Getting started
################

.. include:: quickstart.rst

Quick run on other datasets
~~~~~~~~~~~~~~~~~~~~~~~~~~~~


Run experiments on Office31
---------------------------

The default configuration file `office31.json` is configured for domain adaptation from Amazon to Webcam.

::

    python run_full_options.py -d ../configs/datasets/office31.json -g 0

`-g 0` tell PyTorch to use the GPU with id 0, remove this parameter altogether to train on CPU.
You can list several GPU ids with `-g 0 1 ...` (note this can cause errors with some pytorch-lightning versions).
The above command will train networks with the default configuration in `../configs/office31_network.json`, which defines the architecture (eg ResNet50 for the feature extractor)
and the learning hyperparameters (epochs, learning rate, ...).

You can edit the content of the `../configs/datasets/office31.json` config file to use
other domain configurations (eg Webcam to DSLR). Please note it is
important to change the "dataset_name" field to organize the output directory structure.

::

    {
    "dataset_group": "office31",
    "dataset_name": "Amazon to Webcam",
    "source": "amazon",
    "target": "webcam",
    "size_type": "source",
    "weight_type": "natural"
    }

You can edit `../configs/office31_network.json` to change any network parameter. The configuration contains two subsets of parameters: 

 - `train_params` define the hyperparameters to be used for training: learning rate, optimizer, number of epochs.
 - `archi_params` define the "static" architecture of the network, with three blocks for `feature` extrator, `task` classifier and `critic` network. 
    The critic network parameters may be ignored by some methods.


 Example::

    {
        "train_params": {
            "adapt_lambda": true,
            "adapt_lr": true,
            "lambda_init": 1,
            "nb_adapt_epochs": 150,
            "nb_init_epochs": 50,
            "init_lr": 1e-3,
            "batch_size": 32,
            "optimizer": {
            "type": "SGD",
            "optim_params": {
                "momentum": 0.9,
                "weight_decay": 0.0005,
                "nesterov": true
            }
            }
        },
        "archi_params": {
            "feature": {
                "name": "ResNet50",
                "feature_dim": 128
            },
            "task": {
                "name": "feedforward",
                "n_classes": 31
            },
            "critic": {
                "name": "feedforward",
                "hidden_size": [
                    256
                ]
            }
        }
    }

    

Run experiments on Digits
--------------------------


This is very similar to Office31. The default configuration file `digits.json` is configured for domain adaptation from MNIST to USPS. You can easily
change the domains by editing this configuration file.

::

    python run_full_options.py -d ../configs/datasets/digits.json -g 0


This will use by default the network configuration in `../configs/digits_network.json`.