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import datetime | |
import linecache | |
import os | |
import pynvml3 | |
import torch | |
print_tensor_sizes = True | |
last_tensor_sizes = set() | |
gpu_profile_fn = f'{datetime.datetime.now():%d-%b-%y-%H:%M:%S}-gpu_mem_prof.txt' |
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from tqdm import tqdm_notebook as tqdm | |
from joblib import Parallel, delayed | |
import time | |
import random | |
def func(x): | |
time.sleep(random.randint(1, 10)) | |
return x |
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def run_release_gpu(func): | |
def parallel_wrapper(output_dict, *argv, **kwargs): | |
ret = func(*argv, **kwargs) | |
if ret is not None: | |
output_dict['ret'] = ret | |
def outer_wrapper(*argv, **kwargs): | |
same_process = kwargs.pop('same_process', False) | |
if same_process: | |
return func(*argv, **kwargs) |
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find . -name '*.png' | while read line; do echo ${line}; convert -resize 70% ${line} ${line}.small.png; pngquant --speed 1 ${line}.small.png -o ${line}.quant.png; done | |
find . -name '*.small.png' | while read line; do rm $line; done | |
read -p "Press [Enter] if you are happy with *.quant.png images, otherwise press Ctrl-C." | |
find . -name '*.quant.png' | while read line; do mv ${line} ${line:0:-10}; done | |
for EXT in png pdf; do find -name "*.${EXT}" | while read line; do echo $line; done; done | while read line; do if ! grep -q -r --include \*.tex ${line#*/} .; then echo ${line}; rm ${line}; fi; done |
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use std::error::Error; | |
enum TaskError<'a, C> { | |
CustomError(C), | |
StdError(Box<dyn Error + 'a>) | |
} | |
type TaskResult<'a, R, E> = std::result::Result<R, TaskError<'a, E>>; | |
impl<'a, E: Error + 'a, C> From<E> for TaskError<'a, C> { |
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a=(x y z); b=(q w e); for i in ${!a[@]}; do echo ${a[i]}-${b[i]}; done |
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import tensorflow as tf | |
import tensorflow_datasets as tfds | |
spec = tfds.features.FeaturesDict({ | |
'image': tfds.features.Tensor(shape=(28, 28, 1), dtype=tf.float32), | |
'label': tfds.features.ClassLabel(names=['no', 'yes']), | |
'metadata': { | |
'id': tf.int64, | |
'language': tf.string, | |
}, |
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import sys | |
import glob | |
import tqdm | |
import imageio | |
import matplotlib.pyplot as plt | |
import numpy as np | |
import tensorflow as tf |
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#!/usr/bin/bash | |
watch "nvidia-smi | tail -n +7; nvidia-smi | nvidia-smi | sed -n '/| Processes:/,\$p' | tail -n +4 | head -n -1 | awk '{print \$3}' | while read line; do ps a -o pid,user | grep \$line | grep -v grep; done | |
" |
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