| # 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 tests.test_graph_conv import TestGraphConv | |
| def bm_graph_conv() -> None: | |
| backends = ["cpu"] | |
| if torch.cuda.is_available(): | |
| backends.append("cuda") | |
| kwargs_list = [] | |
| gconv_dim = [128, 256] | |
| num_meshes = [32, 64] | |
| num_verts = [100] | |
| num_faces = [1000] | |
| directed = [False, True] | |
| test_cases = product( | |
| gconv_dim, num_meshes, num_verts, num_faces, directed, backends | |
| ) | |
| for case in test_cases: | |
| g, n, v, f, d, b = case | |
| kwargs_list.append( | |
| { | |
| "gconv_dim": g, | |
| "num_meshes": n, | |
| "num_verts": v, | |
| "num_faces": f, | |
| "directed": d, | |
| "backend": b, | |
| } | |
| ) | |
| benchmark( | |
| TestGraphConv.graph_conv_forward_backward, | |
| "GRAPH CONV", | |
| kwargs_list, | |
| warmup_iters=1, | |
| ) | |
| if __name__ == "__main__": | |
| bm_graph_conv() | |