Wenyi Zhao 34dc5f2a79 PR #50020: [MLIR][DISC] support fusion on buffer ... 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		2021-06-16 09:51:29 -07:00
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mhlo	PR #50020: [MLIR][DISC] support fusion on buffer	2021-06-16 09:51:29 -07:00
CMakeLists.txt	Add CMake files and lit configurations, enough for `ninja check-mlir-hlo` to pass on all the tests	2020-08-07 22:14:34 -07:00