1.2 数据预处理 数据的偏离程度以及数据之间的关联性会拉大整体数据标准差、造成统计偏见以及使数据带有...
scale_fn:自定义的scaling policy,通过只包含有1个参数的lambda函数定义。0 <= scale_fn(x) <= 1 for all x >= 0. 默认:None。如果定义了scale_fn, 则忽略 mode参数。 scale_mode (str):{‘cycle’, ‘iterations’}中的一个. Defines whether scale_fn is evaluated on cycle number or cycle itera...
mode:三种模式,‘triangular’,‘triangular2’,‘exp_range‘。如果设定了scale_fn,那么这个参数就没用了。 gamma:‘exp_range‘模式下的更新常数。 scale_fn:自定义放缩函数,保证值为[0,1]。 scale_mode:‘cycle’,‘iterations’ cycle_momentum,base_momentum, max_omentum:LR更新的动量。 last_epoch:-1为...
is_channel_first: false is_scale: true mean: [0.485,0.456,0.406] std: [0.229, 0.224,0.225] !ResizeImage interp: 1 max_size: 1500 target_size: 1000 use_cv2: true !Permute channel_first: true to_bgr: false batch_transforms: !PadBatch pad_to_stride: 32 use_padded_im_info: true batch...
3)scale操作 4)facet操作 5)labs操作 6)theme操作 当我们熟悉ggplot2包这些知识后,我们就可以使用它设计和实现一系列有用的图形,以帮助我们获取数据洞见和增强沟通效果。 学习资料: https://rkabacoff.github.io/datavis/IntroGGPLOT.html 02 如何使用tidyverse包绘制Pair Plot?
def embedding_layer(input): emb = fluid.embedding( input=input, is_sparse=True, is_distributed=is_distributed, size=[self.sparse_feature_number + 1, 1], padding_idx=0, param_attr=fluid.ParamAttr( initializer=fluid.initializer.TruncatedNormalInitializer( loc=0.0, scale=init_value_), regularizer...
You can also try more stronger model pre-trained on large-scale image dataset, i.e., MoCo, DetCo, which may get better results. bash tools/dist_train.sh configs/train/mixed_train_res18_d1_l2_rec_ytv_fly.py 4 License This work is licensed under MIT license. See the LICENSE for ...
这是很有可能出现:OFFSCALE的字样。那就说明你需要在EFIs上把地图调大一些。最恐怖的是,你看到了红色标识,那说明飞机离你太近了。赶快停防撞系统指挥,他叫你爬升你就怕,叫你下降你就降!则是咋PFD会显示,别闲地往下拉,看图,PFD是叫你向上爬!!这时你必须在20秒至30秒做出动作!不然你就911了! 9楼2015-04-...
In this work, we present the theoretical and computational formulations of a multiscale crystal defect dynamics (MCDD) for the simulation of crystal defect... S Li,B Ren,H Minaki - 《Philosophical Magazine》 被引量: 16发表: 2014年 Tractable term-structure models and the zero lower bound We...
Finally, we show numerically the appropriateness of our proposed approximate solution for large scale problems in comparison with other recently proposed approximate solutions. The numerical results show that our proposed algorithm produces significantly more accurate solutions. 展开 ...