// CHECK: tf_executor.island wraps "tf.LegacyCall"(%outputs, %outputs) <{_disable_call_shape_inference = true, f = @test_func_name0}> : (tensor<!tf_type.resource<tensor<i64>>>, tensor<!tf_type.resource<tensor<i64>>>) -> tensor<*x!tf_type.resource>

        tensor_shape {
        }
        float_val: 0.25
      }
    }
  }
  experimental_debug_info {
  }
}
node {
  name: "foo"
  op: "foo"
  input: "Const"
  attr {
    key: "_disable_call_shape_inference"
    value {
      b: true
    }
  }
  experimental_debug_info {
  }
}
node {
  name: "gradients/Shape"
  op: "Shape"
  input: "foo"
  attr {
    key: "T"
    value {

        type: DT_INT32
      }
    }
    ret {
      key: "a"
      value: "a_0"
    }
    attr {
      key: "_disable_call_shape_inference"
      value {
        b: true
      }
    }
  }
}

# CHECK: func @main

# CHECK-LABEL:  func @main() {
# CHECK:    "tf.LegacyCall"() <{_disable_call_shape_inference = true, f = @foo0}> {device = ""}
# CHECK:    "tf.LegacyCall"() <{_disable_call_shape_inference = false, f = @bar0}> {device = ""}

# CHECK-LABEL:  func private @foo0()
# CHECK: "tf.LegacyCall"() <{_disable_call_shape_inference = false, f = @bar0}> {device = ""}

    }
  }
  attr {
    key: "shared_name"
    value {
      s: "x"
    }
  }
}
node {
  name: "func_call"
  op: "test_func_name"
  input: "x"
  input: "x"
  attr {
    key: "_disable_call_shape_inference"
    value {
      b: true
    }
  }
}
library {
  function {
    signature {
      name: "test_func_name"
      input_arg {
        name: "a_0"
        type: DT_RESOURCE
      }

  min_consumer: 12
}

# Verify that functions from the library are properly imported.

# CHECK-LABEL:  func @main() {
# CHECK:    "tf.LegacyCall"() <{_disable_call_shape_inference = false, f = @foo110}> {device = ""}
# CHECK:    "tf.LegacyCall"() <{_disable_call_shape_inference = false, f = @foo111}> {device = ""}

# CHECK-LABEL:  func private @foo110()

    %outputs_0, %control_1 = tf_executor.island wraps "tf.LegacyCall"(%outputs, %outputs) {_disable_call_shape_inference = true, f = @test_func_name0} : (tensor<!tf_type.resource<tensor<i64>>>, tensor<!tf_type.resource<tensor<i64>>>) -> tensor<*x!tf_type.resource> loc("called")
    tf_executor.fetch %outputs_0 : tensor<*x!tf_type.resource>
  }

# the names are matching between the function definition and the uses / call
# site (a numerical suffix may be appended).

# CHECK: "tf.LegacyCall"(%outputs) <{_disable_call_shape_inference = false, f = @foo0}> {device = ""}

// CHECK-LABEL: func @convert_to_legacy_attribute
func.func @convert_to_legacy_attribute(%arg0: tensor<*xf32>, %arg1: tensor<f32>, %arg2: tensor<f32>) -> tensor<*xf32> attributes {tf._disable_call_shape_inference = true, tf.signature.is_stateful} {
  // CHECK-NOT: _replication_info =
  %0 = tf_executor.graph {

                         op->getSuccessors(), new_regions);
      inner_op = rewriter.create(state);
    } else {
      bool disable_call_shape_inference = false;
      if (op->hasAttr("_disable_call_shape_inference")) {
        disable_call_shape_inference =
            op->getAttrOfType<BoolAttr>("_disable_call_shape_inference")
                .getValue();
      }
      inner_op =