6 Commits

Author SHA1 Message Date
Walter Erquinigo
9d1063642c
[NFC] Set a variable in the mlir data formatter (#65554)
The formatter fails when num_children is invoked and self.impl_type is
not set.
2023-09-06 20:13:39 -04:00
Jeremy Furtek
6685fd8239 [mlir] Add support for TF32 as a Builtin FloatType
This diff adds support for TF32 as a Builtin floating point type. This
supplements the recent addition of the TF32 semantic to the LLVM APFloat class
by extending usage to MLIR.

https://reviews.llvm.org/D151923

More information on the TF32 type can be found here:

https://blogs.nvidia.com/blog/2020/05/14/tensorfloat-32-precision-format/

Reviewed By: jpienaar

Differential Revision: https://reviews.llvm.org/D153705
2023-07-06 08:56:07 -07:00
Tobias Hieta
f9008e6366
[NFC][Py Reformat] Reformat python files in mlir subdir
This is an ongoing series of commits that are reformatting our
Python code.

Reformatting is done with `black`.

If you end up having problems merging this commit because you
have made changes to a python file, the best way to handle that
is to run git checkout --ours <yourfile> and then reformat it
with black.

If you run into any problems, post to discourse about it and
we will try to help.

RFC Thread below:

https://discourse.llvm.org/t/rfc-document-and-standardize-python-code-style

Differential Revision: https://reviews.llvm.org/D150782
2023-05-26 08:05:40 +02:00
David Majnemer
2f086f265b [APFloat] Add E4M3B11FNUZ
X. Sun et al. (https://dl.acm.org/doi/10.5555/3454287.3454728) published
a paper showing that an FP format with 4 bits of exponent, 3 bits of
significand and an exponent bias of 11 would work quite well for ML
applications.

Google hardware supports a variant of this format where 0x80 is used to
represent NaN, as in the Float8E4M3FNUZ format. Just like the
Float8E4M3FNUZ format, this format does not support -0 and values which
would map to it will become +0.

This format is proposed for inclusion in OpenXLA's StableHLO dialect: https://github.com/openxla/stablehlo/pull/1308

As part of inclusion in that dialect, APFloat needs to know how to
handle this format.

Differential Revision: https://reviews.llvm.org/D146441
2023-03-24 20:06:40 +00:00
Jake Hall
96267b6b88 [mlir] Add Float8E5M2FNUZ and Float8E4M3FNUZ types to MLIR
Float8E5M2FNUZ and Float8E4M3FNUZ have been added to APFloat in D141863.
This change adds these types as MLIR builtin types alongside Float8E5M2
and Float8E4M3FN (added in D133823 and D138075).

Reviewed By: krzysz00

Differential Revision: https://reviews.llvm.org/D143744
2023-02-13 18:26:27 +00:00
River Riddle
62fec084d6 [mlir] Add LLDB visualizers for MLIR constructs
This commit adds a significant amount of visualizers attempting
to cover the majority of our visualization needs. It covers:

* Operations/OperationName/Ops/OpInterfaces
* Attributes/Types/Attr|TypeInterfaces/NamedAttribute
* Blocks/Regions
* Various range types (e.g. ValueRange/TypeRange)
* Values/BlockArguments/OpResults

This does require an NFC change to interfaces to rename
the concept field to avoid clash with the base class. It
also requires exposing a few method to the debugger
to help resolve information that is non-trivial to reconstruct.
These methods are re-exported using a debug_Blah naming
scheme to avoid messing with hot methods.

Note that this makes use of the new callback feature in lldb-16
(currently trunk) that allows for providing visualizers based on
a dynamic callback, instead of just the typename. It requires
a very new lldb, but allows for providing good default visualization
for all attributes/operations/types out of the box.

Differential Revision: https://reviews.llvm.org/D139602
2022-12-11 22:45:34 -08:00