// CHECK: tf.VarHandleOp
  %0 = "tf.VarHandleOp"() {container = "", shared_name = "x"} : () -> tensor<!tf_type.resource<tensor<i32>>>
  %cst = "tf.Const"() {device = "/CPU:0", value = dense<true> : tensor<i1>} : () -> tensor<i1>
  // CHECK: "tf.If"(%cst, %0)
  %1 = "tf.If"(%cst, %0) {then_branch = @some_func, else_branch = @some_func, is_stateless = false} : (tensor<i1>, tensor<!tf_type.resource<tensor<i32>>>) -> tensor<i32>

      // can't lower tf.Const.
      Value cst;
      if (use_mhlo_const) {
        cst = builder.create<mhlo::ConstantOp>(func_op->getLoc(), attrs);
      } else {
        cst = builder.create<TF::ConstOp>(func_op->getLoc(), attrs);
      }
      func_op.getArgument(i).replaceAllUsesWith(cst);
    }
    return module_op;
  }

    %9 = "tf.Const"() <{value = dense<"test"> : tensor<3x!tf_type.string>}> : () -> tensor<3x!tf_type.string>
    %cst = "tf.Const"() <{value = dense<0> : tensor<i32>}> : () -> tensor<i32>
    %11:4 = "tf.Split"(%cst, %0) {num_split = 4 : i32} : (tensor<i32>, tensor<128x1024xf32>) -> (tensor<32x1024xf32>, tensor<32x1024xf32>, tensor<32x1024xf32>, tensor<32x1024xf32>)

			// We found a function that was executed.
			nCtrs := sd[i+coverage.NumCtrsOffset].Load()
			pkgId := sd[i+coverage.PkgIdOffset].Load()
			funcId := sd[i+coverage.FuncIdOffset].Load()
			cst := i + coverage.FirstCtrOffset
			counters := sd[cst : cst+int(nCtrs)]

			// Check to make sure that we have at least one live
			// counter. See the implementation note in ClearCoverageCounters
			// for a description of why this is needed.

  getOperation().walk([&](mlir::TF::ConstOp cst) {
    auto dict = cst->getAttrDictionary();
    if (dict.size() == 1) {
      return;  // Optimization. Assume the one attribute is "value".
    }
    // Recreate the attributes dictionary to only contain "value".
    NamedAttrList attributes;
    attributes.append(NamedAttribute(value_str_attr, cst->getAttr("value")));
    cst->setAttrs(attributes.getDictionary(&getContext()));

            }

            @Override
            public void visitLdcInsn(Object cst) {
                super.visitLdcInsn(remap(cst));
            }

            @Override
            public void visitLocalVariable(String name, String desc, String signature, Label start, Label end, int index) {

  %cst = "tf.Const"() {value = dense<1.1> : tensor<100x512xf32>} : () -> tensor<100x512xf32>
  %one = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>

  void SetupAllStates();

  // Returns Whether the constant is a weight, which shouldn't be shared by
  // different ops.
  bool IsWeight(Operation* cst) { return llvm::is_contained(weights_, cst); }

  // Returns all the related quantization constraints of the op.
  std::unique_ptr<OpQuantSpec> GetQuantSpec(Operation* op);
  std::unique_ptr<OpQuantScaleSpec> GetQuantScaleSpec(Operation* op);

}

// CHECK-LABEL: decompose_quant_rescale
func.func @decompose_quant_rescale(%arg0: tensor<2xi32>) -> !tfr.tensor {
  %zp = arith.constant 67 : i64
  %cst = "tf.Const"() {value = dense<1.0> : tensor<f32>} : () -> tensor<f32>
  %scale_factor = "tfr.cast"(%cst) : (tensor<f32>) -> !tfr.tensor
  %input = "tfr.cast"(%arg0) : (tensor<2xi32>) -> !tfr.tensor

    // CHECK:   %[[CST:.*]] = "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>
    // CHECK:   %[[SUB:.*]] = "tf.Sub"(%[[CARG1]], %[[CST]])
    // CHECK:   %[[ELEM:.*]] = "tf._SomeOp"() : () -> tensor<f32>
    %cst = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %sub = "tf.Sub"(%arg1, %cst) : (tensor<i32>, tensor<i32>) -> tensor<i32>