commit | 7e463806dd20d8df8f93e9d02e1cf505e7df3a5b | [log] [tgz] |
---|---|---|
author | Scott Todd <scotttodd@google.com> | Thu Jun 30 14:31:00 2022 -0700 |
committer | GitHub <noreply@github.com> | Thu Jun 30 14:31:00 2022 -0700 |
tree | 080d5ecc6c3e41b6c7d18ab0c5d0b30298eb05e5 | |
parent | f1ec6e7c3284f2942aaa706fac68da43fd4b1f47 [diff] |
Replace mhlo ops with core dialect ops in some tests. (#9688) Progress on https://github.com/iree-org/iree/issues/9667, working towards removing MHLO and other input dialects from the "core" parts of the IREE compiler. Any tests using input dialects should be organized under the relevant `compiler/InputConversion/*` or `tests/e2e/*_ops/` directories. Some exceptions are okay, such as samples and benchmarks, but it will be easier to spot those exceptions once more of these are cleaned up. In this batch: * A few mechanical changes from mhlo elementwise ops to arith/math elementside ops * Changed "nested ops" and "attributes" tests in `Flow/Transforms/test/deduplicate_executables.mlir` from `mhlo.reduce` to `linalg.generic` * Split `Flow/Transforms/test/transformation.mlir` (testing `--iree-mhlo-input-transformation-pipeline --iree-flow-transformation-pipeline`) into `Flow/Transforms/test/transformation_pipeline.mlir` and `InputConversion/MHLO/test/transformation_pipeline.mlir` (one test per pipeline)
IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.
See our website for project details, user guides, and instructions on building from source.
IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!
See our website for more information.
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.