SumGAN upgrade

[sylvainma]

• [x] Flag for pretraining the lstm VAE as recommended in paper
• [x] Refactoring and bugfixes
• [x] Introduction of SumGAN_{att}

Command with "tractable" dimensions:

python main.py --model sumgan --epochs 100 --splits-file splits/tvsum_splits.json \
  --sigma 0.3 \
  --sLSTM_hidden_size 128 --sLSTM_num_layers 1 --edLSTM_hidden_size 128 --edLSTM_num_layers 1 --cLSTM_hidden_size 128 --cLSTM_num_layers 1

I used this split file for debugging/overfitting:

[
    {
        "train_keys": [
            "video_1"
        ],
        "test_keys": [
            "video_1"
        ]
    }
]

[sylvainma]

SunGAN Attention introduced:

• Transformer instead of sLSTM
• Transformer-based autoencoder instead of lstm VAE

Expectations:

• Transformer-based autoencoder easier to train than lstm VAE
• Faster computations (transformers benefit from GPU compared to lstms)

Test command:

python main.py --model sumgan_att --epochs 1 --sigma 0.3 --pretrain_ae 1 \
  --cLSTM_hidden_size 512 --cLSTM_num_layers 2