From 94777fc88663cee16fd68a9310b7ffce9e49a80b Mon Sep 17 00:00:00 2001 From: zhangyi Date: Mon, 18 May 2020 10:14:49 +0800 Subject: [PATCH] add links to Gitee repository in tutorials and add a picture named logo_source.png --- resource/logo_source.png | Bin 0 -> 3030 bytes .../advanced_use/computer_vision_application.md | 2 ++ .../customized_debugging_information.md | 3 +++ .../advanced_use/distributed_training.md | 2 ++ .../advanced_use/mindspore_cpu_win_install.md | 2 ++ .../source_en/advanced_use/mixed_precision.md | 2 ++ .../source_en/advanced_use/model_security.md | 2 ++ .../source_en/advanced_use/nlp_application.md | 2 ++ .../advanced_use/on_device_inference.md | 2 ++ .../advanced_use/visualization_tutorials.md | 2 ++ tutorials/source_en/quick_start/quick_start.md | 2 ++ .../use/data_preparation/converting_datasets.md | 2 ++ .../data_processing_and_augmentation.md | 2 ++ .../use/data_preparation/loading_the_datasets.md | 2 ++ .../source_en/use/debugging_in_pynative_mode.md | 2 ++ .../use/saving_and_loading_model_parameters.md | 1 + .../checkpoint_for_hybrid_parallel.md | 2 ++ .../advanced_use/computer_vision_application.md | 2 ++ .../customized_debugging_information.md | 3 +++ .../advanced_use/distributed_training.md | 2 ++ .../advanced_use/mindspore_cpu_win_install.md | 2 ++ .../source_zh_cn/advanced_use/mixed_precision.md | 2 ++ .../source_zh_cn/advanced_use/model_security.md | 2 ++ .../advanced_use/network_migration.md | 2 ++ .../source_zh_cn/advanced_use/nlp_application.md | 2 ++ .../advanced_use/on_device_inference.md | 2 ++ .../advanced_use/use_on_the_cloud.md | 2 ++ .../advanced_use/visualization_tutorials.md | 2 ++ .../source_zh_cn/quick_start/quick_start.md | 2 ++ .../use/data_preparation/converting_datasets.md | 2 ++ .../data_processing_and_augmentation.md | 2 ++ .../use/data_preparation/loading_the_datasets.md | 2 ++ .../use/debugging_in_pynative_mode.md | 2 ++ .../use/saving_and_loading_model_parameters.md | 2 ++ 34 files changed, 67 insertions(+) create mode 100644 resource/logo_source.png diff --git a/resource/logo_source.png b/resource/logo_source.png new file mode 100644 index 0000000000000000000000000000000000000000..7240ef4e5e49b975bb70dd3d27ae9f273f7e2172 GIT binary patch literal 3030 zcmV;{3n}!8P)6DFYxA}Cd+ls+bArs3!UjZ%7&y1+vQLqfZk#K96XTaZDbU-kO{fxx+E zYuCKw8FQme;*K&z8jLxrJ|<=sVcCv-D1W+t!=^jG^f&wNsd(W;teAqU^Fcsq~-M{%mI!Fo8L^i%AkUHe`H+c35iQBy19QDEXL}S&v~D$*PMk z`!O&NH+W3kz%d90Pk_Ky&D)--qL`RjPcoUj0;m8+fjn-oB)q)i-Q(Q@p~HcAdlvKg zqs%Zb1Qy^1jRlN&Do0BNWZF>pOZlxxAWN8Dzsd7K-tFlsCL)zv0+4YFag<;&A4?p>AS zRPaAM}ILh_9*gJur?0YPX{ z39LAF=(KujIMzPIzZxo8Qe$EtQr=PkwI)ltES{UDwqvG_Y-0r%d@{tZ+Xc3+M6mPi zVOz6HRI2ZKUnbzQ?~iZ0tJ9(zxNt#)ZEu_)qRpbotxw0BXQQ2G6Iq;(*}&LxL4qljig=UHvB6T8sT}xNqqK(g*owOB-Z> z%(dt9}QL-6{5T8Z@UZo@q1rUbdWNj>UTmO_~PsycE^HoJHF} zim!d+d{zM6ZTb}~Op+6H15N3qTVLS|OBeD$*55)E#xTO(;8x>FooXt1w!*tHizux)EE+p1DL_{|iV>_VQ( zT0H%`Q|!@wk$CdsIf1bKAhGRm;MiI}irEUuVSIhpDP~XeIkKE5L$3?KD98GtskWRe zY>PdL=E(c~+@71y)7P6pUnAOx8mp51ywtrE)lV%^E04Yk6}D;#0O2I2H}&Od?T1WV ziuKJ&T087;nZjUu`JCW5kXe|FC@YiA-a`WFQmkKUaIC{Fw3V%&&#F4X-afsKOeU+B zB@uliY<#MZb#GXJNpt-eZKn+~2#)34yqsgUQl>B$3oS#Vk`{T}G zhX}il&7bzUV{`jg%?N$8JzW+xRz-atuYL;BI4Km=KI2Sx5^Qa?V4+EK|1ev7bv^il z?d5w%*xm_?o73D?A5q>*hd#78jzP1N_v{MxbPA|5aau<>6j4XmAkqd)>&m%U=KBQ4 z5q#9AwmqM(r)8aT?z+K*PQ`x*z+}}jqfn-$**%_ETx}x@Lp6Jc1%ITq; zd)BA;c*_7=`huF8E7Sa9nZH;5xOIRZ?R6J)T?f#*tB=PH`uVF?EaJ+8ifqw59$91X z@{_0eyI(BG7tiB`8-vHdJ2c<)wpG6*SFKpY`g)nOcyfzi^_mnH0srn0eECwv_s&y% z`?cUu2kV3Chu%Jf`>vzc8EY(CclGgD|2!V?`~@O?^f6d-YnqmYy4?3mZ==xuqT=o7 zbs*T!Qu=e@k9VHG7B~Y81A{=$yAI+06z41;aKGyb?BSAYHuV%6shF5q&6c~XO9f6I zH*g#X9u7D{1mB`DF`q-+k9mHQvH*eO=)4el1IkrdOw4R2pC9TcA~?n(5IFYP(Hv!o zj4F$Xne7anJoI0}D^1bW2K3*mSwp`u%I7_-%3@+>GoyAs|DRVM-iG_3Url-d1qcMr zzAZoaZ9~hW`Lekccb1V{oJf|js#nC*2N2%OtApDEsPF-s|?