}

// CHECK-LABEL: QuantizeWithoutNorm
func.func @QuantizeWithoutNorm(%arg0: tensor<1x1x5xf32>) -> tensor<*xf32> attributes {tf.entry_function = {inputs = "input0", outputs = "output24"}} {
  %none = "tfl.no_value"() {value = unit} : () -> none
  %input = "quantfork.stats"(%arg0) {layerStats = dense<[-1.2, 1.5]> : tensor<2xf32>} : (tensor<1x1x5xf32>) -> tensor<1x1x5xf32>

        Args:
          input_tensor: Input tensor to matmul with the filter.

        Returns:
          A 'output' -> output tensor mapping
        """
        out = math_ops.matmul(input_tensor, random_tensor_gen_fn((2, 3)))
        out = math_ops.matmul(out, random_tensor_gen_fn((3, 4)))
        return {'output': out}

    model = TwoMatmulModel()
    input_shape = (1, 2)

    save.save(
        model,