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File size: 2,948 Bytes
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import json\n",
"from os.path import join"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"OUT_DIR = 'output/'\n",
"EXP_DIR = join(OUT_DIR, 'semsup_descs_amzn13k_curie_nocoil', 'predictions')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/n/fs/nlp-pranjal/SemSup-LMLC/training\n"
]
}
],
"source": [
"%cd .."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"files = dict()\n",
"for file in os.listdir(EXP_DIR):\n",
" t = float(file.split('_')[-1].replace('.pkl',''))\n",
" if t not in files:\n",
" files[t] = []\n",
" files[t] += [join(EXP_DIR, file)]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"21.792958695441484"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import itertools\n",
"tsize = 0\n",
"for file in itertools.chain(*files.values()):\n",
" tsize += os.path.getsize(file)\n",
"tsize/ (1024**3)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"files = {k:files[k] for k in sorted(files.keys())}"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"10.170047391206026"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import random\n",
"tsize = 0\n",
"for k in sorted(list(files.keys()))[10:]:\n",
" if random.random() > 0.6:\n",
" continue\n",
" for f in files[k]:\n",
" tsize += os.path.getsize(f)\n",
" os.remove(f)\n",
"tsize/ (1024**3)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"interpreter": {
"hash": "90fcbf6f06d9a30c70fdaff45e14c5534421a599dc22a7267c486c9cb67dea6d"
},
"kernelspec": {
"display_name": "Python 3.9.12 ('base')",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}
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