break loop
	}
}

// This comment didn't appear in generated go code.
func haha() {
	// Needed for cover to add counter increment here.
	_ = 42
}

// Some someFunction.
//
//go:nosplit
func someFunction() {

      %2:2 = "tf.IdentityN"(%1#0, %1#1) : (tensor<i32>, tensor<f32>) -> (tensor<i32>, tensor<f32>) loc("identity@some_function")
      tf_executor.yield %2#0, %2#1 : tensor<i32>, tensor<f32> loc("identity@some_function")
    } loc("identity@some_function")
    tf_executor.fetch
  }
  func.return

// CHECK-NEXT:      "tf_executor.island"() ({
// CHECK-NEXT:        "tf.Identity"(%{{.*}}) : (tensor<f32>) -> tensor<f32> loc("identity@some_function")
// CHECK-NEXT:        "tf_executor.yield"(%{{.*}}) : (tensor<f32>) -> () loc("identity@some_function")
// CHECK-NEXT:      }) : () -> (tensor<f32>, !tf_executor.control) loc("identity@some_function")
// CHECK-NEXT:      "tf_executor.fetch"(%{{.*}}) : (tensor<f32>) -> () loc(unknown)

import tensorflow.compat.v2 as tf
from tensorflow.compiler.mlir.tensorflow.tests.tf_saved_model import common


class TestModule(tf.Module):

  @tf.function(input_signature=[tf.TensorSpec([], tf.float32)])
  def some_function(self, x):
    return self.callee(x)

  # CHECK: While importing SavedModel function 'callee': in input signature:
  # CHECK-SAME: Unhandled structured value kind {{.*}} at index path: <value>.1.foo
  @tf.function

  #
  # CHECK:      func {{@[a-zA-Z_0-9]+}}(%arg0: tensor<f32> {{.*}}) -> (tensor<f32> {{.*}})
  # CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["some_function"]
  @tf.function(input_signature=[tf.TensorSpec([], tf.float32)])
  def some_function(self, x):
    return x


if __name__ == '__main__':

  signature_def = tf.saved_model.signature_def_utils.build_signature_def(
      inputs=None, outputs={'s': tensor_info_s}, method_name='some_function')
  signature_def2 = tf.saved_model.signature_def_utils.build_signature_def(
      inputs=None, outputs={'t': tensor_info_t}, method_name='some_function')

  # Create two signatures that share the same variable.
  return {'key': signature_def, 'key2': signature_def2}, None, None

  # CHECK-SAME:   tensor<f32> {tf_saved_model.index_path = []})
  # CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["some_function"]
  @tf.function(input_signature=[tf.TensorSpec([], tf.float32)])
  def some_function(self, x):
    return x + self.v42 + self.c43


if __name__ == '__main__':

class TestModule(tf.Module):

  @tf.function(input_signature=[
      tf.TensorSpec([], tf.float32),
      tf.TensorSpec([], tf.float32)
  ])
  def some_function(self, x, y):
    return x + y
    # Basic check that the debug info file is being correctly saved and loaded.
    #
    # CHECK: "tf.AddV2"{{.*}}loc(#loc{{[0-9]+}})
    # CHECK: "tf.Identity"{{.*}}loc(#loc{{[0-9]+}})

  return {
      'key': (tf.compat.v1.saved_model.signature_def_utils.build_signature_def(
          inputs={'x': tensor_info_x},
          outputs={'r': tensor_info_r},
          method_name='some_function'))
  }, None, None


if __name__ == '__main__':
  common_v1.set_tf_options()

  signature_def = tf.saved_model.signature_def_utils.build_signature_def(
      inputs=None,
      outputs={'result': tensor_info_result},
      method_name='some_function')

  return {'key_1': signature_def, 'key_2': signature_def}, None, None


if __name__ == '__main__':
  common_v1.set_tf_options()