Metadata-Version: 1.2
Name: DLStudio
Version: 2.0.4
Summary: An educational module to make it easier to design experimental deep-learning networks in PyTorch
Home-page: https://engineering.purdue.edu/kak/distDLS/DLStudio-2.0.4.html
Author: Avinash Kak
Author-email: kak@purdue.edu
Maintainer: Avinash Kak
Maintainer-email: kak@purdue.edu
License: Python Software Foundation License
Download-URL: https://engineering.purdue.edu/kak/distDLS/DLStudio-2.0.4.tar.gz
Description: 
        
        Consult the module API page at
        
              https://engineering.purdue.edu/kak/distDLS/DLStudio-2.0.4.html
        
        for all information related to this module, including information related
        to the latest changes to the code.  
        
        ::
        
              convo_layers_config = "1x[128,3,3,1]-MaxPool(2) 1x[16,5,5,1]-MaxPool(2)"
              fc_layers_config = [-1,1024,10]
              
              dls = DLStudio(
                                dataroot = "/home/kak/ImageDatasets/CIFAR-10/",
                                image_size = [32,32],
                                convo_layers_config = convo_layers_config,
                                fc_layers_config = fc_layers_config,
                                path_saved_model = "./saved_model",
                                momentum = 0.9,
                                learning_rate = 1e-3,
                                epochs = 2,
                                batch_size = 4,
                                classes = ('plane','car','bird','cat','deer','dog','frog','horse','ship','truck'),
                                use_gpu = True,
                                debug_train = 0,
                                debug_test = 1
                            )
              
              configs_for_all_convo_layers = dls.parse_config_string_for_convo_layers()
              convo_layers = dls.build_convo_layers2( configs_for_all_convo_layers )
              fc_layers = dls.build_fc_layers()
              model = dls.Net(convo_layers, fc_layers)
              dls.show_network_summary(model)
              dls.load_cifar_10_dataset()
              dls.run_code_for_training(model)
              dls.run_code_for_testing(model)
        
              
                  
Keywords: P,y,T,o,r,c,h, ,p,r,o,g,r,a,m,m,i,n,g
Platform: A
Platform: l
Platform: l
Platform:  
Platform: p
Platform: l
Platform: a
Platform: t
Platform: f
Platform: o
Platform: r
Platform: m
Platform: s
Classifier: Topic :: Scientific/Engineering
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.8
