7 Commits

Author SHA1 Message Date
Kazu Hirata
c06d3a7b72
[mlir] Remove unused includes (NFC) (#148769)
These are identified by misc-include-cleaner.  I've filtered out those
that break builds.  Also, I'm staying away from llvm-config.h,
config.h, and Compiler.h, which likely cause platform- or
compiler-specific build failures.
2025-07-14 22:19:23 -07:00
Sandeep Dasgupta
81d7eef134
Sub-channel quantized type implementation (#120172)
This is an implementation for [RFC: Supporting Sub-Channel Quantization
in
MLIR](https://discourse.llvm.org/t/rfc-supporting-sub-channel-quantization-in-mlir/82694).

In order to make the review process easier, the PR has been divided into
the following commit labels:

1. **Add implementation for sub-channel type:** Includes the class
design for `UniformQuantizedSubChannelType`, printer/parser and bytecode
read/write support. The existing types (per-tensor and per-axis) are
unaltered.
2. **Add implementation for sub-channel type:** Lowering of
`quant.qcast` and `quant.dcast` operations to Linalg operations.
3. **Adding C/Python Apis:** We first define he C-APIs and build the
Python-APIs on top of those.
4. **Add pass to normalize generic ....:** This pass normalizes
sub-channel quantized types to per-tensor per-axis types, if possible.


A  design note:
- **Explicitly storing the `quantized_dimensions`, even when they can be
derived for ranked tensor.**
While it's possible to infer quantized dimensions from the static shape
of the scales (or zero-points) tensor for ranked
data tensors
([ref](https://discourse.llvm.org/t/rfc-supporting-sub-channel-quantization-in-mlir/82694/3)
for background), there are cases where this can lead to ambiguity and
issues with round-tripping.

```
Consider the example: tensor<2x4x!quant.uniform<i8:f32:{0:2, 0:2}, {{s00:z00, s01:z01}}>>
```

The shape of the scales tensor is [1, 2], which might suggest that only
axis 1 is quantized. While this inference is technically correct, as the
block size for axis 0 is a degenerate case (equal to the dimension
size), it can cause problems with round-tripping. Therefore, even for
ranked tensors, we are explicitly storing the quantized dimensions.
Suggestions welcome!


PS: I understand that the upcoming holidays may impact your schedule, so
please take your time with the review. There's no rush.
2025-03-23 07:37:55 -05:00
Rafael Ubal
852b648624
[mlir] Improvements to the 'quant' dialect (#100667)
Full revamp of the 'quant' dialect. This is an implementation for the
RFC at
https://discourse.llvm.org/t/rfc-improvements-in-the-quant-dialect/79942
2024-09-26 14:09:28 -04:00
Ramkumar Ramachandra
db791b278a
mlir/LogicalResult: move into llvm (#97309)
This patch is part of a project to move the Presburger library into
LLVM.
2024-07-02 10:42:33 +01:00
Jacques Pienaar
f007bcbc3c [mlir] Convert quantized dialect bytecode to generated.
Serves as rather self-contained documentation for using the generator
from https://reviews.llvm.org/D144820.

Differential Revision: https://reviews.llvm.org/D152118
2023-06-06 11:16:07 -07:00
Fangrui Song
cbb0981388 [mlir] llvm::Optional::value => operator*/operator->
std::optional::value() has undesired exception checking semantics and is
unavailable in older Xcode (see _LIBCPP_AVAILABILITY_BAD_OPTIONAL_ACCESS). The
call sites block std::optional migration.
2022-12-17 19:07:38 +00:00
Jacques Pienaar
7732c97f52 [mlir][quant] Initial bytecode encoding for quantized types
Add bytecode encoding for quantized types. These mostly follow the
storage representation of these.

Differential Revision: https://reviews.llvm.org/D136004
2022-10-17 16:28:46 -07:00