main(encodings_source:"Path to the tokens encoded as an ID. (eltype should be np.int32)", offsets_source:"Path to the offsets array indicating where each value of the array indicates where a chunk of text should start. (eltype should be np.uint64, first value should be 0)", output_dir:"Directory in which to save the checkpoints. Created if it does not exist"='.', save_every:"How many epochs to run before saving a checkpoint"=1, ckpt_prefix:"Prefix to name each checkpoint. Additional parameter choices are inserted into the checkpoint name."='flyvec_model', starting_checkpoint:"Path to .npy file of saved checkpoint"=None, W:"Size of the W-gram sliding window used to train the word vectors"=11, hid:"Number of hidden units (neurons). Do not change"=400, initial_learning_rate:"Initial learning rate"=0.002, delta:"From equation"=0.0, mu:"If no checkpoint provided, use this as mean for random normal initialization of synapses"=0.0, sigma:"If no checkpoint provided, use this as stdev for random normal initialization of synapses"=0.02, Nep:"Maximum number of epochs, fewer if starting from a checkpoint"=15, batch_size:"Minibatch size"=10000, prec:"Precision, avoid dividing by 0"=1e-30)