func.func @fuseUnpackAndConcatToReshape(%arg0: tensor<1x3x2xf32>) -> tensor<1x6xf32> {
  %0:3 = "tfl.unpack"(%arg0) {axis = 1 : i32, num = 3 : i32} : (tensor<1x3x2xf32>) -> (tensor<1x2xf32>, tensor<1x2xf32>, tensor<1x2xf32>)
  %1 = "tfl.concatenation"(%0#0, %0#1, %0#2) {axis = -1 : i32, fused_activation_function = "NONE"} : (tensor<1x2xf32>, tensor<1x2xf32>, tensor<1x2xf32>) -> tensor<1x6xf32>
  func.return %1 : tensor<1x6xf32>

// CHECK:           %[[VAL_11:.*]] = "tf.ArgMax"(%[[VAL_0]], %[[VAL_9]]) : (tensor<1x32x1xf32>, tensor<1xi32>) -> tensor<1x1xi32>
// CHECK:           return %[[VAL_10]], %[[VAL_11]] : tensor<1x1xf32>, tensor<1x1xi32>
// CHECK:         }
func.func @convert_argmax_with_reshaped_iota(%arg0: tensor<1x32x1xf32>) -> (tensor<1x1xf32>, tensor<1x1xi32>) {

  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
func.func @squeeze_ranked(%arg0: tensor<?x?x?xf32>) -> tensor<?xf32> {