# TODO(b/173549186): Move Google-internal TF code out of learning/brain
package_group(
    name = "internal",
    packages = [
        "//devtools/python/indexer/...",
        "//learning/brain/keras/...",
        "//learning/brain/mlir/...",
        "//learning/brain/tfrt/...",
        "//learning/lib/ami/simple_ml/...",
        "//learning/pathways/...",
        "//learning/serving/contrib/tfrt/mlir/canonical_ops/...",

		}
	}

	if matches == 0 {
		if len(vs.Spec.Http) > 0 {
			fmt.Fprintf(writer, "%sWARNING: No destinations match pod subsets (checked %d HTTP routes)\n",
				printSpaces(initPrintNum+printLevel1), len(vs.Spec.Http))
		}
		if len(vs.Spec.Tcp) > 0 {
			fmt.Fprintf(writer, "%sWARNING: No destinations match pod subsets (checked %d TCP routes)\n",
				printSpaces(initPrintNum+printLevel1), len(vs.Spec.Tcp))
		}

            }

            validateStringNoExpression("groupId", problems, Severity.WARNING, Version.V20, m.getGroupId(), m);
            if (parent == null) {
                validateStringNotEmpty("groupId", problems, Severity.FATAL, Version.V20, m.getGroupId(), m);
            }

            validateStringNoExpression("artifactId", problems, Severity.WARNING, Version.V20, m.getArtifactId(), m);

			b.Fatal(err)
		}
	}
}

func TestEncodeDecodeBaseOptions(t *testing.T) {
	v := BaseOptions{}
	var buf bytes.Buffer
	msgp.Encode(&buf, &v)

	m := v.Msgsize()
	if buf.Len() > m {
		t.Log("WARNING: TestEncodeDecodeBaseOptions Msgsize() is inaccurate")
	}

	vn := BaseOptions{}
	err := msgp.Decode(&buf, &vn)
	if err != nil {
		t.Error(err)
	}

	buf.Reset()
	msgp.Encode(&buf, &v)

        if (context == null) {
            return null;
        }
        return context.get(key);
    }

    /**
     * Sets the project's class realm. <strong>Warning:</strong> This is an internal utility method that is only public
     * for technical reasons, it is not part of the public API. In particular, this method can be changed or deleted

  if (environ_cp.get('TF_NEED_ROCM') == '1' and environ_cp.get('HIP_PLATFORM')):
    write_action_env_to_bazelrc('HIP_PLATFORM', environ_cp.get('HIP_PLATFORM'))

  if is_windows():
    print('\nWARNING: Cannot build with CUDA support on Windows.\n'
          'Starting in TF 2.11, CUDA build is not supported for Windows. '
          'For using TensorFlow GPU on Windows, you will need to build/install '

                    // still unreadable even in non-strict mode, rethrow original error
                    throw e;
                }

                Severity severity = request.isProjectBuild() ? Severity.ERROR : Severity.WARNING;
                problems.add(
                        severity,
                        ModelProblem.Version.V20,
                        "Malformed POM " + modelSource.getLocation() + ": " + e.getMessage(),

// called.
TF_CAPI_EXPORT extern TF_OperationDescription* TF_NewOperation(
    TF_Graph* graph, const char* op_type, const char* oper_name);

// Specify the device for `desc`.  Defaults to empty, meaning unconstrained.
TF_CAPI_EXPORT extern void TF_SetDevice(TF_OperationDescription* desc,
                                        const char* device);

// The calls to TF_AddInput and TF_AddInputList must match (in number,

  }

  /**
   * Creates a new {@code Multimap} backed by {@code map}, whose internal value collections are
   * generated by {@code factory}.
   *
   * <p><b>Warning: do not use</b> this method when the collections returned by {@code factory}
   * implement either {@link List} or {@code Set}! Use the more specific method {@link

   * simply use the standard method-chaining idiom, as illustrated in the documentation at top,
   * configuring a {@code CacheBuilder} and building your {@link Cache} all in a single statement.
   *
   * <p><b>Warning:</b> if you ignore the above advice, and use this {@code CacheBuilder} to build a
   * cache whose key or value type is incompatible with the weigher, you will likely experience a