Add support for lowering torch.aten.cat to tosa.concat
* add support for aten cat to tosa
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Co-authored-by: yifei <y.zhou@xilinx.com>
Co-authored-by: Lisa Liu <lingl@xilinx.com>
Currently, we run just the Linux in-tree tests when the RollPyTorch
workflow runs, but this is insufficient since WHL files for macOS or
Windows are sometimes not uploaded by PyTorch, causing the RollPyTorch
action to pass but all subsequent torch-mlir CI tests to fail because of
the broken build.
The easiest way to validate the RollPyTorch action on all platforms is
to run the standard set of tests that we run for each submitted PR, so
this patch makes the RollPyTorch action submit a PR instead of
committing the changes to the main branch directly. The PR is assigned
to a handful of folks for review, although this can be changed in the
future.
This commit updates the `llvm-project` and `mlir-hlo` submodules to
commits:
- llvm-project: 6875424135312aeb26ab8e0358ba7f9e6e80e741
- mlir-hlo: 92fd33a4bacbeb93ab276a49f38bdebd5f9d7487
The calls to `mlir::MlirOptMain` are updated to no longer specify the
flag `preloadDialectInContext` that has been removed (see:
https://reviews.llvm.org/D149039).
When the user does not specify the `stride` value in 2d pooling ops,
`stride` is given the value of an empty list. However, the current
lowerings for pooling ops assumed that the `stride` operand would
always be a list of two ints, leading to crashes when that was not the
case. This commit fixes the crashes by setting the value of `stride`
to `kernel_size` when `stride` is the empty list, since this is the
default `stride` value specified in PyTorch docs. See:
https://pytorch.org/docs/stable/generated/torch.nn.MaxPool2d.html#torch.nn.MaxPool2d
This reverts commit 0bf31ae614.
This reverts commit f7a1a076fa.
The last two PyTorch rolls have PyTorch versions that don't currently work on MacOS. This commit reverts to a PyTorch version that does work.
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.
The current decomposition for `aten.randn.generator` does not specify
the `dtype` argument of the empty tensors created to store the random
values. This leads to invalid IR when the output type of the `randn`
op is not the default PyTorch dtype.
Ramiro Leal-Cavazos
Prashant Kumar
rahul shrivastava
yifei410
Ashay Rane
Sean Silva
Chi_Liu
Maksim Levental
Yuanqiang Liu
Roll PyTorch Action
Zhekun Zhang
Vivek Khandelwal
Ze Zhang
Eric Kunze
Sambhav Jain