importlib.import_module("tf_keras.src.optimizers")
  else:
    importlib.import_module("keras.src.optimizers")
except (ImportError, AttributeError):
  pass

del importlib

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied

      else:
        error_count += 1
        elem_name = 'error'
      if command:
        failure_msg = (f'\nThe command was:\n\n'
                       f'{command}\n\n')
      else:
        failure_msg = ('\nCouldn\'t parse a bazel command '
                       'matching the invocation, inside the log. '
                       'Please look for it in the build log.\n\n')
      failure_msg += (

if _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH", ""):
  _ll.load_pluggable_device_library(
      _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH")
  )

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied

    if environ_cp.get('TF_CUDA_CLANG') == '1':
      # Set up which clang we should use as the cuda / host compiler.
      clang_cuda_compiler_path = set_clang_cuda_compiler_path(environ_cp)
      clang_version = retrieve_clang_version(clang_cuda_compiler_path)
      disable_clang_offsetof_extension(clang_version)
    else:
      # Set up which gcc nvcc should use as the host compiler
      # No need to set this on Windows