SQUARE = 92,
  ZEROS_LIKE = 93,
  FILL = 94,
  FLOOR_MOD = 95,
  RANGE = 96,
  RESIZE_NEAREST_NEIGHBOR = 97,
  LEAKY_RELU = 98,
  SQUARED_DIFFERENCE = 99,
  MIRROR_PAD = 100,
  ABS = 101,
  SPLIT_V = 102,
  UNIQUE = 103,
  CEIL = 104,
  REVERSE_V2 = 105,
  ADD_N = 106,
  GATHER_ND = 107,
  COS = 108,
  WHERE = 109,
  RANK = 110,
  ELU = 111,
  REVERSE_SEQUENCE = 112,

      // CHECK:      %[[SPLIT_OUT:[a-z0-9]+]]:2 = "tf.Split"(%[[CONST_SPLIT_DIM]], %[[RI_0]])
      // CHECK:      %[[PARALLEL_EXECUTE_OUTPUT:[0-9]*]]:3 = "tf_device.parallel_execute"
      // CHECK-NEXT:   %[[LAUNCH_0_OUTPUT:[0-9]*]]:2 = "tf_device.launch"() <{device = "TPU_REPLICATED_CORE_0"}>
      //
      // CHECK-NEXT:     %[[EXECUTE_0_OUTPUT:[0-9]*]]:2 = "tf.TPUExecute"(%[[SPLIT_OUT]]#0, %[[COMPILE]]#1)

			apierrors.NewInternalError(fmt.Errorf("no RequestInfo found in the context")),
			Codecs, schema.GroupVersion{}, w, req,
		)
		return
	}
	if !requestInfo.IsResourceRequest {
		pathParts := splitPath(requestInfo.Path)
		// only match /apis/<group>/<version>
		// only registered under /apis
		if len(pathParts) == 3 {
			r.versionDiscoveryHandler.ServeHTTP(w, req)
			return
		}
		// only match /apis/<group>

  func.return %0#0 : tensor<1x4x2x3xf32>

  // CHECK-LABEL: splitv
  // CHECK: "tfl.split_v"(%arg0, %arg1, %arg2) <{num_splits = 2 : i32}> : (tensor<1x4x3x3xf32>, tensor<2xi32>, tensor<i32>) -> (tensor<1x4x2x3xf32>, tensor<1x4x1x3xf32>)
}

  let results = (outs
    TFL_VariadicTensorOf<[F32, I16, I32, I8, UI8, QI8, QUI8, QI16]>:$outputs
  );

  let hasVerifier = 1;

  let hasOptions = 1;
}

def TFL_SplitVOp : TFL_Op<"split_v", [
    Pure,
    QuantizableResult,
    SameOperandsAndResultsScale]> {
  let summary = "Splits a tensor into `num_split` tensors along one dimension.";

  let description = [{

    "SQUARE",
    "ZEROS_LIKE",
    "FILL",
    "FLOOR_MOD",
    "RANGE",
    "RESIZE_NEAREST_NEIGHBOR",
    "LEAKY_RELU",
    "SQUARED_DIFFERENCE",
    "MIRROR_PAD",
    "ABS",
    "SPLIT_V",
    "UNIQUE",
    "CEIL",
    "REVERSE_V2",
    "ADD_N",
    "GATHER_ND",
    "COS",
    "WHERE",
    "RANK",
    "ELU",
    "REVERSE_SEQUENCE",
    "MATRIX_DIAG",

ForGeneralPurposeString(kthread.openSlice),ts,args,0);kthread.thread.sliceGroup.pushSlice(slice);},cpufreqUpDownEvent(eventName,cpuNumber,pid,ts,eventBase){const data=splitData(eventBase.details);this.cpufreqSlice(ts,eventName,data.cpu,data);return true;},cpufreqTargetEvent(eventName,cpuNumber,pid,ts,eventBase){const data=splitData(eventBase.details);this.cpufreqSlice(ts,eventName,data.cpu,data);return true;},cpufreqBoostUnboostEvent(eventName,cpuNumber,pid,ts,eventBase){this.cpufreqBoostSlice(t...