%elem = "tf._SomeOp"() : () -> tensor<f32>
  // CHECK-NOT: "tf.TensorListPushBack"
  // CHECK: %[[UPDATE:.*]] = "tf.XlaDynamicUpdateSlice"
  // CHECK: %[[CONST1:.*]] = "tf.Const"() <{value = dense<1> : tensor<1xi32>}> : () -> tensor<1xi32>
  // CHECK: %[[ADD:.*]] = "tf.AddV2"(%[[BARG2]], %[[CONST1]])
  // CHECK-NOT: "tf.TensorListPushBack"

  %0 = "tf.TensorListPushBack"(%arg0, %arg1) : (tensor<!tf_type.variant<tensor<?x1xf32>>>, tensor<16x1xf32>) -> tensor<!tf_type.variant<tensor<?x1xf32>>>

    %tl_0 = "tf.EmptyTensorList"(%elem_shape, %size) : (tensor<2xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<?x1xf32>>>
    %tl_1 = "tf.TensorListPushBack"(%tl_0, %elem) : (tensor<!tf_type.variant<tensor<?x1xf32>>>, tensor<16x1xf32>) -> tensor<!tf_type.variant<tensor<?x1xf32>>>
    %tl_2 = "tf.TensorListPushBack"(%tl_1, %elem) : (tensor<!tf_type.variant<tensor<?x1xf32>>>, tensor<16x1xf32>) -> tensor<!tf_type.variant<tensor<?x1xf32>>>

    // op into an op with a single varidic output in `.td`.
    auto converted = rewriter.create<TFL::CustomOp>(
        op->getLoc(), op->getResultTypes(), op->getOperands(),
        "TensorListPushBack", TFL::ConstBytesAttr::get(getContext(), ""));
    rewriter.replaceOp(op, converted.getResults());
    return success();
  }
};

struct ConvertVariantAddNOp : public OpRewritePattern<TF::AddNOp> {

// CHECK:      return [[RESULT]] : tensor<?x?x?xf32>
}

// -----

func.func @tensorlistPushBack(%arg0: tensor<3x10xf32>, %arg1: tensor<1xi32>, %arg2: tensor<10xf32>) -> tensor<?x10xf32> {
  %0 = "tf.TensorListFromTensor"(%arg0, %arg1) : (tensor<3x10xf32>, tensor<1xi32>) -> tensor<!tf_type.variant<tensor<10xf32>>>

  auto buffer = push.getInputHandle();
  auto it = buffer_to_size->find(buffer);
  if (it == buffer_to_size->end()) {
    return push.emitOpError(
        "found tf.TensorListPushBack on unknown TensorList.");
  }
  if (it->getSecond().fixed) {
    return push.emitError("cannot push on a fixed-size tensor list");
  }
  auto size = it->getSecond().size;
  OpBuilder builder(push);

        // TODO(srbs): This filter is a little conservative. E.g. a subgraph of
        // the form:
        //                          Const
        //                            |
        // EmptyTensorList -> TensorListPushBack -> TensorListPopBack -> Op
        //                                                  |
        //                                        (Discard popped list)
        //

  %max_size = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32>
  %tl = "tf.EmptyTensorList"(%elem_shape, %max_size) : (tensor<2xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<8x4xf32>>>
  %push = "tf.TensorListPushBack"(%tl, %arg0) : (tensor<!tf_type.variant<tensor<8x4xf32>>>, tensor<8x4xf32>) -> tensor<!tf_type.variant<tensor<8x4xf32>>>
  return
}
```

will be transformed to:

```mlir

      for (const mlir::OpOperand &use : arg.getUses()) {
        mlir::Operation *op = use.getOwner();
        // Currently we only check if the tensorlist argument is consumed by
        // `TensorListPushBack` or `TensorListResize`, since those are the only
        // length-mutating ops supported in this pass.
        if (llvm::isa<TF::TensorListPushBackOp>(op) ||
            llvm::isa<TF::TensorListResizeOp>(op)) {

  %max_size = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32>
  %tl = "tf.EmptyTensorList"(%elem_shape, %max_size) : (tensor<2xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<8x4xf32>>>
  %push = "tf.TensorListPushBack"(%tl, %arg0) : (tensor<!tf_type.variant<tensor<8x4xf32>>>, tensor<8x4xf32>) -> tensor<!tf_type.variant<tensor<8x4xf32>>>
  return
}
```

will be transformed to:

```mlir