numel` op.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2021-12-02 11:51:13 +05:30
Gaurav Shukla 73b27b32dc [MLIR][TORCH] Add E2E support for `aten.squeeze` op
This commit adds lowering of `aten.Squeeze` op into
`linalg.TensorCollapseShape` op. The size 1 dynamic dimensions are not
handled as a part of this commit.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2021-11-30 23:00:28 +05:30
ds1231h 9ad5954e41 aten.abs and aten.reciprocal to linalg 2021-11-30 11:31:55 -05:00
Yi Zhang 5d28549c2c Add folder for torch.aten.Int.Tensor
This is to fold the common pattern from Bert inference like:
```
%111 = torch.prim.NumToTensor.Scalar %110 : !torch.int ->
    !torch.vtensor<[],si64>
%112 = torch.aten.Int.Tensor %111 : !torch.vtensor<[],si64> ->
    !torch.int
```
2021-11-30 21:55:48 +05:30
Daniel Garvey 539511c19b
Add dropout op (#436)
Co-authored-by: dan <dan@nod-labs.com>
2021-11-29 12:30:03 -06:00
Liam Fitzpatrick 7616d28ce1 Add leakyrelu support 2021-11-27 23:04:46 +05:30
Prateek Gupta f461a7ebce
[TORCH][MLIR] Add E2E support for aten._softmax operation. (#431)
Signed-Off-By: Prateek Gupta <prateek@nod-labs.com>
2021-11-25 11:19:02 +05:30
nodlabs 67ce816fca lowered addcmul and addcdiv to linalg 2021-11-24 17:26:47 -05:00
Prashant Kumar ea7a30f9b9 Add e2e test for aten.log_softmax_back_data op
aten.log_softmax_back_data op lowering and required
tests has been added. Some NFC have also been added.

Signed-off-by: Prashant Kumar prashant@nod-labs.com
2021-11-19 00:08:28 +05:30
Gaurav Shukla 663fc1ef51 [MLIR][TORCH] Add E2E support for [`aten.mul.Scalar`|`aten.addmm`]
This commit adds lowering of `aten.mul.Scalar` and also adds
decomposition of `aten.addmm` to `aten.mul.Scalar`, `aten.add.Tensor`
and `aten.mm` ops.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2021-11-18 22:26:41 +05:30
Prateek Gupta ecf78b9849
[TORCH][MLIR] Add E2E support for `aten.gelu_backward` operation. (#418)
This commit adds new operation `aten.gelu_backward` in the aten
dialect and adds lowering of this operation from aten to linalg.

Signed-Off-By: Prateek Gupta <prateek@nod-labs.com>
2021-11-17 14:59:38 +05:30
Yi Zhang 0fe70994e5 Add support for multiple return values
This change is to unblock the work of some backprop ops returning more
than one tensors. We will need to think of a more scalable approach
in the future if more flexible return types combinations are needed.
2021-11-16 21:07:45 -05:00
Prashant Kumar 909f7d7171 Add e2e testing for aten_tanh_backward op.
The e2e testing for aten_tanh_backward op has been added.
The testing is done for ref_backend.
2021-11-09 11:28:49 -05:00
George Petterson 2764e86f02 Add Rsqrt 2021-11-09 11:08:28 -05:00
Yi Zhang 3bd9d2a4c7 Add e2e support for aten._softmax_backward_data.
Decompose aten._softmax_backward_data into aten math ops. Also decompose
`aten.size` to facilitate decomposing _softmax_backward_data.
2021-11-09 13:09:30 +05:30
George Petterson e23cabf3a9 Add log2 2021-11-08 16:19:59 -05:00
Wang Kangyu 4bb9b44775 Add lowering of "aten.pow.Tensor_Scalar" op
Add e2e support for torch.pow(Tensor, Float)
2021-11-08 09:19:50 -08:00
Wang Kangyu b33543af85 Add lowering of aten.floor op 2021-11-06 17:31:44 -04:00
nodlabs 5ff823ace9 lowerd Sqrt to linalg
reused clang-format, as changes got deleted
2021-11-06 11:29:46 -04:00
Prashant Kumar ef897dbb19 Add lowering of `aten.log_softmax` op.
The `aten.log_softmax` is decomposed into `aten.softmax` and
`aten.log` op.
2021-11-03 22:10:05 +05:30
Prashant Kumar 127c7d8e27 Add lowering of `torch.log` op
The lowering of `torch.log` op has been added.

