MyCaffe 0.10.0.122-beta1

.NET Framework 4.0 This package targets .NET Framework 4.0. The package is compatible with this framework or higher.
This is a prerelease version of MyCaffe.
There is a newer version of this package available.
See the version list below for details. 
dotnet add package MyCaffe --version 0.10.0.122-beta1                

                    
                

            
NuGet\Install-Package MyCaffe -Version 0.10.0.122-beta1
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="MyCaffe" Version="0.10.0.122-beta1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add MyCaffe --version 0.10.0.122-beta1                

                    
                

            
#r "nuget: MyCaffe, 0.10.0.122-beta1"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
// Install MyCaffe as a Cake Addin
#addin nuget:?package=MyCaffe&version=0.10.0.122-beta1&prerelease

// Install MyCaffe as a Cake Tool
#tool nuget:?package=MyCaffe&version=0.10.0.122-beta1&prerelease

MyCaffe AI Platform and Test Application (CUDA 10.0.130, cuDNN 7.4.1) Release with LSTM Recurrent Learning Support and Char-RNN

CUDA 10.0.130, cuDNN 7.4.1, nvapi 410, Native Caffe up to 10/24/2018, Windows 10-1803, Driver 416.94

IMPORTANT NOTE: When using TCC mode, we recommend that ALL headless GPU’s are placed in TCC mode for we have experienced stability issues when using a mix of TCC and WDM modes with headless GPU’s.

MyCaffe now supports Recurrent Learning using CUDA 10 and cuDNN 7.4.1 to implement the Char-RNN described by A. Karpathy [1] and originally implemented on Caffe [2] by adepierre [3].

This release of the MyCaffe AI Platform and Test Applications has the following new additions: • CUDA 10.0.130/cuDNN 7.4.1 now supported (with driver 416.94). • RTX 2080 ti supported. • Added support for custom gyms. • Added new DataGeneral gym. • Added new streaming database support. • Added new data preprocessing support with CUDA plugins. • Added new CUDA level extension support. • Added support for prototxt comments. • Added new TrainerRNN for Recurrent Learning training. • Added new Char-RNN model that learns Shakespeare. • Added new WAV-RNN model for learning audio.

The following bug fixes are in this release: • Fixed bug in Input layer not loading shape from prototxt. • Fixed bug related to mixed types in saved weights. • Improved blob sharing in Bias, Embed, LSTMSimple, PreLU and Scale layers. • Improved AutoTest sub-item status reporting.

Easily create the CIFAR-10 and MNIST datasets using the MyCaffe Test Application which you can download from the MyCaffe GitHub site.

Create and train the Policy Gradient Reinforcement Learning, Auto-Encoder, DANN and ResNet models by following step-by-step instructions in the SignalPop Tutorials. And, to see other cool examples that show what MyCaffe can do, see the SignalPop Examples.

If you would like to visually design, develop, test and debug your models, see the SignalPop AI Designer specifically designed to enhance your MyCaffe deep learning.

Also, check out the SignalPop Universal Miner that not only gives you detailed information on each of your GPU's (such as temperature, fan speed, overclock, and usage), it allows you to easily start mining Ethereum. When not training AI, put those GPU's to use making some Ether - never let a good GPU go to waste!

Happy ‘deep’ learning!

[1] A. Karpathy, The Unreasonable Effectiveness of Recurrent Neural Networks, Andrej Karpathy blog, May 21, 2015.

[2] Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama and T. Darrell, Caffe: Convolutional Architecture for Fast Feature Embedding, June 20, 2014.

[3] adepierre, adepierre/caffe-char-rnn Github, Github.com, January 25, 2017.

Product Compatible and additional computed target framework versions.
.NET Framework net40 is compatible.  net403 was computed.  net45 was computed.  net451 was computed.  net452 was computed.  net46 was computed.  net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
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Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

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MyCaffe/MyCaffe
A complete deep learning platform written almost entirely in C# for Windows developers! Now you can write your own layers in C#!
Version Downloads Last updated
1.12.2.41 675 9/18/2023
1.12.1.82 469 6/8/2023
1.12.0.60 687 2/21/2023
1.11.8.27 849 11/23/2022
1.11.7.7 1,182 8/8/2022
1.11.6.38 891 6/10/2022
0.11.6.86-beta1 405 2/11/2022
0.11.4.60-beta1 370 9/11/2021
0.11.3.25-beta1 494 5/19/2021
0.11.2.9-beta1 335 2/3/2021
0.11.1.132-beta1 371 11/21/2020
0.11.1.56-beta1 366 10/17/2020
0.11.0.188-beta1 409 9/24/2020
0.11.0.65-beta1 431 8/6/2020
0.10.2.309-beta1 555 5/31/2020
0.10.2.124-beta1 475 1/21/2020
0.10.2.38-beta1 464 11/29/2019
0.10.1.283-beta1 462 10/28/2019
0.10.1.221-beta1 470 9/17/2019
0.10.1.169-beta1 564 7/8/2019
0.10.1.145-beta1 557 5/31/2019
0.10.1.48-beta1 581 4/18/2019
0.10.1.21-beta1 561 3/5/2019
0.10.0.190-beta1 724 1/15/2019
0.10.0.140-beta1 677 11/29/2018
0.10.0.122-beta1 701 11/15/2018
0.10.0.75-beta1 716 10/7/2018

MyCaffe AI Platform