update doc

docs/conf.py

@@ -178,7 +178,7 @@
         {
             "href": "doc_extend_contribute",
             "internal": True,
-            "title": "Specify custom model in commandline",
+            "title": "Developers note",
         },
         # {
         #     "href": "https://squidfunk.github.io/mkdocs-material/",

docs/doc_extend_contribute.md

@@ -1,18 +1,114 @@
-# Extend or contribute with a custom domain generalization model
-
-## External extension by implementing your custom models
-
-Look at this example
-
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --apath=examples/models/demo_custom_model.py --model=custom --nname_argna2val my_custom_arg_name --nname_argna2val alexnet
-
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --apath=examples/models/demo_custom_model.py --model=custom --npath_argna2val my_custom_arg_name --npath_argna2val examples/nets/resnet.py
-```
+## Software Architecture and Design
+![Design Diagram](libDG.svg)
 
-where the example python file corresponding to `--apath` defines a model which contains several modules that can be customized to different neural networks via `--npath_argna2val` if the neural network is specified in a python file
-or `nname_argna2val` if the neural network is already implemented.
 
+## Code structure
 
-# Software Architecture and Design
-![Design Diagram](libDG.svg)
+domainlab/
+├── algos
+│   ├── a_algo_builder.py
+│   ├── builder_api_model.py
+│   ├── builder_custom.py
+│   ├── builder_dann.py
+│   ├── builder_diva.py
+│   ├── builder_erm.py
+│   ├── builder_hduva.py
+│   ├── builder_jigen1.py
+│   ├── __init__.py
+│   ├── msels
+│   ├── observers
+│   ├── trainers
+│   ├── utils.py
+│   └── zoo_algos.py
+├── arg_parser.py
+├── cli.py
+├── compos
+│   ├── a_nn_builder.py
+│   ├── builder_nn_alex.py
+│   ├── builder_nn_conv_bn_relu_2.py
+│   ├── builder_nn_external_from_file.py
+│   ├── __init__.py
+│   ├── nn_zoo
+│   ├── pcr
+│   ├── utils_conv_get_flat_dim.py
+│   ├── vae
+│   └── zoo_nn.py
+├── dsets
+│   ├── a_dset_mnist_color_rgb_solo.py
+│   ├── dset_img_path_list.py
+│   ├── dset_mnist_color_solo_default.py
+│   ├── dset_poly_domains_mnist_color_default.py
+│   ├── dset_subfolder.py
+│   ├── __init__.py
+│   ├── utils_color_palette.py
+│   ├── utils_data.py
+│   └── utils_wrapdset_patches.py
+├── exp
+│   ├── exp_cuda_seed.py
+│   ├── exp_main.py
+│   ├── exp_utils.py
+│   └── __init__.py
+├── exp_protocol
+│   ├── aggregate_results.py
+│   ├── benchmark.smk
+│   ├── __init__.py
+│   └── run_experiment.py
+├── __init__.py
+├── mk_exp.py
+├── models
+│   ├── a_model_classif.py
+│   ├── a_model.py
+│   ├── args_jigen.py
+│   ├── args_vae.py
+│   ├── __init__.py
+│   ├── interface_vae_xyd.py
+│   ├── model_custom.py
+│   ├── model_dann.py
+│   ├── model_diva.py
+│   ├── model_erm.py
+│   ├── model_hduva.py
+│   ├── model_jigen.py
+│   └── model_vae_xyd_classif.py
+├── tasks
+│   ├── a_task_classif.py
+│   ├── a_task.py
+│   ├── b_task_classif.py
+│   ├── b_task.py
+│   ├── __init__.py
+│   ├── task_dset.py
+│   ├── task_folder_mk.py
+│   ├── task_folder.py
+│   ├── task_mini_vlcs.py
+│   ├── task_mnist_color.py
+│   ├── task_pathlist.py
+│   ├── task_utils.py
+│   ├── utils_task_dset.py
+│   ├── utils_task.py
+│   └── zoo_tasks.py
+├── utils
+│   ├── flows_gen_img_model.py
+│   ├── generate_benchmark_plots.py
+│   ├── get_git_tag.py
+│   ├── hyperparameter_gridsearch.py
+│   ├── hyperparameter_sampling.py
+│   ├── __init__.py
+│   ├── logger.py
+│   ├── override_interface.py
+│   ├── perf_metrics.py
+│   ├── perf.py
+│   ├── sanity_check.py
+│   ├── test_img.py
+│   ├── u_import_net_module.py
+│   ├── u_import.py
+│   ├── utils_classif.py
+│   ├── utils_class.py
+│   ├── utils_cuda.py
+│   └── utils_img_sav.py
+└── zdata
+    ├── mixed_codec
+    ├── pacs_mini_10
+    ├── pacs_split
+    ├── patches_permutation4jigsaw
+    ├── script
+    ├── vlcs_mini
+    └── ztest_files