Package: tinyms
TinyMSEnglish |查看中文TinyMS is an Easy-to-Use deep learning framework development toolkit based onMindSpore, designed to provide quick-start guidelines for machine learning beginners.InstallationDistributionVersionCommandPyPIx.y.zpip install tinyms==x.y.zlatestpip install git+https://github.com/tinyms-ai/tinyms.gitDockerx.y.zdocker pull tinyms==x.y.zlatest-NOTICE:Thex.y.zversion shown above should be replaced with the real version number.Please checkout theinstall documentto quickly install or upgrade TinyMS project.Quick startHave no idea what to do with TinyMS❓ See theQuick Startto implement the image classification application in one minutes❗Besides, here are some use cases listed to demonstrate how TinyMS simplifies the code flow for users.Data loading and preprocessfromtinyms.dataimportMnistDataset,download_datasetfromtinyms.visionimportmnist_transformdata_path=download_dataset('mnist')mnist_ds=MnistDataset(data_path,shuffle=True)mnist_ds=mnist_transform.apply_ds(mnist_ds)Network constructionfromtinyms.modelimportlenet5net=lenet5(class_num=10)Model train/evaluationfromtinyms.modelimportModelmodel=Model(net)model.compile(loss_fn=net_loss,optimizer=net_opt,metrics=net_metrics)model.train(epoch_size,train_dataset)model.save_checkpoint('./checkpoint_lenet.ckpt')···model.load_checkpoint('./checkpoint_lenet.ckpt')model.eval(eval_dataset)Model predictionfromPILimportImageimporttinymsastsfromtinyms.modelimportModel,lenet5fromtinyms.visionimportmnist_transformimg=Image.open(img_path)img=mnist_transform(img)net=lenet5(class_num=10)model=Model(net)model.load_checkpoint('./checkpoint_lenet.ckpt')input=ts.expand_dims(ts.array(img),0)res=model.predict(input).asnumpy()print("The label is:",mnist_transform.postprocess(res))API documentationIf you are interested in learning TinyMS API, please find TinyMS Python API inAPI Documentation.TutorialFor a more detailed step-by-step video tutorial, please refer to the following website.EpisodeTitleContentDocsStatusUpdate TimeEP01How to learn Deep Learning? The Most Efficient Way For Beginners!Teacher's profile+DeepLearning Course Introduction-Published2021.3.30EP02How we teach computers to understand pictures? Three Ways to Install TinyMSIt uncovers the magic of computer vision + three ways to install TinyMS (Ubuntu, Win10, Docker)TinyMS Installation For BeginnersPublished2020.3.31EP03Learn Shell Script in 30 MinutesIt covers the essential concepts such as using variables, basic operators, loops & functions and so on. It also gives you an insight by scaling down some real-time scenarios and demonstrating them using the docker container.Learn Shell Script in 30 Minutes (doc)Published2020.4.1EP04Learn Python in 30 Minutes(Part I.)Python installation, basic syntax, primitive data types and operatorsLearn Python in 30 MinutesPublished2021.4.23EP05Learn Python in 30 Minutes(Part II.)Python conditional statements, loop statements, iterators, generators, functions, class, module, advanced usages, and several most commonly used Python libraries in deep learningLearn Python in 30 MinutesPublished2022.1.10CommunityFor any developers who are not familiar with how TinyMS community works, please find theContributing Guidelinesto get started.Release NotesThe release notes, see ourRELEASE.LicenseApache License 2.0