[Apache TVM Discuss] [Development] Modularize and Modernize TensorIR Tests

2023-07-02 Thread tqchen via Apache TVM Discuss
As we start to build multiple modules, it is useful to start modularizing the unit-tests with a goal of reducing some of the actual integration tests. Previously quite a few tests are written in a way that directly invokes end to end compilation, we also have tests that are coupled with legacy

Re: [apache/tvm] [Release] v0.13.0 release schedule (Issue #15134)

2023-07-02 Thread Bohan Hou
> The new branch and tag is now ready. -- Reply to this email directly or view it on GitHub: https://github.com/apache/tvm/issues/15134#issuecomment-1616748355 You are receiving this because you are subscribed to this thread. Message ID:

[Apache TVM Discuss] [Development] Modularize and Modernize TensorIR Tests

2023-07-02 Thread Junru Shao via Apache TVM Discuss
It is worth pointing out that: * Most of the existing tests are CPU-bound, including those uses GPU for execution (end-to-end tests), which also relies heavily on CPU for code generation * All e2e tests can be decoupled as host-side compilation on CPU + execution on device (e.g. GPUs) * Brute

Re: [apache/tvm] [Release] v0.13.0 release schedule (Issue #15134)

2023-07-02 Thread ysh329
Hi @spectrometerHBH, please make a PR on **v0.13.0 branch** like [this](https://github.com/apache/tvm/pull/14739/files), modify version to `0.13.0` **on v0.13.0 branch**. -- Reply to this email directly or view it on GitHub: https://github.com/apache/tvm/issues/15134#issuecomment-1617129797 You

[Apache TVM Discuss] [Development/unity] [DISCUSS] Inplace Update in Dataflow Block

2023-07-02 Thread Zihao Ye via Apache TVM Discuss
Hi @slyubomirsky @tqchen , can we enable multiple outputs for `call_tir_inplace`? We have a use case of fusing rotary embedding and flashattention in MLC-LLM, the programming interface is: ``` @T.prim_func def fused_rotary_flashattention(k: T.Buffer(...), q: T.Buffer(...), v: T.Buffer(...), o