{xahKC_j=j! zqWh`)D^bgh;vP54Q?*mT0Pcy}2=0m6DE>+m`a?DcS1F?}?x=b?OcE+*+;r>h(bwa94m3;`>pQyd4aftF)qR#g` zZs5qHXSw zU3p}R+@?Wz#ewL+Df5yHnmAZuW(zVXWbmj#B;_HZ0zk^tK#5vuBvG=Mn3;^e^-@GiFc%fn9nk5K&U}dG+-p-34l^%O6g-_W*S8U!lRTvCMG5(CgxM( YfBKt2oNm08M*si-07*qoM6N<$f_6{u&j0`b literal 0 HcmV?d00001 diff --git a/tutorials/source_en/advanced_use/computer_vision_application.md b/tutorials/source_en/advanced_use/computer_vision_application.md index 388e9816..66c80826 100644 --- a/tutorials/source_en/advanced_use/computer_vision_application.md +++ b/tutorials/source_en/advanced_use/computer_vision_application.md @@ -16,6 +16,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/computer_vision_application.md) + ## Overview Computer vision is the most widely researched and mature technology field of deep learning, and is widely used in scenarios such as mobile phone photographing, intelligent security protection, and automated driving. Since AlexNet won the ImageNet competition in 2012, deep learning has greatly promoted the development of the computer vision field. Almost all the most advanced computer vision algorithms are related to deep learning. Deep neural network can extract image features layer by layer and retain local invariance. It is widely used in visual tasks such as classification, detection, segmentation, tracking, retrieval, recognition, promotion, and reconstruction. diff --git a/tutorials/source_en/advanced_use/customized_debugging_information.md b/tutorials/source_en/advanced_use/customized_debugging_information.md index feba4f50..5c131d5b 100644 --- a/tutorials/source_en/advanced_use/customized_debugging_information.md +++ b/tutorials/source_en/advanced_use/customized_debugging_information.md @@ -13,6 +13,9 @@ - [Log-related Environment Variables and Configurations](#log-related-environment-variables-and-configurations) + +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/customized_debugging_information.md) + ## Overview This section describes how to use the customized capabilities provided by MindSpore, such as callback, metrics, and log printing, to help you quickly debug the training network. diff --git a/tutorials/source_en/advanced_use/distributed_training.md b/tutorials/source_en/advanced_use/distributed_training.md index 0c14495a..147ba687 100644 --- a/tutorials/source_en/advanced_use/distributed_training.md +++ b/tutorials/source_en/advanced_use/distributed_training.md @@ -17,6 +17,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/distributed_training.md) + ## Overview MindSpore supports `DATA_PARALLEL` and `AUTO_PARALLEL`. Automatic parallel is a distributed parallel mode that integrates data parallel, model parallel, and hybrid parallel. It can automatically establish cost models and select a parallel mode for users. diff --git a/tutorials/source_en/advanced_use/mindspore_cpu_win_install.md b/tutorials/source_en/advanced_use/mindspore_cpu_win_install.md index 81aef71b..88476fab 100644 --- a/tutorials/source_en/advanced_use/mindspore_cpu_win_install.md +++ b/tutorials/source_en/advanced_use/mindspore_cpu_win_install.md @@ -14,6 +14,8 @@ This document describes how to quickly install MindSpore on a Windows system wit +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/mindspore_cpu_win_install.md) + ## Environment Requirements ### System Requirements and Software Dependencies diff --git a/tutorials/source_en/advanced_use/mixed_precision.md b/tutorials/source_en/advanced_use/mixed_precision.md index 64e0ae52..d9966421 100644 --- a/tutorials/source_en/advanced_use/mixed_precision.md +++ b/tutorials/source_en/advanced_use/mixed_precision.md @@ -10,6 +10,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/mixed_precision.md) + ## Overview The mixed precision training method accelerates the deep learning neural network training process by using both the single-precision and half-precision data formats, and maintains the network precision achieved by the single-precision training at the same time. diff --git a/tutorials/source_en/advanced_use/model_security.md b/tutorials/source_en/advanced_use/model_security.md index 1ecc9389..01a6059d 100644 --- a/tutorials/source_en/advanced_use/model_security.md +++ b/tutorials/source_en/advanced_use/model_security.md @@ -15,6 +15,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/model_security.md) + ## Overview This tutorial describes the model security protection methods provided by MindArmour, helping you quickly use MindArmour and provide certain security protection capabilities for your AI model. diff --git a/tutorials/source_en/advanced_use/nlp_application.md b/tutorials/source_en/advanced_use/nlp_application.md index 9ec0a1de..089d5200 100644 --- a/tutorials/source_en/advanced_use/nlp_application.md +++ b/tutorials/source_en/advanced_use/nlp_application.md @@ -20,6 +20,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/nlp_application.md) + ## Overview Sentiment classification is a subset of text classification in NLP, and is the most basic application of NLP. It is a process of analyzing and inferencing affective states and subjective information, that is, analyzing whether a person's sentiment is positive or negative. diff --git a/tutorials/source_en/advanced_use/on_device_inference.md b/tutorials/source_en/advanced_use/on_device_inference.md index 7a93e30d..431c42d1 100644 --- a/tutorials/source_en/advanced_use/on_device_inference.md +++ b/tutorials/source_en/advanced_use/on_device_inference.md @@ -11,6 +11,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/on_device_inference.md) + ## Overview MindSpore Predict is a lightweight deep neural network inference engine that provides the inference function for models trained by MindSpore on the device side. This tutorial describes how to use and compile MindSpore Predict. diff --git a/tutorials/source_en/advanced_use/visualization_tutorials.md b/tutorials/source_en/advanced_use/visualization_tutorials.md index cbf51241..37fe0066 100644 --- a/tutorials/source_en/advanced_use/visualization_tutorials.md +++ b/tutorials/source_en/advanced_use/visualization_tutorials.md @@ -19,6 +19,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/advanced_use/visualization_tutorials.md) + ## Overview Scalars, images, computational graphs, and model hyperparameters during training are recorded in files and can be viewed on the web page. diff --git a/tutorials/source_en/quick_start/quick_start.md b/tutorials/source_en/quick_start/quick_start.md index c14bacee..fb7e9498 100644 --- a/tutorials/source_en/quick_start/quick_start.md +++ b/tutorials/source_en/quick_start/quick_start.md @@ -2,6 +2,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/quick_start/quick_start.md) + - [Implementing an Image Classification Application](#implementing-an-image-classification-application) - [Overview](#overview) - [Preparations](#preparations) diff --git a/tutorials/source_en/use/data_preparation/converting_datasets.md b/tutorials/source_en/use/data_preparation/converting_datasets.md index 474cd00a..cd311c1f 100644 --- a/tutorials/source_en/use/data_preparation/converting_datasets.md +++ b/tutorials/source_en/use/data_preparation/converting_datasets.md @@ -14,6 +14,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/use/data_preparation/converting_datasets.md) + ## Overview You can convert non-standard datasets and common datasets into the MindSpore data format so that they can be easily loaded to MindSpore for training. In addition, the performance of MindSpore in some scenarios is optimized, which delivers better user experience when you use datasets in the MindSpore data format. diff --git a/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md b/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md index 4a34368b..d31697d5 100644 --- a/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md +++ b/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md @@ -16,6 +16,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md) + ## Overview Data is the basis of deep learning. Data input plays an important role in the deep neural network training. Therefore, after the original dataset is obtained and before data is loaded and trained, data processing or augmentation is often required due to data size and performance restrictions, to obtain optimized data input. diff --git a/tutorials/source_en/use/data_preparation/loading_the_datasets.md b/tutorials/source_en/use/data_preparation/loading_the_datasets.md index 355d673c..e97eddb9 100644 --- a/tutorials/source_en/use/data_preparation/loading_the_datasets.md +++ b/tutorials/source_en/use/data_preparation/loading_the_datasets.md @@ -13,6 +13,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/use/data_preparation/loading_the_datasets.md) + ## Overview MindSpore helps you load common datasets, datasets of specific data formats, or custom datasets. Before loading a dataset, you need to import the required library `mindspore.dataset`. diff --git a/tutorials/source_en/use/debugging_in_pynative_mode.md b/tutorials/source_en/use/debugging_in_pynative_mode.md index 3f9ba9b5..4fc80672 100644 --- a/tutorials/source_en/use/debugging_in_pynative_mode.md +++ b/tutorials/source_en/use/debugging_in_pynative_mode.md @@ -11,6 +11,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/use/debugging_in_pynative_mode.md) + ## Overview MindSpore supports the following running modes which are optimized in terms of debugging or running: diff --git a/tutorials/source_en/use/saving_and_loading_model_parameters.md b/tutorials/source_en/use/saving_and_loading_model_parameters.md index 88d80140..6d321d0c 100644 --- a/tutorials/source_en/use/saving_and_loading_model_parameters.md +++ b/tutorials/source_en/use/saving_and_loading_model_parameters.md @@ -13,6 +13,7 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_en/use/saving_and_loading_model_parameters.md) ## Overview diff --git a/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md b/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md index 3a174e6e..5d055690 100644 --- a/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md +++ b/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md @@ -26,6 +26,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md) + ## 概述 ### 背景 diff --git a/tutorials/source_zh_cn/advanced_use/computer_vision_application.md b/tutorials/source_zh_cn/advanced_use/computer_vision_application.md index 0135c636..79db9460 100644 --- a/tutorials/source_zh_cn/advanced_use/computer_vision_application.md +++ b/tutorials/source_zh_cn/advanced_use/computer_vision_application.md @@ -16,6 +16,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/computer_vision_application.md) + ## 概述 计算机视觉是当前深度学习研究最广泛、落地最成熟的技术领域，在手机拍照、智能安防、自动驾驶等场景有广泛应用。从2012年AlexNet在ImageNet比赛夺冠以来，深度学习深刻推动了计算机视觉领域的发展，当前最先进的计算机视觉算法几乎都是深度学习相关的。深度神经网络可以逐层提取图像特征，并保持局部不变性，被广泛应用于分类、检测、分割、跟踪、检索、识别、提升、重建等视觉任务中。 