models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a
[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are
reachable and exploitable through production-grade, benign models.

### Compilation

Compiling models via the recommended entry points described in

#include "tensorflow/c/experimental/filesystem/modular_filesystem.h"
#include "tensorflow/cc/framework/gradients.h"
#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/cc/framework/scope_internal.h"
#include "tensorflow/cc/ops/while_loop.h"
#include "tensorflow/cc/saved_model/loader.h"
#include "tensorflow/core/distributed_runtime/server_lib.h"
#include "tensorflow/core/framework/logging.h"

      ASSERT_EQ(expected[i], data[i]) << "Different data at index " << i;
    }
  }

  std::vector<TF_Output> ToOutput(const std::vector<TF_Operation*> ops) {
    std::vector<TF_Output> out;
    for (auto op : ops) {
      out.push_back({op, 0});
    }
    return out;
  }

  void Define(int num_opers, const std::vector<TF_Operation*>& opers,

	defer func(old int) { buildcfg.GOPPC64 = old }(buildcfg.GOPPC64)
	for _, goppc64 := range []int{8, 9, 10} {
		t.Logf("GOPPC64=power%d", goppc64)
		buildcfg.GOPPC64 = goppc64
		// Some pseudo-ops may assemble differently depending on GOPPC64
		testEndToEnd(t, "ppc64", "ppc64")
		testEndToEnd(t, "ppc64", "ppc64_p10")
	}
}

func testRISCV64AllProfiles(t *testing.T, testFn func(t *testing.T)) {
	t.Helper()

*   [C/C++ license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op.cc#L1)
*   [Python license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/nn.py#L1)
*   [Java license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/java/src/main/java/org/tensorflow/Graph.java#L1)

// --------------------------------------------------------------------------
// Load plugins containing custom ops and kernels

// TF_Library holds information about dynamically loaded TensorFlow plugins.
typedef struct TF_Library TF_Library;

// Load the library specified by library_filename and register the ops and
// kernels present in that library.
//

  exitCommand: ""

## List of command to run after minio install
## NOTE: the mc command TARGET is always "myminio"
customCommands:
  # - command: "admin policy attach myminio consoleAdmin --group='cn=ops,cn=groups,dc=example,dc=com'"

## Additional Annotations for the Kubernetes Job customCommandJob
customCommandJob:
  securityContext:
    enabled: false
    runAsUser: 1000
    runAsGroup: 1000
  resources:

		adminLogIf(ctx, err)
		writeErrorResponseJSON(ctx, w, toAdminAPIErr(ctx, err), r.URL)
		return
	}
}

// SRPeerBucketOps - PUT /minio/admin/v3/site-replication/bucket-ops?bucket=x&operation=y
func (a adminAPIHandlers) SRPeerBucketOps(w http.ResponseWriter, r *http.Request) {
	ctx := r.Context()

	objectAPI, _ := validateAdminReq(ctx, w, r, policy.SiteReplicationOperationAction)

// once (i.e., on the main function side) in running distributed functions.
// This test creates a cluster with two workers, create a variable on the
// second worker, and run a distributed function (VariableAddFunction) whose ops
// span the local and remote workers. If the graph optimization pass is executed
// on both the main function side and the component function side, an error will
// be thrown in the registered graph optimization pass.

// function. Otherwise return nullptr in result and error Status from the
// function.
//
// If `library_filename` has already been loaded, we return a cached handle.
// Device and Kernels/Ops are registered as globals when a library is loaded
// for the first time.
TF_Library* TF_LoadPluggableDeviceLibrary(const char* library_filename,
                                          TF_Status* status) {