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README.md.tvm
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README.md.tvm
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<!--- Licensed to the Apache Software Foundation (ASF) under one -->
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<!--- to you under the Apache License, Version 2.0 (the -->
<!--- "License"); you may not use this file except in compliance -->
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<!--- Unless required by applicable law or agreed to in writing, -->
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<img src=https://raw.githubusercontent.com/apache/incubator-tvm-site/master/images/logo/tvm-logo-small.png width=128/> Open Deep Learning Compiler Stack
==============================================
[Documentation](https://tvm.apache.org/docs) |
[Contributors](CONTRIBUTORS.md) |
[Community](https://tvm.apache.org/community) |
[Release Notes](NEWS.md)
[](https://ci.tlcpack.ai/job/tvm/job/master/)
[](https://github.com/apache/incubator-tvm/actions?query=workflow%3AWinMacBuild)
Apache TVM (incubating) is a compiler stack for deep learning systems. It is designed to close the gap between the
productivity-focused deep learning frameworks, and the performance- and efficiency-focused hardware backends.
TVM works with deep learning frameworks to provide end to end compilation to different backends.
License
-------
© Contributors Licensed under an [Apache-2.0](LICENSE) license.
Contribute to TVM
-----------------
TVM adopts apache committer model, we aim to create an open source project that is maintained and owned by the community.
Checkout the [Contributor Guide](https://tvm.apache.org/docs/contribute/)
Acknowledgement
---------------
We learned a lot from the following projects when building TVM.
- [Halide](https://github.com/halide/Halide): Part of TVM's TIR and arithmetic simplification module
originates from Halide. We also learned and adapted some part of lowering pipeline from Halide.
- [Loopy](https://github.com/inducer/loopy): use of integer set analysis and its loop transformation primitives.
- [Theano](https://github.com/Theano/Theano): the design inspiration of symbolic scan operator for recurrence.