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https://github.com/stevenrobertson/cuburn.git
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185823ad55
Using one stream with two pagelocked host buffers allows us to keep the GPU work queue full without pegging the CPU, and also reduces the incidences where a host buffer will get overwritten before it can be written. devtid() was flaky, so this patch also introduces a ringbuffer to handle the 'slots' concept. It also introduces an adaptive number of temporal samples, which improves efficiency but also killed the assumption that (ntemporal_samples % 256 == 0), which required some additional fixes.
56 lines
1.3 KiB
Python
56 lines
1.3 KiB
Python
#!/usr/bin/python
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# Temporary helper script while I update main.py
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import os
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import sys
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import time
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import argparse
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import multiprocessing
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from subprocess import Popen
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from ctypes import *
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from itertools import ifilter
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import numpy as np
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import Image
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import scipy
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import pycuda.autoinit
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import cuburn.render
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import cuburn.genome
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import pycuda.compiler
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import pycuda.driver as cuda
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import cuburn.code.interp
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np.set_printoptions(precision=5, edgeitems=20)
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real_stdout = sys.stdout
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def save(rimg, pfx):
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noalpha = rimg.buf[:,:,:3]
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name = pfx + str(rimg.idx)
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img = scipy.misc.toimage(noalpha, cmin=0, cmax=1)
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img.save(name+'.png')
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print name, rimg.gpu_time
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sys.stdout.flush()
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def main(jobfilepath, outprefix):
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# This includes the genomes and other cruft, a dedicated reader will be
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# built in time tho
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info = cuburn.genome.load_info(open(jobfilepath).read())
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times = np.linspace(0, 1, info.duration * info.fps + 1)
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#rtimes = zip(['%05d' % i for i in range(len(times))[1:]], times, times[1:])
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rtimes = [('still', times[0], times[0]), ('motion', times[1], times[2])]
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renderer = cuburn.render.Renderer(info)
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renderer.compile()
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renderer.load()
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for out in renderer.render(rtimes):
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save(out, outprefix)
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if __name__ == "__main__":
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main(sys.argv[1], sys.argv[2] if len(sys.argv) > 2 else 'out/')
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