var states []string
	if obj.DeletionTimestamp != nil {
		states = append(states, "deleted")
	}
	if obj.Status.Allocation == nil {
		if obj.DeletionTimestamp == nil {
			states = append(states, "pending")
		}
	} else {
		states = append(states, "allocated")
		if len(obj.Status.ReservedFor) > 0 {
			states = append(states, "reserved")

		ts.Config.ConnState = func(c net.Conn, state ConnState) {
			if c == nil {
				t.Errorf("nil conn seen in state %s", state)
				return
			}
			sl := <-activeLog
			if sl.active == nil && state == StateNew {
				sl.active = c
			} else if sl.active != c {
				t.Errorf("unexpected conn in state %s", state)
				activeLog <- sl
				return
			}

      // TODO: b/326332748 - For forward convolution in transpose_conv,
      // IsSamePadding calculation may need to be updated.
      // Reference: https://arxiv.org/pdf/1603.07285.pdf
      // Section 4.6 > Relationship 13 states `stride_dim = dilation + 1`.
      rewriter.replaceOpWithNewOp<TFL::TransposeConvOp>(
          // op result should be recasted to desired quantized type.
          op, output_type, /*output_shape=*/

      // The reduce function __reduce_func has 36 arguments, and the source of those arguments are listed below:
      //   [arg0, arg5]:   these are states coming from ReduceDatasetOp's [arg1, arg6]
      //   [arg6: arg14]:  these are the input elements coming from the output of %51:9
      //   [arg15: arg35]: these are the captured elements from ReduceDatasetOp's [arg7:arg27]

      "SparsityParameterAttr":$s_param, "Attribute":$compressed_data),
    [{
      $_state.addTypes(qtype.getValue());
      $_state.addAttribute("qtype", qtype);
      $_state.addAttribute("value", value);
      $_state.addAttribute("s_param", s_param);
      $_state.addAttribute("compressed_data", compressed_data);
    }]>
  ];
}

def TFL_QuantizeOp: TFL_Op<"quantize", [

    input_shapes.push_back(xla::TypeToShape(type));
  }

  absl::Status status = loader->RefineDynamicShapes(input_shapes);
  if (!status.ok()) {
    // Do not return false here.
    //
    // RefineDynamicShapes returns ok only when it produces full static shapes.
    // It may partially succeed by producing RankedTensor shapes with dynamic
    // dimensions. Such info is still useful for the downstream. We don't need

		status := ""
		if ready {
			status = "ready"
		}
		handleProbeSync(kl, update, handler, "readiness", status)
	case update := <-kl.startupManager.Updates():
		started := update.Result == proberesults.Success
		kl.statusManager.SetContainerStartup(update.PodUID, update.ContainerID, started)

		status := "unhealthy"
		if started {
			status = "started"
		}

// its String method returns "<invalid Value>", and all other methods panic.
// Most functions and methods never return an invalid value.
// If one does, its documentation states the conditions explicitly.
//
// A Value can be used concurrently by multiple goroutines provided that
// the underlying Go value can be used concurrently for the equivalent
// direct operations.
//

// srl : 2015-05-07 InterNetX, Corp
srl

// stada : 2014-11-13 STADA Arzneimittel AG
stada

// staples : 2015-07-30 Staples, Inc.
staples

// star : 2015-01-08 Star India Private Limited
star

// statebank : 2015-03-12 STATE BANK OF INDIA
statebank

// statefarm : 2015-07-30 State Farm Mutual Automobile Insurance Company
statefarm

// stc : 2014-10-09 Saudi Telecom Company
stc

	releasem(mp)
}

// templateThread is a thread in a known-good state that exists solely
// to start new threads in known-good states when the calling thread
// may not be in a good state.
//
// Many programs never need this, so templateThread is started lazily
// when we first enter a state that might lead to running on a thread
// in an unknown state.
//
// templateThread runs on an M without a P, so it must not have write