Signed-off-by: Prashant Kumar <prashant@nod-labs.com>
2021-11-02 21:18:00 +05:30
George Petterson 6dde5b347e Add rsub 2021-11-02 09:56:48 -04:00
Prashant Kumar 53b4275ef5 Add lowering of `aten.Int.Tensor` op.
The lowering of `aten.Int.Tensor` op has been added.
The changes has been made as a part of `convert-torch-to-linalg` pass.

Signed-off-by: Prashant Kumar <prashant@nod-labs.com>
2021-11-01 21:58:08 +05:30
Sean Silva b02b65cf6e Fix for upstream Torch change.
After https://github.com/pytorch/pytorch/pull/65967 the `graph()` method
is only available on `torch::jit::GraphFunction` now.

Fixes https://github.com/llvm/torch-mlir/issues/388
2021-10-28 11:12:05 -07:00
Prateek Gupta c33a2ca952 [TORCH][MLIR] Add E2E support for aten.permute.
This commit adds lowering of aten.permute to linalg.generic operation.

Signed-Off-By: Prateek Gupta <prateek@nod-labs.com>
2021-10-28 10:25:26 -04:00
Sean Silva 30df2ec71b Add min/max/clamp support.
Part of #380

Also
- BoolType is not considered as Scalar
- e2e framework fixes for nan handling
- `tu.rand(..., low=, high=)` support
- delete unused variable (fix warning)
- Add IouOfModule from #380 to e2e test suite (this is a common
  calculation in vision models)

 Your branch is ahead of 'origin/main' by 1 commit.
2021-10-27 13:29:21 -07:00
Prashant Kumar 5009cbf55c Add lowering of aten.matmul op.
Lowering of `aten.matmul` op is added from torch to linalg dialect.
The different cases correspond to
https://pytorch.org/docs/stable/generated/torch.matmul.html.
TODO: Broadcasting in case of batch-matmul is yet to be taken care of.

Signed-off-by: Prashant Kumar <prashant@nod-labs.com>
2021-10-26 12:45:09 -04:00
Boian Petkantchin e276dbbaa6
Add aten::gelu lowering (#374)
* Print more exception info on error during test execution

* Fix formatting

* Add aten::gelu lowering

Co-authored-by: Boian Petkantchin <boian@nod-labs.com>
2021-10-25 16:16:01 -07:00
Stella Laurenzo fe69bb339c
Bump llvm-project to 3d92722f74993969243d1400bc3257ca3d03902f. (#369)
* Picks up Python configure changes (was pinned to a bad intermediate commit).
* Uses the new mlir_configure_python_dev_packages() to ensure CMake python is found consistently.
* Fixes the JIT importer to build as a MODULE vs SHARED (needed for linking to Python as a module, per config changes).
* Adds some notes to the README to help folks build a smaller set focused just on this project.
2021-10-21 21:09:00 -07:00
Yi Zhang abfaf8c577 Add aten.ne.bool to make CI pass 2021-10-21 14:45:41 -04:00
George Petterson 8853dfbc74 Add broadcast 2021-10-19 13:33:31 -04:00
Yi Zhang a459e09ab7 E2e support for aten.softmax.int and aten.embedding
- Added a DecomposeComplexOps pass to decompose complex torchOps.
- Refactored `visitAtenArgmaxOp` and `visitAtenAnyDimOp` to
`visitReductionAlongDimIntOp`.
- Moved some helper functions into
torch-mlir/Dialect/Torch/Utils/Utils.h to be shared by multiple files.
- Added support for f64 tensor as argument and return types.
2021-10-18 17:57:45 -04:00
dan 7750d2173a add argmax lowering
Add argmax lowering from torch to linalg
2021-10-13 14:31:16 -04:00
Sean Silva 19e9fc4ef1 Bring some more order to the e2e error reporting situation.
- Move `run_pipeline_with_repro_report` to a more common place, and use it
  consistently
- Attach a `torch.debug_module_name` to the enclosing `builtin.module`
  op to allow for self-contained error reporting (not needing to pass
  the names around.
- Remove redundant error reporting in linalg_on_tensors_backend.py and
  tosa_backend.py (their respective backend abstract base classes now
  take care of the error reports themselves)
- Save off original value of sys.stderr, rather than always resetting to
  `sys.__stderr__`. This is just more hygienic, and allows nesting if
  desired.
2021-10-08 13:00:12 -07:00
Yi Zhang 98ba255288 E2e support for layernorm. 2021-10-04 14:15:13 -04:00