text: # Copyright (c) Meta Platforms, Inc. and affiliates.
  # All rights reserved.
  #
  # This source code is licensed under the BSD-style license found in the
  # LICENSE file in the root directory of this source tree.
  
  
  from itertools import product
  
  import torch
  from fvcore.common.benchmark import benchmark
  from test_packed_to_padded import TestPackedToPadded
  
  
  def bm_packed_to_padded() -> None:
      kwargs_list = []
      backend = ["cpu"]
      if torch.cuda.is_available():
          backend.append("cuda:0")
  
      num_meshes = [2, 10, 32]
      num_verts = [100, 1000]
      num_faces = [300, 3000]
      num_ds = [0, 1, 16]
  
      test_cases = product(num_meshes, num_verts, num_faces, num_ds, backend)
      for case in test_cases:
          n, v, f, d, b = case
          kwargs_list.append(
              {"num_meshes": n, "num_verts": v, "num_faces": f, "num_d": d, "device": b}
          )
      benchmark(
          TestPackedToPadded.packed_to_padded_with_init,
          "PACKED_TO_PADDED",
          kwargs_list,
          warmup_iters=1,
      )
  
      benchmark(
          TestPackedToPadded.packed_to_padded_with_init_torch,
          "PACKED_TO_PADDED_TORCH",
          kwargs_list,
          warmup_iters=1,
      )
  
  
  if __name__ == "__main__":
      bm_packed_to_padded()
  