}

// -----

// Test invalid tf.Less
func.func @testLess(tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32> {
^bb0(%arg0: tensor<4xi32>, %arg1: tensor<4xi32>):
  // expected-error @+1 {{op result #0 must be tensor of bool values}}
  %0 = "tf.Less"(%arg0, %arg1) : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32>
  func.return %0 : tensor<4xi32>
}

// -----

// Test valid tf.ConcatV2

func.func @testMaximumOfZeroToReluInt(%arg0: tensor<4xi32>) -> tensor<4xi32> {
  // CHECK: %0 = "tf.Relu"(%arg0) : (tensor<4xi32>) -> tensor<4xi32>
  // CHECK: return %0
  %cst_0 = arith.constant dense<0> : tensor<i32>
  %0 = "tf.Maximum"(%arg0, %cst_0) : (tensor<4xi32>, tensor<i32>) -> tensor<4xi32>
  func.return %0 : tensor<4xi32>
}

// CHECK-LABEL: testMaximumOfZeroToReluInt32OnGpu

// -----

func.func @testFusedActivationFunction(%arg0: tensor<4xi32>, %arg1: tensor<4xi32>) -> (tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>) {
  // CHECK: "NONE"
  %0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<4xi32>
  // CHECK: "RELU"
  %1 = tfl.add %arg0, %arg1 {fused_activation_function = "RELU"} : tensor<4xi32>
  // CHECK: "RELU_N1_TO_1"

    // CHECK: tf.Const
    // CHECK-SAME: () -> tensor<4xi32>
    %0 = "tf.Const"() {value = dense<[200, 26, 26, 32]> : tensor<4xi32>} : () -> tensor<*xi32>
    // CHECK: tf.Const
    // CHECK-SAME: () -> tensor<4xi32>
    %1 = "tf.Const"() {value = dense<[200, 26, 26, 32]> : tensor<4xi32>} : () -> tensor<*xi32>
    // CHECK: tf.Add
    // CHECK-SAME: (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32>

}

func.func @dynamic_update_slice(%arg0: tensor<4x5xi32>, %arg1: tensor<1x5xi32>, %arg2: tensor<2xi32>) -> tensor<4x5xi32> {
  %0 = "tf.XlaDynamicUpdateSlice"(%arg0, %arg1, %arg2) : (tensor<4x5xi32>, tensor<1x5xi32>, tensor<2xi32>) -> tensor<4x5xi32>
  func.return %0 : tensor<4x5xi32>

// CHECK-LABEL:dynamic_update_slice
// CHECK: "tfl.dynamic_update_slice"(%arg0, %arg1, %arg2) : (tensor<4x5xi32>, tensor<1x5xi32>, tensor<2xi32>) -> tensor<4x5xi32>

// CHECK-DAG: %[[CONST_0:.+]] = arith.constant dense<[1, 14, 14, 4]> : tensor<4xi32>
// CHECK-DAG: %[[CONST_1:.*]] = "tfl.pseudo_const"() <{value = dense<{{\[\[0, 0\], \[1, 1\], \[1, 1\], \[0, 0\]\]}}> : tensor<4x2xi32>}> : () -> tensor<4x2xi32>

  %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>