pytorch3d/tests/bm_graph_conv.py
Patrick Labatut af93f34834 License lint codebase
Summary: License lint codebase

Reviewed By: theschnitz

Differential Revision: D29001799

fbshipit-source-id: 5c59869911785b0181b1663bbf430bc8b7fb2909
2021-06-22 03:45:27 -07:00

51 lines
1.2 KiB
Python

# Copyright (c) Facebook, Inc. and its 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_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()