├── .gitignore ├── IndRNN_onlyrecurrent.py ├── Indrnn_densenet.py ├── Indrnn_plainnet.py ├── Indrnn_residualnet_preact.py ├── PTB ├── Indrnn_densenet_returnstates.py ├── Indrnn_plainnet_returnstates.py ├── Indrnn_residualnet_preact_returnstates.py ├── README.md ├── cuda_IndRNN_onlyrecurrent.py ├── data.py ├── data │ └── .gitignore ├── dynamiceval.py ├── getdata.sh ├── language_utils.py ├── opts.py ├── results │ ├── 5097_logdynamic_len20_lambda_save.log │ ├── 5637_logwordptb_wtying_864_grow256_drop514_65652_save.log │ └── 5802_res_logwordptb_wtying_lr2e4_5blocks_2000_drop45_last5_65652_RecHuniform_pThre200_NOsmallnormini_bnbefore.log ├── run_dense_cptb.sh ├── run_dense_wptb.sh ├── run_res.sh ├── train_language.py └── utils.py ├── README.md ├── action_recognition ├── IndRNN_onlyrecurrent.py ├── Indrnn_action_train.py ├── Indrnn_densenet.py ├── Indrnn_densenet_FA.py ├── Indrnn_plainnet.py ├── Indrnn_residualnet_preact.py ├── README.md ├── cuda_IndRNN_onlyrecurrent.py ├── data_reader.py ├── opts.py ├── results │ ├── 8315_plain_logindrnn_6layers_512_drop4_bs128_consU_pThre100_inilasth_save.log │ ├── 8418_res_logindrnn_5blocks_512_drop5_bs128_consU_pThre150_save.log │ ├── 8488_dense_logindrnn_864_first6_grow48_drop53531_bs128_consU_inilast_pThre100_save.log │ ├── 8510_dense_logindrnn_864_first6_grow48_drop54541_bs128_consU_inilast_pThre100_save.log │ ├── 8655_dense_logindrnn_864_first6_grow48_drop53531_bs128_consU_inilast_pThre150_geoaug_timediff_datarandtime_testno40_save.log │ ├── 8812_plain_CVlogindrnn_6layers_512_drop4_bs128_consU_pThre100_inilasth_save.log │ ├── 9016_dense_CVlogindrnn_864_first6_grow48_drop53531_bs128_consU_inilast_pThre100_save.log │ ├── 9023_res_CVlogindrnn_5blocks_512_drop5_bs128_consU_pThre150_save.log │ └── 9405_dense_CVlogindrnn_864_first6_grow48_drop53531_bs128_consU_inilast_pThre150_geoaug_timediff_datarandtime_testno40_save.log ├── run.sh ├── run_JLD.sh ├── run_dense.sh ├── run_res.sh └── utils.py ├── cuda_IndRNN_onlyrecurrent.py ├── paper ├── Deep Independently Recurrent Neural Network (IndRNN)-arxiv.pdf └── Independently Recurrent Neural Network (IndRNN) Building A Longer and Deeper RNN.pdf ├── pixelMNIST ├── Data_gen.py ├── IndRNN_onlyrecurrent.py ├── Indrnn_densenet.py ├── Indrnn_mnist_train.py ├── Indrnn_plainnet.py ├── Indrnn_residualnet_preact.py ├── README.md ├── cuda_IndRNN_onlyrecurrent.py ├── opts.py ├── result │ ├── 9563_plain_permutelogindrnn_6layers_128_drop1_bs32_consU_pThre100_inilasth_save.log │ ├── 9652_plain_permutelogindrnn_12layers_128_drop1_bs32_consU_pThre100_inilasth_save.log │ ├── 9685_res_permute_logindrnn_5blocks_128_drop1_bs32_consU_pThre100_preact_inilasth_save.log │ ├── 9704_plain_permutelogindrnn_12layers_128_drop1_bs32_consU_pThre100_save.log │ ├── 9716_dense_permute_logindrnn_864_first6_grow16_drop21121_bs32_consU_inilast_pThre200_save.log │ ├── 9904_plain_logindrnn_6layers_128_drop1_bs32_consU_pThre100_inilasth_save.log │ ├── 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