sklearn tsne + matplotlib scatter

import os import torch import clip import matplotlib . pyplot as plt from PIL import Image from sklearn . manifold import TSNE from tqdm import tqdm from collections import defaultdict from random import shuffle   X = torch . cat ( X , dim = 0 ) X_emb = TSNE ( init = "pca" , perplexity = 30.0 ). fit_transform ( X . cpu ()) labels = [ "source" , "z_star/foggy-1" , "z_star/foggy-2" , "z_star/foggy-3" , "z_bar/foggy-1" , "z_bar/foggy-2" , "z_bar/foggy-3" ] fig , ax = plt . subplots ( 1 ) group_len = len ( zs ) for i in range ( 7 ): ax . scatter ( X_emb [ i * group_len :( i + 1 )* group_len , 0 ], X_emb [ i * group_len :( i + 1 )* group_len , 1 ], label = labels [ i ], s = 4 ) ax . legend () fig .savefig( "temp.png" )

load bert pretrained weight to detr encoder

# Example python script of loading BERT-base model to DETR # Create DETR import argparse from models import build_model from util.default_args import get_args_parser parser = argparse.ArgumentParser(parents=[get_args_parser()]) args = parser.parse_known_args()[0] args.model = "detr" args.hidden_dim = 768 args.dim_feedforward = 3072 args.lr = 1e-4 args.lr_backbone = 1e-5 args.num_queries = 100 args.enc_layers = 12 args.nheads = 12 model, criterion, postprocessors = build_model(args) # Load BERT import torch bert = torch.hub.load('huggingface/pytorch-transformers', 'model', 'bert-base-uncased') bert_enc = bert.encoder.state_dict() # Convert keys dict_bert2detr = {} for i in range(args.enc_layers):     key = "layers.{}.self_attn.in_proj_weight".format(i)     dict_bert2detr[key] = torch.cat([bert_enc["layer.{}.attention.self.query.weight".format(i)], [bert_enc["layer.{}.attention.self.key.weight".format(i)], [bert_enc["la...

matplotlib.pyplot non-interative backend

 export MPLBACKEND=agg

VS Code 실행 파일 기준으로 경로 설정하기

 "cwd": "${fileDirname}"

Download multiple file from google drive via gdown

 1. At the Google drive page, open console and type: $$("[data-id]").map((el) => 'https://drive.google.com/uc?id=' + el.getAttribute('data-id')).join(" ") 2. Copy links 3. Open python import os links = COPIED_STRING links = list(map(lambda x: x.split("id=")[-1], links.split(" "))) for link in links:     os.system("gdown {}".format(link)) ref: https://olegkhomenko.medium.com/how-to-download-multiple-files-from-google-drive-using-terminal-7f0f2ee357b8

docker run 인자 확인하기

 docker inspect   --format "$(curl -s https://gist.githubusercontent.com/efrecon/8ce9c75d518b6eb863f667442d7bc679/raw/run.tpl)"   [container name]

docker + matplotlib // cv2 추가 install

  도커 밖에서 xhost +local:'docker inspect --format='{{.Config.Hostname}}' bdba249440d4' 도커 생성 시 --env="DISPLAY" --env="QT_X11_NO_MITSHM=1" --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" -e NVIDIA_DRIVER_CAPABILITIES=graphics,utility,compute apt install python3-tk opencv: apt install libgl1-mesa-glx libglib2.0-0 -y