diff --git a/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md b/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md index 5ea8d27a..bd583bb3 100644 --- a/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md +++ b/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md @@ -12,6 +12,9 @@ - [日志相关的环境变量和配置](#日志相关的环境变量和配置) + +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md) + ## 概述 本文介绍如何使用MindSpore提供的Callback、metrics、print算子、日志打印等自定义能力，帮助用户快速调试训练网络。 diff --git a/tutorials/source_zh_cn/advanced_use/distributed_training.md b/tutorials/source_zh_cn/advanced_use/distributed_training.md index 1582d6ea..4a0fa60e 100644 --- a/tutorials/source_zh_cn/advanced_use/distributed_training.md +++ b/tutorials/source_zh_cn/advanced_use/distributed_training.md @@ -17,6 +17,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/distributed_training.md) + ## 概述 在深度学习中，当数据集和参数量的规模越来越大，训练所需的时间和硬件资源会随之增加，最后会变成制约训练的瓶颈。分布式并行训练，可以降低对内存、计算性能等硬件的需求，是进行训练的重要优化手段。根据并行的原理及模式不同，业界主流的并行类型有以下几种： diff --git a/tutorials/source_zh_cn/advanced_use/mindspore_cpu_win_install.md b/tutorials/source_zh_cn/advanced_use/mindspore_cpu_win_install.md index 4f58546b..3d9c3fbc 100644 --- a/tutorials/source_zh_cn/advanced_use/mindspore_cpu_win_install.md +++ b/tutorials/source_zh_cn/advanced_use/mindspore_cpu_win_install.md @@ -14,6 +14,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/mindspore_cpu_win_install.md) + ## 环境要求 ### 系统要求和软件依赖 diff --git a/tutorials/source_zh_cn/advanced_use/mixed_precision.md b/tutorials/source_zh_cn/advanced_use/mixed_precision.md index b09ba667..b7c66a54 100644 --- a/tutorials/source_zh_cn/advanced_use/mixed_precision.md +++ b/tutorials/source_zh_cn/advanced_use/mixed_precision.md @@ -10,6 +10,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/mixed_precision.md) + ## 概述 混合精度训练方法是通过混合使用单精度和半精度数据格式来加速深度神经网络训练的过程，同时保持了单精度训练所能达到的网络精度。混合精度训练能够加速计算过程，同时减少内存使用和存取，并使得在特定的硬件上可以训练更大的模型或batch size。 diff --git a/tutorials/source_zh_cn/advanced_use/model_security.md b/tutorials/source_zh_cn/advanced_use/model_security.md index 88ed988d..595649d3 100644 --- a/tutorials/source_zh_cn/advanced_use/model_security.md +++ b/tutorials/source_zh_cn/advanced_use/model_security.md @@ -15,6 +15,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/model_security.md) + ## 概述 本教程介绍MindArmour提供的模型安全防护手段，引导您快速使用MindArmour，为您的AI模型提供一定的安全防护能力。 diff --git a/tutorials/source_zh_cn/advanced_use/network_migration.md b/tutorials/source_zh_cn/advanced_use/network_migration.md index 5e3a53a7..0b5619d8 100644 --- a/tutorials/source_zh_cn/advanced_use/network_migration.md +++ b/tutorials/source_zh_cn/advanced_use/network_migration.md @@ -17,6 +17,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/network_migration.md) + ## 概述 你可能已经编写过TensorFlow、PyTorch等框架的脚本，本教程介绍如何将已有的TensorFlow、PyTorch等的网络迁移到MindSpore，包括主要步骤和操作建议，帮助你快速进行网络迁移。 diff --git a/tutorials/source_zh_cn/advanced_use/nlp_application.md b/tutorials/source_zh_cn/advanced_use/nlp_application.md index bc4c7bb1..869a8bf9 100644 --- a/tutorials/source_zh_cn/advanced_use/nlp_application.md +++ b/tutorials/source_zh_cn/advanced_use/nlp_application.md @@ -20,6 +20,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/nlp_application.md) + ## 概述 情感分类是自然语言处理中文本分类问题的子集，属于自然语言处理最基础的应用。它是对带有感情色彩的主观性文本进行分析和推理的过程，即分析说话人的态度，是倾向正面还是反面。 diff --git a/tutorials/source_zh_cn/advanced_use/on_device_inference.md b/tutorials/source_zh_cn/advanced_use/on_device_inference.md index 5830298f..d32e6916 100644 --- a/tutorials/source_zh_cn/advanced_use/on_device_inference.md +++ b/tutorials/source_zh_cn/advanced_use/on_device_inference.md @@ -11,6 +11,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/on_device_inference.md) + ## 概述 MindSpore Predict是一个轻量级的深度神经网络推理引擎，提供了将MindSpore训练出的模型在端侧进行推理的功能。