//    XlaRecvAtHost/XlaSendFromHost) to sequencer node.
  // c) Clear node_def.device(), so device placer won't get confused.
  for (const string& host_func : outside_compilation_host_graphs) {
    VLOG(4) << "Expanding host graph " << host_func;
    // Temporarily use "0" as "_device_ordinal". It will be reset to placeholder
    // value after we expanded all host graphs. We cannot just use placeholder

					parsedCRL.AuthorityKeyId, tc.issuer.SubjectKeyId)
			}
		})
	}
}

func TestRSAPSAParameters(t *testing.T) {
	generateParams := func(hashFunc crypto.Hash) []byte {
		var hashOID asn1.ObjectIdentifier

		switch hashFunc {
		case crypto.SHA256:
			hashOID = oidSHA256
		case crypto.SHA384:
			hashOID = oidSHA384
		case crypto.SHA512:
			hashOID = oidSHA512
		}

}

// -----

func.func @testXlaHostComputeMlir(%arg0: tensor<2xf32>) -> () {
  // expected-error @+1 {{'host_mlir_module' does not contain 'host_func' function}}

    // CHECK:          "tf_device.cluster"
    // CHECK:            %[[HOST_OUTPUT:[0-9]*]] = "tf._XlaHostComputeMlir"()
    // CHECK-SAME:       host_mlir_module = "module  {\0A  func.func @host_func() -> tensor<?xi32> {\0A    %0 = \22tf.B\22() {_xla_outside_compilation = \22cluster1\22} : () -> tensor<?xi32> loc(#loc1)\0A    return %0 : tensor<?xi32> loc(#loc1)\0A  }
    // CHECK:            "tf.C"(%[[HOST_OUTPUT]])

    // CHECK-SAME: tensor<2xf32>
    %0 = "tf._XlaHostComputeMlir"(%arg0) {recv_key = "host_compute_channel_recv", send_key = "host_compute_channel_send", tpu_core = 0, host_mlir_module = "module  {\0A  func.func @host_func(%arg0: tensor<*xf32>) -> tensor<*xf32> {\0A    %0 = \22tf.Identity\22(%arg0) {_xla_outside_compilation = \22cluster1\22} : (tensor<*xf32>) -> tensor<*xf32> \0A    return %0 : tensor<*xf32> \0A  } \0A} \0A"} : (tensor<2xf32>) -> tensor<*xf32>