Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/50020
This pass implements the logic to group kLoop/kInput fusion patterns on
buffer level. The reason for this is that we can avoid a lot of
headaches to handle `shape-only` consumers specially (e.g. memref.dim,
shape.shapeOf) since shapes are already resolved in buffer world. It may
be better to move this pass to tensor level after more shape
inference/constraint infras are ready on mhlo level.
Copybara import of the project:
--
e31f8344b59aa9860097197585215ea1689b8ff4 by Wenyi Zhao <reyizero@gmail.com>:
[MLIR][DISC] support fusion on buffer
This pass implements the logic to group kLoop/kInput fusion patterns on
buffer level. The reason for this is that we can avoid a lot of
headaches to handle `shape-only` consumers specially (e.g. memref.dim,
shape.shapeOf) since shapes are already resolved in buffer world. It may
be better to move this pass to tensor level after more shape
inference/constraint infras are ready on mhlo level.
--
35f2eb2791241b0ab5db1ddcaf1b4006278ddccf by Wenyi Zhao <reyizero@gmail.com>:
fix
--
923c8d61f7fe00a2a0df22d5be396508f0667964 by Wenyi Zhao <reyizero@gmail.com>:
fix sanity check failure
PiperOrigin-RevId: 379743424
Wenyi Zhao