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run_exp_baselines_probs_moving_mnist.sh
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run_exp_baselines_probs_moving_mnist.sh
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echo "Transformer"
kedro run --env=moving_mnist --pipeline=moving_mnist --params "{
'dataset_parameters': {'flatten': true},
'model_type': 'Transformer',
'generic_model_params': {
'd_model': 72,
'num_heads': 9,
'N': 6,
'use_cuda': true,
'embed_mode': 'Embedding',
'dropout': 0.2
},
'optim_params': {
'lr': 0.0001,
'betas': [0.9, 0.999],
'eps': 1e-9,
'quantiles': [0.1, 0.5, 0.9],
'warmup': false,
'T_max_epoch': 100,
'lr_min': 0.0001
}
}"
echo "VanillaLSTM"
kedro run --env=moving_mnist --pipeline=moving_mnist --params "{
'dataset_parameters': {'flatten': true},
'model_type': 'VanillaLSTM',
'generic_model_params': {
'linear_output_size': 72,
'lstm_hidden_size': 72,
'lstm_num_layers': 6,
'hidden_seq_len': 10,
'one_step_ahead': true,
'use_cuda': true,
'dropout': 0.2
},
'optim_params': {
'lr': 0.0001,
'betas': [0.9, 0.999],
'eps': 1e-9,
'quantiles': [0.1, 0.5, 0.9],
'warmup': false,
'T_max_epoch': 100,
'lr_min': 0.0001
}
}"
echo "VanillaLSTMSeq2Seq"
kedro run --env=moving_mnist --pipeline=moving_mnist --params "{
'dataset_parameters': {'flatten': true},
'model_type': 'VanillaLSTMSeq2Seq',
'generic_model_params': {
'linear_output_size': 72,
'lstm_hidden_size': 72,
'lstm_num_layers': 6,
'one_step_ahead': true,
'use_cuda': true,
'dropout': 0.2,
'sigmoid_output': false
},
'optim_params': {
'lr': 0.0001,
'betas': [0.9, 0.999],
'eps': 1e-9,
'quantiles': [0.1, 0.5, 0.9],
'warmup': false,
'T_max_epoch': 100,
'lr_min': 0.0001
}
}"
echo "VanillaLSTMSeq2SeqAttn"
kedro run --env=moving_mnist --pipeline=moving_mnist --params "{
'dataset_parameters': {'flatten': true},
'model_type': 'VanillaLSTMSeq2SeqAttn',
'generic_model_params': {
'linear_output_size': 72,
'lstm_hidden_size': 72,
'lstm_num_layers': 6,
'one_step_ahead': true,
'use_cuda': true,
'dropout': 0.2,
'sigmoid_output': false
},
'optim_params': {
'lr': 0.0001,
'betas': [0.9, 0.999],
'eps': 1e-9,
'quantiles': [0.1, 0.5, 0.9],
'warmup': false,
'T_max_epoch': 100,
'lr_min': 0.0001
}
}"
echo "ConvLSTM"
kedro run --env=moving_mnist --pipeline=moving_mnist --params "{
'dataset_parameters': {'flatten': false},
'model_type': 'ConvLSTM',
'generic_model_params': {
'input_channels': 1,
'hidden_channels': [8, 8, 8, 8, 8, 8],
'kernel_size': 3,
'pred_input_dim': 10,
'one_step_ahead': true,
'use_cuda': true,
'dropout': 0.2,
'sigmoid_output': false
},
'optim_params': {
'lr': 0.0001,
'betas': [0.9, 0.999],
'eps': 1e-9,
'quantiles': [0.1, 0.5, 0.9],
'warmup': false,
'T_max_epoch': 100,
'lr_min': 0.0001
}
}"