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# EDIT 10/04/2022 - This version was provided by @jayelm who fixed some bugs and made the function much more robust | |
import os | |
import subprocess | |
import time | |
def assign_free_gpus(threshold_vram_usage=1500, max_gpus=2, wait=False, sleep_time=10): | |
""" | |
Assigns free gpus to the current process via the CUDA_AVAILABLE_DEVICES env variable | |
This function should be called after all imports, |
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class OctConv(nn.Module): | |
def __init__(self, ch_in, ch_out, kernel_size, stride=1, alphas=[0.5,0.5]): | |
super(OctConv, self).__init__() | |
# Get layer parameters | |
self.alpha_in, self.alpha_out = alphas | |
assert 0 <= self.alpha_in <= 1 and 0 <= self.alpha_in <= 1, \ | |
"Alphas must be in interval [0, 1]" | |
self.kernel_size = kernel_size | |
self.stride = stride |
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from __future__ import print_function, absolute_import | |
__all__ = ['accuracy'] | |
def accuracy(output, target, topk=(1,)): | |
"""Computes the precision@k for the specified values of k""" | |
maxk = max(topk) | |
batch_size = target.size(0) | |
_, pred = output.topk(maxk, 1, True, True) |