%res_p3 = "tfl.cumsum"(%arg, %axis_p3) {exclusive = false, reverse = false} : (tensor<1x2x1x3xf32>, tensor<i32>) -> tensor<1x2x1x3xf32>
  func.return %res_m4, %res_m3, %res_m2, %res_m1, %res_00, %res_p1, %res_p2, %res_p3 : tensor<1x2x1x3xf32>, tensor<1x2x1x3xf32>, tensor<1x2x1x3xf32>, tensor<1x2x1x3xf32>, tensor<1x2x1x3xf32>, tensor<1x2x1x3xf32>, tensor<1x2x1x3xf32>, tensor<1x2x1x3xf32>

func.func @quantized_dot_general_not_converted(%arg0: tensor<1x1x512xf32>, %arg1: tensor<512x512x!quant.uniform<i8:f32, 0.00285>>) -> tensor<1x1x512xf32> {
  %0 = "mhlo.dot_general"(%arg0, %arg1) {
    dot_dimension_numbers = #mhlo.dot<
      lhs_contracting_dimensions = [2],
      rhs_contracting_dimensions = [0]
    >} : (tensor<1x1x512xf32>, tensor<512x512x!quant.uniform<i8:f32, 0.00285>>) -> tensor<1x1x512xf32>
  func.return %0 : tensor<1x1x512xf32>
}

  func.return %0 : tensor<2x2xf16>
}

// -----

// CHECK-LABEL: squeeze
func.func @squeeze(%arg0: tensor<1x1x10xf32>) -> tensor<1x10xf32> {
  // CHECK: mhlo.reshape
  %0 = "tf.Squeeze"(%arg0) : (tensor<1x1x10xf32>) -> tensor<1x10xf32>
  func.return %0 : tensor<1x10xf32>
}

// -----

// CHECK-LABEL: squeeze_ranked