%2:2 = "tf.IteratorGetNext"(%0) {_class = ["loc:@iterator"], device = ""} : (tensor<!tf_type.resource>) -> (tensor<200x28x28x1xf32>, tensor<200x10xf32>)
  // CHECK: tf.Iterator
  // CHECK: tf.MakeIterator
  // CHECK: tf.IteratorGetNext
  return

// generated GraphDef to make sure the export is valid.

module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 890 : i32}}  {
  func.func @main(%arg0: tensor<100x28x28x3xf32> {}) -> (tensor<*xf32> {}) attributes {tf.entry_function = {control_outputs = "", inputs = "a:0", outputs = "conv2d_2/BiasAdd:0"}} {
    %0 = tf_executor.graph {

    explicit_paddings = [],
    padding = "VALID",
    strides = [1, 1, 1, 1],
    use_cudnn_on_gpu = true
  } : (tensor<4xi32>, tensor<3x3x1x32xf32>, tensor<100x26x26x32xf32>) -> tensor<100x28x28x1xf32>
  func.return %result : tensor<100x28x28x1xf32>
}

// -----

// CHECK-LABEL: @conv2d_backprop_input_grouped
func.func @conv2d_backprop_input_grouped(
    %filter: tensor<2x2x5x21xf32>,