// CHECK-NEXT:   value {
// CHECK-NEXT:     list {
// CHECK-NEXT:       type: DT_INT64
// CHECK-NEXT:     }
// CHECK-NEXT:   }
// CHECK-NEXT: }
// CHECK-NEXT: attr {
// CHECK:        key: "dense_shapes"
// CHECK-NEXT:   value {
// CHECK-NEXT:     list {
// CHECK-NEXT:       shape {
// CHECK-NEXT:         dim {
// CHECK-NEXT:           size: 1
// CHECK-NEXT:         }
// CHECK-NEXT:       }

  %dense_value =
    "tf.ParseExampleV2"(%serialized, %names, %sparse_keys, %dense_keys, %ragged_keys, %dense_default)
    // CHECK: Tdense = [i64]
    // CHECK-SAME: dense_shapes = [#corert.shape<>]
    { device = "/device:CPU:0", num_sparse = 0 : i64, dense_shapes = [#tf_type.shape<>], resultSegmentSizes = array<i32: 0, 0, 0, 1, 0, 0>}

tensor<2x!tf_type.string>

      %outputs_10:8, %control_11 = tf_executor.island wraps "tf.ParseExampleV2"(%arg0, %outputs_4, %outputs_8, %outputs_2, %outputs_6, %outputs, %outputs_0) {Tdense = ["tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT"], dense_shapes = [#tf_type.shape<>, #tf_type.shape<>], device = "", num_sparse = 2 : i64, ragged_split_types = [], ragged_value_types = [], resultSegmentSizes = array<i32: 2, 2, 2, 2, 0, 0>, sparse_types = ["tfdtype$DT_STRING", "tfdtype$DT_INT64"]} : (tensor...

    key: "Nsparse"
    value {
      i: 0
    }
  }
  attr {
    key: "Tdense"
    value {
      list {
        type: DT_INT64
      }
    }
  }
  attr {
    key: "dense_shapes"
    value {
      list {
        shape {
          dim {
            size: 1
          }
        }
      }
    }
  }
  attr {
    key: "sparse_types"
    value {

// CHECK-LABEL: func @_tfrt_fallback_init
// CHECK-SAME: {{.*}} !tfrt.chain
// CHECK: tfrt_fallback_async.createop(%arg0) key(0) device("/device:CPU:0") "tf.ParseExampleV2"()
// CHECK-SAME: Tdense = [f32, f32], dense_shapes = [#corert.shape<>, #corert.shape<>]
// CHECK-SAME: num_sparse = 2 : i64, ragged_split_types = [], ragged_value_types = []
// CHECK-SAME: sparse_types = [!corert.string, i64]}
// CHECK-SAME: num_args(7)

  input: "ParseExample/Const_1"
  attr {
    key: "Tdense"
    value {
      list {
        type: DT_FLOAT
        type: DT_FLOAT
      }
    }
  }
  attr {
    key: "dense_shapes"
    value {
      list {
        shape {
        }
        shape {
        }
      }
    }
  }
  attr {
    key: "num_sparse"
    value {
      i: 2
    }
  }

    %11 = "tf.Const"() {value = dense<-1> : tensor<i32>} : () -> tensor<i32>
    // expected-remark@+1 {{Cost: 19}}

            list {
              type: DT_FLOAT
              type: DT_INT64
              type: DT_STRING
            }
          }
        }
        attr {
          name: "dense_shapes"
          type: "list(shape)"
          has_minimum: true
        }
      }
      op {
        name: "Placeholder"
        output_arg {
          name: "output"
          type_attr: "dtype"

  %result:2 = "tf.ParseExampleV2"(%serialized, %names, %empty_str_vector, %dense_keys, %empty_str_vector, %dense_default_0, %dense_default_1) {dense_shapes = [#tf_type.shape<>, #tf_type.shape<>], num_sparse = 0 : i64, resultSegmentSizes = array<i32: 0, 0, 0, 2, 0, 0>} : (tensor<32x!tf_type.string>, tensor<32x!tf_type.string>, tensor<0x!tf_type.string>, tensor<2x!tf_type.string>, tensor<0x!tf_type.string>,...

    TF_StrTensor:$names,
    Variadic<TF_StrTensor>:$sparse_keys,
    Variadic<TF_StrTensor>:$dense_keys,
    Variadic<TensorOf<[TF_Float32, TF_Int64, TF_Str]>>:$dense_defaults,

    TF_ShapeAttrArray:$dense_shapes
  );

  let results = (outs
    Variadic<TF_Int64Tensor>:$sparse_indices,                           // len(sparse_types)
    Variadic<TensorOf<[TF_Float32, TF_Int64, TF_Str]>>:$sparse_values,  // len(sparse_types)