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44 lines
1.0 KiB
Python
44 lines
1.0 KiB
Python
#!/usr/bin/env python3
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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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from itertools import product
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import torch
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from fvcore.common.benchmark import benchmark
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from test_graph_conv import TestGraphConv
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def bm_graph_conv() -> None:
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backends = ["cpu"]
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if torch.cuda.is_available():
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backends.append("cuda")
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kwargs_list = []
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gconv_dim = [128, 256]
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num_meshes = [32, 64]
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num_verts = [100]
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num_faces = [1000]
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directed = [False, True]
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test_cases = product(
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gconv_dim, num_meshes, num_verts, num_faces, directed, backends
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)
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for case in test_cases:
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g, n, v, f, d, b = case
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kwargs_list.append(
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{
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"gconv_dim": g,
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"num_meshes": n,
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"num_verts": v,
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"num_faces": f,
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"directed": d,
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"backend": b,
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}
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)
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benchmark(
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TestGraphConv.graph_conv_forward_backward,
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"GRAPH CONV",
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kwargs_list,
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warmup_iters=1,
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)
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