// expected-remark@+1 {{failed to create tf2xla kernel: INVALID_ARGUMENT: NodeDef missing attrs 'seed2', 'seed' from}}
  %cst = "tf.Const"() {value = dense<[32, 12, 12, 64]> : tensor<4xi32>} : () -> tensor<4xi32>
  %0 = "tf.RandomUniform"(%cst) {} : (tensor<4xi32>) -> tensor<32x12x12x64xf32>
  // CHECK: return %1 : tensor<32x12x12x64xf32>
  func.return %0 : tensor<32x12x12x64xf32>
}
}
// -----

        %cst = "tf.Const"() {value = dense<2.000000e+00> : tensor<2x3x3x1xf32>} : () -> tensor<2x3x3x1xf32>
        %cst_0 = "tf.Const"() {value = dense<0.400000e+00> : tensor<3xf32>} : () -> tensor<3xf32>
        %cst_1 = "tf.Const"() {value = dense<0.500000e+00> : tensor<3xf32>} : () -> tensor<3xf32>
        %w = "tf.Mul"(%cst, %arg1) : (tensor<2x3x3x1xf32>, tensor<f32>) -> tensor<2x3x3x1xf32>

            "class OnField { @B(A.CST) String foo; }",
            "class OnParameter { void foo(@B(A.CST) int x) {} }",
            "class InMethodBody { void foo(int x) { @B(A.CST) int value = 5; } }",
        ]

        impl.snapshot { run("impl:${language.compileTaskName}") }

        when:
        source api: ["class A { public static final int CST = 1234; }"]
        run("impl:${language.compileTaskName}")

    %cst = "tfl.no_value"() {value = unit} : () -> none

module {
  func.func @conv_with_int_per_layer(%arg0: tensor<*xf32>) -> tensor<*xf32> {
    %cst = "tf.Const"() {device = "", value = dense<[-0.0192535277, -5.998660e-03]> : tensor<2xf32>} : () -> tensor<2xf32>

			if sd[i].Load() == 0 {
				continue
			}
			// We found a function that was executed.
			nCtrs := sd[i+coverage.NumCtrsOffset].Load()
			cst := i + coverage.FirstCtrOffset

			if cst+int(nCtrs) > len(sd) {
				break
			}
			counters := sd[cst : cst+int(nCtrs)]
			for i := range counters {
				if counters[i].Load() != 0 {
					totExec++
				}
			}
			i += coverage.FirstCtrOffset + int(nCtrs) - 1

      // CHECK-OPT: %{{.*}} = stablehlo.custom_call @tf.ResizeBilinear(%arg0, %cst) {align_corners = false, device = "", half_pixel_centers = true} : (tensor<1x32x32x128xf32>, tensor<2xi32>) -> tensor<1x64x64x128xf32>
      %1 = "tf.ResizeBilinear"(%arg0, %0) {

  %cst = "tf.Const"() <{value = dense<1> : tensor<i32>}> {device = ""} : () -> tensor<i32>
  %0 = "tf.MultiDeviceIteratorFromStringHandle"(%arg0) <{output_shapes = [#tf_type.shape<>], output_types = [!tf_type.string]}> {device = ""} : (tensor<!tf_type.string>) -> tensor<!tf_type.resource>

    %cst = "tf.Const"() {value = dense<[0, 1, 2, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
    %cst_0 = "tf.Const"() {value = dense<5.0> : tensor<f32>} : () -> tensor<f32>
    // Check that these constants are remained in constants.
    // CHECK: func private @while_cond
    // CHECK-DAG:  %[[CST:.*]]= "tf.Const"() <{value = dense<[0, 1, 2, 3]> : tensor<4xi32>}> : () -> tensor<4xi32>

// CHECK-SAME: tf_saved_model.initializer_type = "restore_op"
// CHECK-DAG: %[[CST:.*]] = "tf.Const"
// CHECK-DAG: %[[VAR_HANDLE:.*]] = "tf.VarHandleOp"
// CHECK: "tf.AssignVariableOp"(%[[VAR_HANDLE]], %[[CST]])

// Test that a new save function that wraps the SaveV2 op is created.
// CHECK: func.func private @tf_quant__save(%[[ARG:.*]]: tensor<!tf_type.string>)