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[xla:gpu] Build with GPU support fails with linker error #10616
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I have met the same error with you, #10592, still awaiting a response. |
Same problem... |
Something like
gets pretty far.
i.e. |
@pxanthopoulos were you able to find a solution? I am facing the same error when trying to build xla from source for GPU:
I tried passing the |
@neeldani what's your configure step like? should look like |
This worked, thank you! |
So, the linker error how to resolve, I get the same error: undefined reference to `tsl::Env::Default()' |
I am trying to build XLA from source following the instructions found below, with Docker & GPU support:
https://openxla.org/xla/build_from_source
More specifically, i cloned the XLA repo from a directory and executed the following commands:
docker run --gpus all --name xla_gpu -w /xla -it -d --rm -v ./xla:/xla tensorflow/build:latest-python3.9 bash
(I added the
--gpus all
flag because the configure script failed as it could not findnvidia-smi
.)docker exec -it xla_gpu bash
./configure.py --backend=CUDA
with output:bazel build --test_output=all --spawn_strategy=sandboxed //xla/...
This step failed with the following error message:
I overcame this error by editing the file
/root/.cache/bazel/_bazel_root/e4ab50d61a21943a819d1e092972a817/external/local_config_nccl/BUILD
referenced at the error message. I added the following to the end of this file:alias( name = "nccl_headers", actual = "@nccl_archive//:nccl_headers", visibility = ["//visibility:public"], )
Then, I reran the 4th step (the build command). After building ~39000 of the ~45000 targets, it then failed with the following error message:
The text was updated successfully, but these errors were encountered: