ERROR: /home/lzx_intern/.cache/bazel/_bazel_lzx_intern/aae30fe3449c6e42de7b177fce7468e4/external/local_config_cc/BUILD:57:1: in cc_toolchain rule @local_config_cc//:cc-compiler-k8: Error while selecting cc_toolchain: Toolchain identifier 'local' was not found, valid identifiers are [local_linux, local_darwin, local_windows]
ERROR: Analysis of target '//tensorflow:libtensorflow_cc.so' failed; build aborted: Analysis of target '@local_config_cc//:cc-compiler-k8' failed; build aborted
INFO: Elapsed time: 5.493s
INFO: 0 processes.
FAILED: Build did NOT complete successfully (41 packages loaded, 257 targets configur\
ed)
currently loading: @protobuf_archive// ... (2 packages)
uj5u.com熱心網友回復：
博主，我編譯的是C++版本成功并測驗了很多例子。就是每次有一些警告，(One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set. If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU. To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.如這種，你遇到過嗎？怎么在C++下激活XLA提高性能。我試了升級到tensorflow2.0不行，試了TF_EnableXLACompilation(options,true);說缺少庫？uj5u.com熱心網友回復：
https://blog.csdn.net/heiheiya/article/details/90697135 樓主的問題應該對應的是這個轉載請註明出處，本文鏈接：https://www.uj5u.com/qita/116550.html
標籤：人工智能技術
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