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https://github.com/facebookresearch/pytorch3d.git
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d57daa6f85
Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff) Reviewed By: nikhilaravi Differential Revision: D20558373 fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8
82 lines
2.3 KiB
Python
82 lines
2.3 KiB
Python
# 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_rasterize_meshes import TestRasterizeMeshes
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# ico levels:
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# 0: (12 verts, 20 faces)
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# 1: (42 verts, 80 faces)
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# 3: (642 verts, 1280 faces)
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# 4: (2562 verts, 5120 faces)
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def bm_rasterize_meshes() -> None:
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kwargs_list = [
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{
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"num_meshes": 1,
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"ico_level": 0,
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"image_size": 10, # very slow with large image size
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"blur_radius": 0.0,
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}
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]
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benchmark(
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TestRasterizeMeshes.rasterize_meshes_python_with_init,
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"RASTERIZE_MESHES",
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kwargs_list,
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warmup_iters=1,
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)
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kwargs_list = []
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num_meshes = [1]
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ico_level = [1]
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image_size = [64, 128]
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blur = [0.0, 1e-8, 1e-4]
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test_cases = product(num_meshes, ico_level, image_size, blur)
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for case in test_cases:
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n, ic, im, b = case
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kwargs_list.append(
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{"num_meshes": n, "ico_level": ic, "image_size": im, "blur_radius": b}
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)
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benchmark(
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TestRasterizeMeshes.rasterize_meshes_cpu_with_init,
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"RASTERIZE_MESHES",
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kwargs_list,
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warmup_iters=1,
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)
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if torch.cuda.is_available():
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kwargs_list = []
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num_meshes = [1, 8]
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ico_level = [0, 1, 3, 4]
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image_size = [64, 128, 512]
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blur = [0.0, 1e-8, 1e-4]
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bin_size = [0, 8, 32]
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test_cases = product(num_meshes, ico_level, image_size, blur, bin_size)
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# only keep cases where bin_size == 0 or image_size / bin_size < 16
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test_cases = [
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elem for elem in test_cases if (elem[-1] == 0 or elem[-3] / elem[-1] < 16)
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]
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for case in test_cases:
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n, ic, im, b, bn = case
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kwargs_list.append(
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{
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"num_meshes": n,
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"ico_level": ic,
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"image_size": im,
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"blur_radius": b,
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"bin_size": bn,
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"max_faces_per_bin": 200,
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}
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)
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benchmark(
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TestRasterizeMeshes.rasterize_meshes_cuda_with_init,
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"RASTERIZE_MESHES_CUDA",
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kwargs_list,
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warmup_iters=1,
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)
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