本教程介绍MindSpore Predict的编译方法和使用指南。 diff --git a/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md b/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md index 172505d5..367600fb 100644 --- a/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md +++ b/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md @@ -3,6 +3,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md) + - [在云上使用MindSpore](#在云上使用mindspore) - [概述](#概述) - [准备工作](#准备工作) diff --git a/tutorials/source_zh_cn/advanced_use/visualization_tutorials.md b/tutorials/source_zh_cn/advanced_use/visualization_tutorials.md index a9a8f54d..357194dd 100644 --- a/tutorials/source_zh_cn/advanced_use/visualization_tutorials.md +++ b/tutorials/source_zh_cn/advanced_use/visualization_tutorials.md @@ -24,6 +24,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/visualization_tutorials.md) + ## 概述 训练过程中的标量、图像、计算图以及模型超参等信息记录到文件中，通过可视化界面供用户查看。 diff --git a/tutorials/source_zh_cn/quick_start/quick_start.md b/tutorials/source_zh_cn/quick_start/quick_start.md index 60523885..83fe90ce 100644 --- a/tutorials/source_zh_cn/quick_start/quick_start.md +++ b/tutorials/source_zh_cn/quick_start/quick_start.md @@ -24,6 +24,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/quick_start/quick_start.md) + ## 概述 下面我们通过一个实际样例，带领大家体验MindSpore基础的功能，对于一般的用户而言，完成整个样例实践会持续20~30分钟。 diff --git a/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md b/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md index b8927be9..501a38bc 100644 --- a/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md +++ b/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md @@ -14,6 +14,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md) + ## 概述 用户可以将非标准的数据集和常见的数据集转换为MindSpore数据格式，从而方便地加载到MindSpore中进行训练。同时，MindSpore在部分场景做了性能优化，使用MindSpore数据格式可以获得更好的性能体验。 diff --git a/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md b/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md index 6571a017..836e36e3 100644 --- a/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md +++ b/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md @@ -16,6 +16,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md) + ## 概述 数据是深度学习的基础，有好的数据输入，可以对整个深度神经网络训练起到非常积极的作用。所以在获取到原始的数据集后，数据加载训练前，因为数据量、性能等等限制，往往会需要先进行数据处理或者数据增强，从而获得更加优化的数据输入。 diff --git a/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md b/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md index f46f84ae..07e4af0f 100644 --- a/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md +++ b/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md @@ -13,6 +13,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md) + ## 概述 MindSpore可以帮助你加载常见的数据集、特定数据格式的数据集或自定义的数据集。加载数据集时，需先导入所需要依赖的库`mindspore.dataset`。 diff --git a/tutorials/source_zh_cn/use/debugging_in_pynative_mode.md b/tutorials/source_zh_cn/use/debugging_in_pynative_mode.md index 9a9e9e67..c22bb340 100644 --- a/tutorials/source_zh_cn/use/debugging_in_pynative_mode.md +++ b/tutorials/source_zh_cn/use/debugging_in_pynative_mode.md @@ -11,6 +11,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/use/debugging_in_pynative_mode.md) + ## 概述 MindSpore支持两种运行模式，在调试或者运行方面做了不同的优化: diff --git a/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md b/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md index 0bdf8fa7..c79003ab 100644 --- a/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md +++ b/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md @@ -13,6 +13,8 @@ +[![source](/resource/logo_source.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md) + ## 概述 在模型训练过程中，可以添加检查点(CheckPoint)用于保存模型的参数，以便进行推理及中断后再训练使用。 -- GitLab