apiserver_envelope_encryption_kms_operations_latency_seconds_bucket{grpc_status_code="OK",method_name="/v2alpha1.KeyManagementService/Encrypt",provider_name="providerName",le="0.0002"} 0

        LinkMetaData linkMetaData = classLinkMetaData.getMethod("$METHOD_NAME()")

        then:
        linkMetaData != null
        linkMetaData.style == LinkMetaData.Style.Javadoc
        linkMetaData.displayName == "$SIMPLE_CLASSNAME.${METHOD_NAME}()"
        linkMetaData.urlFragment == "$METHOD_NAME--"

        when:
        linkMetaData = classLinkMetaData.getMethod("$METHOD_NAME(java.lang.Integer)")

        then:

import inspect

from fastapi import APIRouter, FastAPI

method_names = ["get", "put", "post", "delete", "options", "head", "patch", "trace"]


def test_signatures_consistency():
    base_sig = inspect.signature(APIRouter.get)
    for method_name in method_names:
        router_method = getattr(APIRouter, method_name)
        app_method = getattr(FastAPI, method_name)
        router_sig = inspect.signature(router_method)

            return new HttpDelete(uri);
        } else if (method.equalsIgnoreCase(HttpTrace.METHOD_NAME)) {
            return new HttpTrace(uri);
        } else if (method.equalsIgnoreCase(HttpOptions.METHOD_NAME)) {
            return new HttpOptions(uri);
        } else if (method.equalsIgnoreCase(HttpPatch.METHOD_NAME)) {
            return this.copyEntity(new HttpPatch(uri), request);
        } else {

  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

      inputs={'x': tensor_info_x},
      outputs={'r': tensor_info_r},
      method_name='some_function')
  signature_def2 = tf.saved_model.signature_def_utils.build_signature_def(
      inputs={'x': tensor_info_x},
      outputs={'r': tensor_info_r},
      method_name='some_other_function')

  # Create two signatures that share the same variable.

package mlir.tfrt;

message CompatibilityAnalysisReportProto {
  bool unknown_dialect = 1;
  bool ref_variable = 2;
  bool incompatible_variable = 3;
  bool incompatible_attribute = 4;
  bool control_flow_v1 = 5;
  string method_name = 6;

  // TODO(chky): add more checks, eg. tensor datatypes.
}

message CompatibilityAnalysisProto {
  CompatibilityAnalysisReportProto summary = 1;

  message OpInfo {
    int32 count = 1;

          },
          method_name='some_function')),
      'key2': (tf.compat.v1.saved_model.signature_def_utils.build_signature_def(
          inputs={
              'a': tensor_info_y,
              'b': tensor_info_x,
          },
          outputs={
              'c': tensor_info_t,
              'd': tensor_info_s,
          },
          method_name='reverse_arguments'))
  }, None, None

<component name="ProjectRunConfigurationManager">
  <configuration default="false" name="Not Slow" type="JUnit" factoryName="JUnit" singleton="false">
    <useClassPathOnly />
    <option name="MAIN_CLASS_NAME" value="" />
    <option name="METHOD_NAME" value="" />
    <option name="TEST_OBJECT" value="tags" />
    <option name="VM_PARAMETERS" value="-ea -Djunit.jupiter.extensions.autodetection.enabled=true" />
    <option name="PARAMETERS" value="" />

  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()