commit | 1c0c5a6ff64bedb1cb1275eaba16aab3fc26acdf | [log] [tgz] |
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author | Nirvedh Meshram <96096277+nirvedhmeshram@users.noreply.github.com> | Wed Aug 21 16:57:53 2024 -0500 |
committer | GitHub <noreply@github.com> | Wed Aug 21 16:57:53 2024 -0500 |
tree | e540b091b36baa95edf92a34c45cb38190a3c92a | |
parent | dd8abf70005050f30140871cdc602576c47199ac [diff] |
[Flow] Convert from tensor.cast to flow.tensor.reshape early (#18256) The reason to do this is that tensor.cast's can end up in dispatch regions and break the logic there. If they are converted to flow.tensor.reshape before dispatch formation then the correct thing happens and the resulting flow.tensor.reshape ops are left out of the dispatch.regions. Fixes : https://github.com/iree-org/iree/issues/18229
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
Package | Release status |
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GitHub release (stable) | |
GitHub release (nightly) | |
Python iree-compiler | |
Python iree-runtime |
Host platform | Build status |
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Linux | |
macOS | |
Windows |
For the full list of workflows see https://iree.dev/developers/general/github-actions/.
See our website for more information.
Community meeting recordings: IREE YouTube channel
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.