%tmp0, %ctl0 = tfl.control_node controls "tfl.neg"(%arg0): (tensor<1xf32>) -> tensor<1xf32>
  %tmp1, %ctl1 = tfl.control_node controls "tfl.neg"(%tmp0): (tensor<1xf32>) -> tensor<1xf32>
  %tmp2, %ctl2 = tfl.control_node controls "tfl.neg"(%tmp1): (tensor<1xf32>) -> tensor<1xf32>
  %tmp3, %ctl3 = tfl.control_node controls "tfl.neg"(%tmp2): (tensor<1xf32>) -> tensor<1xf32>

  // expected-error@+1 {{'mhlo.uniform_dequantize' op is illegal as it is a UQ op or contains uq/qint types}}
  %0 = mhlo.uniform_dequantize %arg0 : (tensor<?x?x!quant.uniform<i8:f32, 1.000000e+00:3>>) -> tensor<?x?xf32>
  return %0 : tensor<?x?xf32>
}

// -----

func.func @illegal_tf_uniform_quantize(%arg0 : tensor<1xf32>) -> tensor<1xf32> {

  func.return %1 : tensor<4x4x4xf32>
}

func.func @testMultipleLstms(%arg0: tensor<4x4xf32>, %arg1: tensor<4xf32>, %arg2: tensor<4x4x4xf32>) -> tensor<4x4x4xf32> {

// CHECK-NEXT:      %12 = mhlo.dynamic_reshape %2, %11 : (tensor<4x256x?xf32>, tensor<3xi32>) -> tensor<4x256x?xf32>
// CHECK-NEXT:      %13 = "tfl.batch_matmul"(%3, %12) <{adj_x = false, adj_y = false, asymmetric_quantize_inputs = false}> : (tensor<4x4x256xf32>, tensor<4x256x?xf32>) -> tensor<4x4x?xf32>
// CHECK-NEXT:      %14 = "tfl.shape"(%arg0) : (tensor<4x4x256xf32>) -> tensor<3xi32>

  // CHECK: %{{.*}} = "tfl.reshape"(%{{.*}}, %[[cst]]) : (tensor<4xf32>, tensor<2xi32>) -> tensor<2x2xf32>
  %cst = arith.constant dense<[2, 2]> : tensor<2xi32>
  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %1 = "tfl.reshape" (%0, %cst) : (tensor<4xf32>, tensor<2xi32>) -> tensor<2x2xf32> loc("reshape")
  func.return %1 : tensor<2x2xf32>

        %6:2 = tf_executor.island wraps "tf.opC"() : () -> tensor<1xf32>
        %8:2 = tf_executor.island(%4#1) wraps "tf.opD"(%6#0) : (tensor<1xf32>) -> tensor<1xf32>
        tf_executor.fetch %8#0 : tensor<1xf32>
      }
      tf_executor.yield %3 : tensor<1xf32>
    }
    tf_executor.fetch
  }
  func.return
}

// CHECK:        tf_executor.island wraps "tf.opA"

// CHECK: (%[[ARG:.*]]: tensor<4xf32>) -> (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>)
func.func @main(%arg0: tensor<4xf32>) -> tensor<4xf32> attributes {tf.entry_function = {inputs = "mul"}} {
  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %1 = "tfl.squared_difference"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("squared_difference")

  // CHECK: %[[DIV:.*]] = tfl.div
  %3 = "tfl.div"(%2, %1) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("div")
  // CHECK: %[[EXP:.*]] = "tfl.exp"
  %4 = "tfl.exp"(%3) : (tensor<4xf32>) -> tensor<4xf32> loc("exp")
  // tfl.neg should be pruned
  // CHECK-NOT: "tfl.neg"
  %5 = "tfl.neg"(%4) : (tensor<4xf32>) -> tensor<4xf32> loc("neg")

// CHECK-NEXT:  } ]
// CHECK-NEXT:  signature_defs: [ ]
// CHECK-NEXT:}

func.func @main(%arg0: tensor<4xf32>, %arg1: tensor<4x!quant.uniform<u8:f32, 0.1>>) -> tensor<4xf32> {
  "tfl.NumericVerify"(%arg1, %arg0) {tolerance = 0.1 : f32} : (tensor<4x!quant.uniform<u8:f32, 0.1>>, tensor<4xf32>) -> (tensor<4xf32>)
  func.return %arg0 : tensor<4xf32>

// CHECK-DAG: %[[CAST_0:.*]] = "tf.Cast"(%[[ARG_0]]) <{Truncate = false}> : (tensor<2xbf16>) -> tensor<2xf32>
// CHECK-DAG: %[[CAST_1:.*]] = "tf.Cast"(%[[ARG_1]]) <{Truncate = false}> : (tensor<2xbf16>) -> tensor<2xf32>
// CHECK: %[[ADD:.*]] = "tf.AddV2"(%[[CAST_0]], %[[CAST_1]]) : (tensor<2xf32>, tensor<2xf32>) -> tensor<2xf32>