commit | 8bd857d6fa3a23eab5c8a158af0711dc88333a26 | [log] [tgz] |
---|---|---|
author | Tianqi Chen <tqchen@users.noreply.github.com> | Tue Apr 20 18:04:48 2021 -0400 |
committer | GitHub <noreply@github.com> | Tue Apr 20 15:04:48 2021 -0700 |
tree | ecd9cbb2a36cad86cfab8447d2fd0299f62e29d8 | |
parent | 78657e1f8b2c97c3acc389e2b757c6ac8174388d [diff] |
[RPC][REFACTOR] Use PopenWorker to handle RPC Server. (#7889) Previously the rpc server relies multiprocessing to start a new process and does not work under jupyter. It also have a popen mode that does ensure the socket start listening before returning the port number. This PR switches the implementations use PopenWorker. The port number is returned after the socket get binded, which resolves some of the RPC flaky issues(need sleep to wait the server to start). It also makes the RPC server jupyter friendly.
Documentation | Contributors | Community | Release Notes
Apache TVM 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.
© Contributors Licensed under an Apache-2.0 license.
TVM adopts apache committer model, we aim to create an open source project that is maintained and owned by the community. Check out the Contributor Guide.
We learned a lot from the following projects when building TVM.