func.func @testFullyConnectedWithBadInputShape(%arg0: tensor<2x2x11xf32>, %arg1: tensor<40x40xf32>, %arg2: none) -> tensor<40xf32> {
  // expected-error @+1 {{expect 'input' num_elements % 40 == 0, got input type 'tensor<2x2x11xf32>'}}
  %0 = "tfl.fully_connected"(%arg0, %arg1, %arg2) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<2x2x11xf32>, tensor<40x40xf32>, none) -> tensor<1x40xf32>

  %0 = call @XlaCallModule__resize_0(%arg0) : (tensor<1x2x2x10xf32>) -> tensor<1x4x4x10xf32>
  return %0 : tensor<1x4x4x10xf32>
}
func.func private @XlaCallModule__resize_0(%arg0: tensor<1x2x2x10xf32>) -> (tensor<1x4x4x10xf32>) {
  %0 = mhlo.constant dense<2> : tensor<i32>
  %1 = mhlo.constant dense<0> : tensor<i32>
  %2 = mhlo.constant dense<4.000000e+00> : tensor<f32>

}

func.func @gatherV2VectorIndices_I64Axis(%arg0 : tensor<1x2x20xf32>, %arg1 : tensor<3x5xi32>) -> tensor<1x3x5x20xf32> {
  %0 = "tf.Const"() { value = dense<[1]> : tensor<1xi64> } : () -> tensor<1xi64>
  %1 = "tf.GatherV2"(%arg0, %arg1, %0) : (tensor<1x2x20xf32>, tensor<3x5xi32>, tensor<1xi64>) -> tensor<1x3x5x20xf32>

// CHECK:           %[[VAL_1:.*]] = arith.constant dense<[2, 2, 6]> : tensor<3xi64>
// CHECK:           %[[VAL_2:.*]] = "tf.Reshape"(%[[VAL_0]], %[[VAL_1]]) : (tensor<4x6xf32>, tensor<3xi64>) -> tensor<2x2x6xf32>
// CHECK:           return %[[VAL_2]] : tensor<2x2x6xf32>
// CHECK:         }
func.func @reshape(%arg0: tensor<4x6xf32>) -> tensor<2x2x6xf32> {