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solutions for errors i've met
터미널 에러 내용으로 검색하니 메모리 할당 부족이라는 글밖에 없어서 삽질 좀 했다.
다음 코드로 중복 라이브러리를 허용해준다.
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'
pip install --ignore-installed psutil
pip install --users transformers==3.5.1
-> train_loader = DataLoader(train_dataset, batch_size=4, shuffle=True)
AttributeError
train_loader = DataLoader(dataset=train_dataset, batch_size=4, shuffle=True)
dataset=
라고 attrbute name 명시해주니까 해결됨
[email protected]: Permission denied (publickey).
fatal: Could not read from remote repository.
git remote origin을 삭제하고 다시 등록해도,
git remote -v
확인시 git 계정이 정상적으로 등록되었음에도 에러가 계속 발생함.
origin 주소를 ssh -> http 주소로 변경한다.
참고: https://velog.io/@marksen/Git-fatal-Could-not-read-from-remote-repository
pip install ...
--user
option when installing a libpip install --user ...
import read_roi
from pathlib import Path
file_path = Path('C:\workspace\datasets\file_name.roi')
read_roi.read_roi_file( file_path ) # this is recognized as 'Nonetype' object
read_roi.read_roi_file( str(file_path) )
RuntimeError: Given input size: (512x1x1). Calculated output size: (512x0x0). Output size is too small
This error occurs when the input size is smaller than the kernel size.
In my case, I tried to run VGG16 on MNIST dataset, there were 5 pooling layers with 2x2 kernel.
The original image size of MNIST is 28x28, and it becomes 0x0 after 5th pooling layer.
So the 0x0 shaped feature map couldn't be put on remain layers.
You just need to make the image size bigger than the kernel size of pooling layer where error occurs.
I choosed Choice 1.
For option 1, I added transforms.Resize()
to increase the input_size
of a image. (Pytorch)
# Data load
transform = transforms.Compose([transforms.Resize(32), transforms.ToTensor(), transforms.Normalize(mean=(0.5,), std=(0.5,))])
train_dataset = datasets.MNIST(download=True, root='./', train=True, transform=transform)
train_loader = DataLoader(train_dataset, batch_size=batch_size,shuffle=True, num_workers=0)
test_dataset = datasets.MNIST(download=True, root='./', train=False, transform=transform)
test_loader = DataLoader(test_dataset, batch_size=batch_size,shuffle=False, num_workers=0)
For option 2 & 3, you can consider the fomula that calulates the size(H, W) of a output feature.
- 오류 내용: UnicodeDecodeError: 'cp949' codec can't decode byte 0xe2 in position 1128: illegal multibyte sequence
- 발생 상황: conda env에 Python 설치하면, 위 오류에 의해 pip 명령어 안 먹힘..
- 원인: encoding 문제. cp949(euc-kr)로 설정되어있는 것을 utf-8로 바꿔줘야 한다.
utf-8
은 전 세계 언어를, euc-kr
과 cp949
은 한국어만 표현할 수 있음.
다음 두 가지 파일 수정.
단, 디렉토리는 로컬에 설치된 Python이 아닌, 오류가 발생한 env의 Python Lib여야 함.
1. C:\Users\유저이름\anaconda3\envs\yolov5\Lib\distutils\text_file.py
line #115 : encoding='utf-8' 추가
2. C:\Users\유저이름\anaconda3\envs\yolov5\Lib\configparser.py
line #695 : encoding='utf-8' 수정
I tried reinstalling the 'Python Extension Pack' and 'Pylance' lib a few times, but it didn't work.
put the sentence below to the vscode setting file.
"python.pylanceLspNotebooksEnabled": false
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