{Group: "flowcontrol.apiserver.k8s.io", Version: "v1", Kind: "PriorityLevelConfigurationList"}:             {},
	}

	f := fuzz.New().NilChance(.5).NumElements(1, 1).RandSource(rand.NewSource(1))
	f.Funcs(
		func(s *runtime.RawExtension, c fuzz.Continue) {},
		func(s *metav1.LabelSelector, c fuzz.Continue) {
			c.FuzzNoCustom(s)

 public:
  explicit TapeVSpace(AbstractContext* ctx) : ctx_(ctx) {}
  ~TapeVSpace() override {}

  // Returns the number of elements in the gradient tensor.
  int64_t NumElements(AbstractTensorHandle* tensor) const override;

  // Consumes references to the tensors in the gradient_tensors list and returns
  // a tensor with the result.
  AbstractTensorHandle* AggregateGradients(

  result->clear();
  result->reserve(variable_indices.size());
  for (int var_idx : variable_indices) {
    Var* variable = nullptr;
    if (inputs[var_idx]->NumElements() == 0) {
      return errors::InvalidArgument("Empty resource tensor passed  at index ",
                                     var_idx,
                                     " to GetVariableInfosFromInputs.");
    }

}

// -----

func.func @testSetStaticDimensionBounds(%arg0: tensor<?x?xi32>, %arg1: tensor<4xi32>) -> tensor<?x?xi32> {
  // expected-error @below {{'tf.SetStaticDimensionBounds' op static shape must have num_elements == rank of input tensor}}
  %dyn_arg0 = "tf.SetStaticDimensionBounds" (%arg0, %arg1) :(tensor<?x?xi32>, tensor<4xi32>) -> tensor<?x?xi32>
  func.return %dyn_arg0 : tensor<?x?xi32>
}

// -----

		}
	}
}

func TestResetObjectMetaForStatus(t *testing.T) {
	meta := &ObjectMeta{}
	existingMeta := &ObjectMeta{}

	// fuzz the existingMeta to set every field, no nils
	f := fuzz.New().NilChance(0).NumElements(1, 1).MaxDepth(10)
	f.Fuzz(existingMeta)
	ResetObjectMetaForStatus(meta, existingMeta)

	// not all fields are stomped during the reset.  These fields should not have been set. False

      "SavedModel checkpoint does not contain object graph.");
  if (object_graph_tensor.dtype() != DT_STRING ||
      object_graph_tensor.dims() != 0 ||
      object_graph_tensor.NumElements() != 1) {
    return absl::Status(
        absl::StatusCode::kFailedPrecondition,
        "SavedModel checkpoint object graph was not the correct type.");
  }

    t.reset(imm_t->Resolve(&status));
    if (!status.ok()) {
      return status;
    }
  }
  if (data.size() != t->NumElements()) {
    return tensorflow::errors::InvalidArgument(absl::StrCat(
        "Mismatched number of elements: \n", "Expected: ", data.size(), "\n",
        "Actual: ", t->NumElements(), "\n"));
  }
  memcpy(data.data(), t->Data(), t->ByteSize());
  return ::tensorflow::OkStatus();
}

  mlir::MLIRContext context;
  RegisterDialects(context);
  mlir::Builder b(&context);

  // Create the sample tensor to convert.
  Tensor tensor(DT_STRING, TensorShape({1, 2, 2, 1}));
  EXPECT_EQ(4, tensor.NumElements());
  auto Tt = tensor.flat<tstring>();
  Tt.setValues({"one", "two", "three", "four"});
  auto value_or_status = ConvertTensor(tensor, &b);
  ASSERT_TRUE(value_or_status.ok());
  auto attr = value_or_status.value();

		}
	}
}

func TestSetExtractListRoundTrip(t *testing.T) {
	scheme := runtime.NewScheme()
	codecs := serializer.NewCodecFactory(scheme)
	fuzzer := fuzz.New().NilChance(0).NumElements(1, 5).Funcs(metafuzzer.Funcs(codecs)...).MaxDepth(10)
	for i := 0; i < 5; i++ {
		start := &testapigroup.CarpList{}
		fuzzer.Fuzz(&start.Items)

		list, err := meta.ExtractList(start)
		if err != nil {

func writeTableSec(ctxt *ld.Link, fns []*wasmFunc) {
	sizeOffset := writeSecHeader(ctxt, sectionTable)

	numElements := uint64(funcValueOffset + len(fns))
	writeUleb128(ctxt.Out, 1)           // number of tables
	ctxt.Out.WriteByte(0x70)            // type: anyfunc
	ctxt.Out.WriteByte(0x00)            // no max
	writeUleb128(ctxt.Out, numElements) // min

	writeSecSize(ctxt, sizeOffset)
}