commit | 7dc0472aef922ab10e4f1711222fc72da31043dd | [log] [tgz] |
---|---|---|
author | Eric Lunderberg <Lunderberg@users.noreply.github.com> | Thu Apr 18 10:50:01 2024 -0500 |
committer | GitHub <noreply@github.com> | Thu Apr 18 11:50:01 2024 -0400 |
tree | 1306fd184326b40a796677202c22f810b3864a84 | |
parent | de91c5ca94ae87030ac697fc49aea5f89ce375d0 [diff] |
[Bugfix] CudaDeviceAPI::GetAttr may check kExist when GPUs absent (#16903) This commit resolves a bug that was introduced in https://github.com/apache/tvm/pull/16377. If no CUDA-capable GPUs are present, the call to `cudaGetDeviceCount` will return an error, which will be raised as an exception by the `CUDA_CALL` macro. However, checking the `kExist` flag is valid even if no GPUs are present. This commit removes the use of `CUDA_CALL`, and instead returns false in this case.
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.
TVM is licensed under the Apache-2.0 license.
Check out the TVM Documentation site for installation instructions, tutorials, examples, and more. The Getting Started with TVM tutorial is a great place to start.
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.