Torch Train with Mulit GPU
多GPU训练 1. nn.DataParallel devices = [torch.device(f'cuda:{i}') for i in range(torch.cuda.device_count())] net = nn.DataParallel(net, device_ids=devices) for epoch in range(num_epochs): for X, y...
Soong
Torch Train with Epoch
使用epoch train def train_epoch(model, trainer, loss_fn, dataloader, device): """ train一个epoch return: 平均loss """ model.train() loss_sum = 0.0 for X, y in dataloader: ...
Torch Tricks
torch tricks Set Seed import numpy as np import torch import random def set_seed(seed): np.random.seed(seed) random.seed(seed) torch.manual_seed(seed) if torch.cuda.is_available():...
Torch Modify Model
Modify Model torch model is a callable object, u can visit it as a list or tuple change model to a nn.Sequential model_seq = nn.Sequential(model.children()[:]) get any layer`s output create_...
Torch Custom learning rate scheduler
Learning rate scheduler 带warmup的learning rate随余弦函数变化的scheduler Warmup Phase lr从0线性增加init_lr Decay Phase lr随cos逐步降低到0 通过调整num_cycles决定经过cos的多少个周期 import math import torch...
Torch Custom Criterion
Criterion LabelSmoothedCrossEntropy class LabelSmoothedCrossEntropyCriterion(nn.Module): def __init__(self, smoothing, ignore_index=None, reduce=True): super().__init__() self....
Torch lr scheduler tutorial
PyTorch学习率调整策略 PyTorch中学习率调整策略通过 torch.optim.lr_scheduler 接口实现, 一共9种方法, 可分为三大类: a. 有序调整:等间隔Step调整、指定多间隔MultiStep调整学习率、指数衰减调整Exponential、余弦退火CosineAnnealing b. 自适应调整:自适应调整ReduceLROnPlateau c. 自定义...
cv2 tools - opencv cv2 tutorial tools
cv2 tools stack imgs import cv2 import numpy as np def stackImages(scale, imgArray): rows = len(imgArray) cols = len(imgArray[0]) rowsAvailable = isinstance(imgArray[0], list) wid...
Warping Perspective - opencv cv2 tutorial chapter5
chapter5 import cv2 import numpy as np img = cv2.imread('Resources/cards.jpg') width, height = 250, 350 plt1 = np.float32([[111, 219], [287, 188], [154, 482], [352, 440]]) plt2 = np.float32([[0,...
Virtual Painting - opencv cv2 tutorial project1
project1 import cv2 import numpy as np frameWidth = 480 frameHeight = 560 cap = cv2.VideoCapture(0) cap.set(3, frameWidth) cap.set(4, frameHeight) cap.set(10, 130) config = { 'colorMask': [[...