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Results 1 - 2 of 2 for LD_LIBRARY_PATH (0.19 sec)

  1. configure.py

          environ_cp, 'TF_NEED_ROCM', 'ROCm', False, bazel_config_name='rocm')
      if (environ_cp.get('TF_NEED_ROCM') == '1' and
          'LD_LIBRARY_PATH' in environ_cp and
          environ_cp.get('LD_LIBRARY_PATH') != '1'):
        write_action_env_to_bazelrc('LD_LIBRARY_PATH',
                                    environ_cp.get('LD_LIBRARY_PATH'))
    
      if (environ_cp.get('TF_NEED_ROCM') == '1' and environ_cp.get('ROCM_PATH')):
    Registered: Tue Sep 09 12:39:10 UTC 2025
    - Last Modified: Wed Apr 30 15:18:54 UTC 2025
    - 48.3K bytes
    - Viewed (0)
  2. .github/bot_config.yml

         * If you have above configuration and using _**Ubuntu/Linux**_ platform -
           * Try adding the CUDA, CUPTI, and cuDNN installation directories to the $LD_LIBRARY_PATH environment variable.
           * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).
         * If error still persists then, apparently your CPU model does not support AVX instruction sets.
    Registered: Tue Sep 09 12:39:10 UTC 2025
    - Last Modified: Mon Jun 30 16:38:59 UTC 2025
    - 4K bytes
    - Viewed (0)
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