Generic model API, Model Zoo in Tensorflow, Keras, Pytorch, Hyperparamter search
Project description
ml_models --do
"testall" : test all modules inside model_tf
"test" : test a certain module inside model_tf
"model_list" : #list all models in the repo
"fit" : wrap fit generic m ethod
"predict" : predict using a pre-trained model and some data
"generate_config" : generate config file from code source
ml_optim --do
"test" : Test the hyperparameter optimization for a specific model
"test_all" : TODO, Test all
"search" : search for the best hyperparameters of a specific model
Include models :
encoder_vanilla
bidirectional_vanilla
vanilla_2path
lstm_seq2seq
lstm_attention
lstm_seq2seq_attention
lstm_seq2seq_bidirectional
lstm_seq2seq_bidirectional_attention
lstm_attention_scaleddot
lstm_dilated
lstm.py models
only_attention
multihead_attention
lstm_bahdanau
lstm_luong
lstm_luong_bahdanau
dnc
lstm_residual
byte_net
attention_is_all_you_need
fairseq
encoder_lstm
bidirectional_lstm
lstm_2path
lstm attention
gru
encoder_gru
bidirectional_gru
gru_2path
vanilla
autoencoder
nbeats time series
deepar time series
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