%44 = arith.constant dense<0> : tensor<4xi32>
  %45 = arith.constant dense<[1, 3872, 1, 128]> : tensor<4xi32>
  %46 = arith.constant dense<1> : tensor<4xi32>
  %47 = "tfl.strided_slice"(%arg0, %44, %45, %46) {begin_mask = 0 : i32, ellipsis_mask = 0 : i32, end_mask = 0 : i32, new_axis_mask = 0 : i32, offset = false, shrink_axis_mask = 0 : i32} : (tensor<2x3872x1x128xf32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>) -> tensor<1x3872x1x128xf32>

// %5 = stablehlo.reshape %4 :
//          (tensor<i32>) -> tensor<1xi32>
// %6 = stablehlo.concatenate %5, %0, %1, %2, dim = 0 :
//          (tensor<1xi32>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>)
//            -> tensor<4xi32>
// %7 = stablehlo.dynamic_broadcast_in_dim %arg2, %6
// %8 = stablehlo.add %3, %7
// ```
//
// Statically broadcasted bias will be broadcasted to match the accumulation.
// ```

  %12 = "tf.Transpose"(%11, %6) {device = ""} : (tensor<4x2xi32>, tensor<2xi32>) -> tensor<2x4xi32>
  %13 = "tf.Reshape"(%arg0, %1) {device = ""} : (tensor<1x1x2x1xf32>, tensor<1xi32>) -> tensor<2xf32>
  %14 = "tf.ScatterNd"(%12, %13, %3) {device = ""} : (tensor<2x4xi32>, tensor<2xf32>, tensor<4xi32>) -> tensor<1x2x4x1xf32>