fix: Multiple Getter Calls in class-transformertype: fixIssues describing a broken feature. #1707 openedMay 31, 2024byJHyeok 1 fix: incorrect property name in validation messages when using @Expose()status: needs triageIssues which needs to be reproduced to be verified report.type: fixIssues des...
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference. - TransformerEngine/set
Basic current measurement was performed using a class 0.1 current transformer together with an event recorder. The basic measurement was supplemented by the recording of the current derivative using a Rogowski coil [35]. Due to the dependence of the transformer inrush current on the initial phase ...
classClassNameTransformer:ValueTransformer{overrideclassfunctransformedValueClass() ->AnyClass{returnNSString.self}overrideclassfuncallowsReverseTransformation() ->Bool{returnfalse}overridefunctransformedValue(_value:Any?) ->Any?{return(valueasAnyObject).className}}extensionNSValueTransformerName{staticletclassNam...
In [18] class MyDataset(Dataset): """ 步骤一:继承paddle.io.Dataset类 """ def __init__(self, eng,fre): """ 步骤二:实现构造函数,定义数据集大小 """ super(MyDataset, self).__init__() self.eng = eng self.fre = fre def __getitem__(self, index): """ 步骤三:实现__getitem__...
Li W, Wang L, Xu J, Huo J, Gao Y, Luo J (2019) Revisiting local descriptor based image-to-class measure for few-shot learning. In: 2019 IEEE/CVF conference on computer vision and pattern recognition, pp 7260–7268 Liu Y, Schiele B, Sun Q (2020) An ensemble of epoch-wise empirica...
2. Oil drains of heat dispersion aer scientifically used in the winding, and the surface of heat dissipation is increased, so the tempertature is reduced and the ability of over-load is improved.HV windings HV winding is manufactured with high quality copper ...
迭代器 class MyIterator(data.Iterator): def create_batches(self): if self.train: def pool(d, random_shuffler): for p in data.batch(d, self.batch_size * 100): p_batch = data.batch( sorted(p, key=self.sort_key), self.batch_size, self.batch_size_fn) ...
In [2] class Compose: """ Do transformation on input data with corresponding pre-processing and augmentation operations. The shape of input data to all operations is [height, width, channels]. Args: transforms (list): A list contains data pre-processing or augmentation. Empty list means only...
classification import ClassificationModel import pandas as pd # Train and Evaluation data needs to be in a Pandas Dataframe of two columns. The first column is the text with type str, and the second column is the label with type int. train_data = [['Example sentence belonging to class 1'...