@@ -25,29 +25,28 @@ The `main.py` script accepts the following arguments:
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``` bash
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optional arguments:
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- -h, --help show this help message and exit
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- --data DATA location of the data corpus
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- --model MODEL type of recurrent net (RNN_TANH, RNN_RELU, LSTM, GRU)
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- --emsize EMSIZE size of word embeddings
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- --nhid NHID number of hidden units per layer
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- --nlayers NLAYERS number of layers
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- --lr LR initial learning rate
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- --clip CLIP gradient clipping
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- --epochs EPOCHS upper epoch limit
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- --batch_size N batch size
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- --bptt BPTT sequence length
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- --dropout DROPOUT dropout applied to layers (0 = no dropout)
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- --decay DECAY learning rate decay per epoch
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- --tied tie the word embedding and softmax weights
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- --seed SEED random seed
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- --cuda use CUDA
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- --log-interval N report interval
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- --save SAVE path to save the final model
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- --onnx-export path to export the final model in onnx format
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- --transformer_head N the number of heads in the encoder/decoder of the transformer model
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- --transformer_encoder_layers N the number of layers in the encoder of the transformer model
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- --transformer_decoder_layers N the number of layers in the decoder of the transformer model
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- --transformer_d_ff N the number of nodes on the hidden layer in feed forward nn
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+ -h, --help show this help message and exit
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+ --data DATA location of the data corpus
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+ --model MODEL type of recurrent net (RNN_TANH, RNN_RELU, LSTM, GRU,
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+ Transformer)
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+ --emsize EMSIZE size of word embeddings
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+ --nhid NHID number of hidden units per layer
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+ --nlayers NLAYERS number of layers
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+ --lr LR initial learning rate
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+ --clip CLIP gradient clipping
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+ --epochs EPOCHS upper epoch limit
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+ --batch_size N batch size
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+ --bptt BPTT sequence length
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+ --dropout DROPOUT dropout applied to layers (0 = no dropout)
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+ --tied tie the word embedding and softmax weights
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+ --seed SEED random seed
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+ --cuda use CUDA
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+ --log-interval N report interval
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+ --save SAVE path to save the final model
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+ --onnx-export ONNX_EXPORT
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+ path to export the final model in onnx format
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+ --nhead NHEAD the number of heads in the encoder/decoder of the
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+ transformer model
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```
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With these arguments, a variety of models can be tested.
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