// CHECK: %[[CONV:.+]] = stablehlo.convolution(%[[ARG0]], %[[DQ]])
// CHECK{LITERAL}: dim_numbers = [b, 0, 1, f]x[o, 0, 1, i]->[b, 0, 1, f], window = {pad = [[1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64}
// CHECK-SAME: (tensor<1x3x3x4xf32>, tensor<2x3x3x4xf32>) -> tensor<1x3x3x2xf32>
// CHECK: return %[[CONV]]

// -----

  func.return %0 : tensor<256x32x32x16xf32>
}

// -----

func.func @testConv2D4DBias(tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<1x1x1x16xf32>) -> tensor<256x32x32x16xf32> {
^bb0(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<1x1x1x16xf32>):

}

func.func @batch_to_space_nd_unsupported(%arg0: tensor<?x1x1x1x4xf32>, %arg1: tensor<3xi32>, %arg2: tensor<3x2xi32>) -> tensor<?x3x3x3x4xf32> {
  %0 = "tf.BatchToSpaceND"(%arg0, %arg1, %arg2) : (tensor<?x1x1x1x4xf32>, tensor<3xi32>, tensor<3x2xi32>) -> tensor<?x3x3x3x4xf32>
  func.return %0 : tensor<?x3x3x3x4xf32>
  // CHECK-LABEL: batch_to_space_nd_unsupported
  // CHECK: "tf.BatchToSpaceND"
}