%0 = "tfl.var_handle"() {container = "", shared_name = "states"} : () -> tensor<!tf_type.resource<tensor<1x2x3xf32>>>
  %1 = "tfl.read_variable"(%0) : (tensor<!tf_type.resource<tensor<1x2x3xf32>>>) -> tensor<1x2x3xf32>
  %2 = "tfl.quantize"(%1) {qtype = tensor<1x2x3x!quant.uniform<u8<1:255>:f32, 0.047244094488188976:128>>} : (tensor<1x2x3xf32>) -> tensor<1x2x3x!quant.uniform<u8<1:255>:f32, 0.047244094488188976:128>>

  // CHECK: [[Result:%.*]] = "tf.Case"(%arg0, %arg1)
  // CHECK-SAME: branches = [@tf.CaseRegion_branch0{{.*}}, @tf.CaseRegion_branch1{{.*}}]
  // CHECK-SAME: is_stateless = false
  %0 = "tf.CaseRegion"(%arg0) ({
    %1 = "tf.Cast"(%arg1) {Truncate = false} : (tensor<!tf_type.resource<tensor<1x2x3xf32>>>) -> tensor<!tf_type.resource>

// CHECK-NEXT:    return %[[VAL_2]] : tensor<1x2x4x1xf32>
// CHECK-NEXT:  }
}

// -----

module {
// expected-warning @+1 {{Invalid number of results from MaxUnpooling2D}}

  // CHECK: %[[INP0:.*]] = "tf.ExpandDims"(%[[ARG0]], %[[AXIS]]) : (tensor<3x5xf32>, tensor<i64>) -> tensor<1x3x5xf32>
  // CHECK: %[[INP1:.*]] = "tf.ExpandDims"(%[[ARG1]], %[[AXIS]]) : (tensor<3x5xf32>, tensor<i64>) -> tensor<1x3x5xf32>
  // CHECK: "tf.ConcatV2"(%[[INP0]], %[[INP1]], %[[AXIS]]) : (tensor<1x3x5xf32>, tensor<1x3x5xf32>, tensor<i64>) -> tensor<2x3x5xf32>

// CHECK-NEXT:    return %2 : tensor<3x2xf32>
}

func.func @transpose_3d(%arg0: tensor<1x2x3xf32>) -> tensor<3x2x1xf32> {
  %0 = "mhlo.transpose"(%arg0) <{permutation = dense<[2, 1, 0]> : tensor<3xi64>}> : (tensor<1x2x3xf32>) -> tensor<3x2x1xf32>
  func.return %0 : tensor<3x2x1xf32>

// CHECK-LABEL:   transpose_3d

  func.return %1 : tensor<1x2x2x5xf32>

// CHECK: %0 = "tfl.dequantize"(%arg0)
// CHECK: %1 = "tfl.strided_slice"(%0, %arg1, %arg2, %arg3)
// CHECK: %2 = "tfl.quantize"(%1) <{qtype = tensor<1x2x2x5x!quant.uniform<u8:f32, 1.000000e-01>>}> {volatile}
// CHECK: %3 = "tfl.dequantize"(%2)
// CHECK: return %3 : tensor<1x2x2x5xf32>
}

// CHECK-LABEL: QuantizePad

  %1 = "tf.GatherV2"(%params, %indices, %axis) {batch_dims = -1 : i64} : (tensor<16x2x3xf32>, tensor<16x5xi32>, tensor<1xi32>) -> tensor<16x2x5xf32>
  func.return %1 : tensor<16x2x5xf32>
}

// -----

// CHECK-LABEL: @gather_v2_dynamic
//  CHECK-SAME: %[[PARAMS:[a-zA-Z0-9_]+]]
//  CHECK-SAME: %[[INDICES:[a-zA-Z0-9_]+]]

// CHECK:           %[[VAL_4:.*]] = "tf.Transpose"(%[[VAL_0]], %[[VAL_3]]) : (tensor<1x2x3xf32>, tensor<3xi64>) -> tensor<3x2x1xf32>
// CHECK:           return %[[VAL_4]] : tensor<3x2x1xf32>
// CHECK:         }
func.func @transpose_3d_int32(%arg0: tensor<1x2x3xf32>) -> tensor<3x2x1xf32> {
  %0 = mhlo.constant dense<[2, 1, 0]> : tensor<3xi32>
  %1 = mhlo.constant dense<[2, 1, 0]> : tensor<3xi64>

  // CHECK: "tfl.strided_slice"(%arg0, %arg1, %arg2, %arg3) <{begin_mask = 0 : i32, ellipsis_mask = 0 : i32, end_mask = 0 : i32, new_axis_mask = 0 : i32, offset = false, shrink_axis_mask = 0 : i32}> : (tensor<12x2x2x5xf32>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x2x2x5xf32>