wantNoneReg(ctxt, ins, "rd", ins.rd)
	wantIntReg(ctxt, ins, "rs1", ins.rs1)
	wantIntReg(ctxt, ins, "rs2", ins.rs2)
	wantNoneReg(ctxt, ins, "rs3", ins.rs3)
}

func validateU(ctxt *obj.Link, ins *instruction) {
	wantImmI(ctxt, ins, ins.imm, 20)
	wantIntReg(ctxt, ins, "rd", ins.rd)
	wantNoneReg(ctxt, ins, "rs1", ins.rs1)
	wantNoneReg(ctxt, ins, "rs2", ins.rs2)
	wantNoneReg(ctxt, ins, "rs3", ins.rs3)

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.jstree-default li, 
.jstree-default ins,
#vakata-dragged.jstree-default .jstree-invalid, 
#vakata-dragged.jstree-default .jstree-ok, 
#jstree-marker.jstree-default { _background-image:url("../images/d.gif"); }
.jstree-default .jstree-open ins { _background-position:-72px 0; }
.jstree-default .jstree-closed ins { _background-position:-54px 0; }
.jstree-default .jstree-leaf ins { _background-position:-36px 0; }

  }];

  let arguments = (ins
    StrAttr:$node_def,
    I32Attr:$op_key
  );

  let assemblyFormat = "attr-dict";
}

def ConstOp: TensorflowMlrt_Op<"constop", []> {
  let summary = "The tf_mlrt ConstOp";

  let description = [{
    The ConstOp creates a constant tensorflow::Tensor from serialized proto.
  }];

  let arguments = (ins
    StrAttr:$tensor_proto
  );

  let description = [{
    Set a tensor in resource array.

    arg: the tensor to be set in the resource array.
    index: the index in the resource array
  }];

  let arguments = (ins
    TFTensorType:$arg,
    I64Attr:$index
  );

  let results = (outs);

  let assemblyFormat = "operands attr-dict";
}

  }];

  let arguments = (ins
    MlrtFutureType:$future
  );

  let assemblyFormat = "operands attr-dict";
}

def AwaitAllControlOp: Mlrt_Op<"await_all_control", []> {
  let summary = "Awaits multiple signals";

  let description = [{
    Awaits multiple signals

    $futures: A list of !mlrt.futures
  }];

  let arguments = (ins
    Variadic<MlrtFutureType>:$futures
  );

// elements. It returns a new slice of inline elements with links added.
func addSymbolLinksInlines(ins []md.Inline, defaultPackage string) []md.Inline {
	ins = splitAtBrackets(ins)
	var res []md.Inline
	for i := 0; i < len(ins); i++ {
		if txt := symbolLinkText(i, ins); txt != "" {
			link, ok := symbolLink(txt, defaultPackage)
			if ok {
				res = append(res, link)
				i += 2
				continue
			}

    %3 = tfr.constant [i32, f32] -> !tfr.attr
    %4 = tfr.constant f32 -> !tfr.attr
    ```
  }];

  let arguments = (ins TFR_allowedConstValues:$value);

  let results = (outs TFR_AttrType:$out);

  let hasFolder = 1;

  let builders = [
    OpBuilder<(ins "Attribute":$value),
    [{
      auto* ctx = value.getContext();
      $_state.addAttribute("value", value);

      "std::vector<int>", "GetSparseOperands", (ins)
    >,
    InterfaceMethod<
      [{Returns the supported block size of float sparse operands.}],
      "std::vector<std::vector<int>>", "GetFloatBlockSize", (ins)
    >,
    InterfaceMethod<
      [{Returns the supported block size of quantized sparse operands.}],
      "std::vector<std::vector<int>>", "GetQuantizedBlockSize", (ins)
    >,
  ];
}

  }]>;

def TFL_FusedBroadcastableBinaryBuilder :
  OpBuilder<(ins "Value":$lhs, "Value":$rhs,
    "StringAttr":$fusedActivationFunction),
  [{
    buildFusedBroadcastableBinOp(
       &$_builder, $_state, lhs, rhs, fusedActivationFunction);
  }]>;

def TFL_ComparisonBinaryBuilder :
  OpBuilder<(ins "Value":$lhs, "Value":$rhs),
  [{
    buildComparisonBinOp(&$_builder, $_state, lhs, rhs);

  let summary = "Constant tensor op";

  let arguments = (ins
    ElementsAttr:$value
  );

  let results = (outs
    TF_Tensor:$output
  );

  TF_DerivedResultTypeAttr dtype = TF_DerivedResultTypeAttr<0>;

  let builders = [
    OpBuilder<(ins "Attribute":$value)>,
    OpBuilder<(ins "Type":$type, "Attribute":$value)>,
  ];

  let hasFolder = 1;