const auto attr = DenseIntElementsAttr::get(shape_type, values);
    return builder.create<TF::ConstOp>(loc, attr);
  }

  const auto type = RankedTensorType::get(shape, builder.getF32Type());
  const auto value_attr = DenseFPElementsAttr::get(type, values);
  return builder.create<TF::ConstOp>(loc, value_attr);
}

// Creates a 1D array with integer/float type.
template <typename T>

  Type resultType = RankedTensorType::get(shape, element_type);
  auto constant_attr = DenseElementsAttr::get(shape_spec_type, shape);
  auto shape_tensor =
      rewriter.create<TF::ConstOp>(loc, shape_spec_type, constant_attr);
  return rewriter.create<TF::ReshapeOp>(loc, resultType, /*tensor=*/value,
                                        /*shape=*/shape_tensor);
}

template <typename BatchMatMulOpType>

}

TF::ConstOp Create1DConstantOp(const std::vector<int>& value, Location loc,
                               OpBuilder* builder) {
  auto type =
      mlir::RankedTensorType::get(value.size(), builder->getIntegerType(32));
  auto dense_values = mlir::DenseIntElementsAttr::get(type, value);
  return builder->create<TF::ConstOp>(loc, dense_values);
}

TF::ConstOp CreateScalarConstantOp(int value, Location loc,

	tests := []struct {
		name       string
		pod        *v1.Pod
		node       *v1.Node
		wantStatus *framework.Status
	}{
		{
			name: "A pod having no tolerations can't be scheduled onto a node with nonempty taints",
			pod:  podWithTolerations("pod1", []v1.Toleration{}),
			node: nodeWithTaints("nodeA", []v1.Taint{{Key: "dedicated", Value: "user1", Effect: "NoSchedule"}}),

    return %cst_0 : tensor<8xf32>
  }
}

// -----

// Tests the case when there is no ConstOp.
module attributes {tf_saved_model.semantics} {

// Check that nothing happens when there's no ConstOp in the graph.
// CHECK-NOT: "tf_saved_model.session_initializer"()

  ASSERT_THAT(test_func, NotNull());

  Operation* mul_op = FindOperationOfType<TF::MulOp>(test_func);
  SmallVector<Value> results = ConstantFoldOpIfPossible(mul_op);
  EXPECT_THAT(results, SizeIs(1));
  EXPECT_TRUE(isa<TF::ConstOp>(results[0].getDefiningOp()));
}

TEST_F(ConstantFoldingTest, NotFoldingIdentity) {
  constexpr absl::string_view kModuleCode = R"mlir(
    module {
      func.func @test_fold_constant() -> (tensor<1024x24x24x3xf32>) {

  // CHECK-NEXT: [[PREFIX:%.*]] = tf_mlrt.constop
  %cst = "tf.Const"() {__op_key = 0: i32, value = dense<"restore_ariables"> : tensor<!tf_type.string>} : () -> tensor<!tf_type.string>
  // CHECK-NEXT: [[SLICE:%.*]] = tf_mlrt.constop
  %cst_0 = "tf.Const"()  {__op_key = 1: i32, value = dense<""> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>
  // CHECK-NEXT: [[NAME:%.*]] = tf_mlrt.constop

    IntegerAttr group_key = rewriter.getI32IntegerAttr(0);

    auto const_group_size = rewriter.create<TF::ConstOp>(
        assign_group->getLoc(), assign_group.getResult(0).getType(),
        group_size);
    auto const_group_key = rewriter.create<TF::ConstOp>(
        assign_group->getLoc(), assign_group.getResult(1).getType(), group_key);

	spdyServer := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, req *http.Request) {
		ctx, err := createSPDYServerStreams(w, req, Options{
			Stdin:  true,
			Stdout: true,
		})
		if err != nil {
			t.Errorf("error on createHTTPStreams: %v", err)
			return
		}
		defer ctx.conn.Close()
		// Loopback STDIN data onto STDOUT stream.

			runPreFilter: true,
		},
		{
			name: "Pod with no Affinity will schedule onto a node",
			pod:  &v1.Pod{},
			labels: map[string]string{
				"foo": "bar",
			},
			wantPreFilterStatus: framework.NewStatus(framework.Skip),
			runPreFilter:        true,
		},
		{
			name: "Pod with Affinity but nil NodeSelector will schedule onto a node",
			pod: &v1.Pod{
				Spec: v1.PodSpec{
					Affinity: &v1.Affinity{