labml_nn/__init__.py,sha256=oi3XqSrA0mfp6U-me-rzXWwdR65LCIfeuDvRsynXz84,8869
labml_nn/activations/__init__.py,sha256=Y3l9M3Er274x0smB3TjVSBk_0p4ZVn6bRlqzgA8yMMU,288
labml_nn/activations/swish.py,sha256=yV5i0TF6uQv27mycEUUWSvv_fokoRhx93WsQxZz98aA,277
labml_nn/activations/fta/__init__.py,sha256=WsFKPAre3DA7GGP24p5Nf_c9D7qoq5BR_Ao4nNo0-Ls,4866
labml_nn/activations/fta/experiment.py,sha256=kNEqbTbxCBHk9LaexbJ0Viu3C7V1C9kH3oDDYe4dCww,7429
labml_nn/adaptive_computation/__init__.py,sha256=ayKOWve81ZE1r87RRv9wpE_q4CDZr1-pvaLN4kByuH0,448
labml_nn/adaptive_computation/parity.py,sha256=qjalXMCD1wpFk_Bn3QgfF0cKi09GcWZGKHk6s8Yltck,1751
labml_nn/adaptive_computation/ponder_net/__init__.py,sha256=c8WYVN1uvZkw5O0YcafE9fTj62DvYiSnL_0p4IRXEjk,10346
labml_nn/adaptive_computation/ponder_net/experiment.py,sha256=S0Y80ahtZ7szOPiKVcpEMSTJFXfAJFnVoQjpCsvKURc,5038
labml_nn/capsule_networks/__init__.py,sha256=Hd3TglVlDs9ndz85ceu2_S5Y9qARn6FmJwFmrq7nJM0,7821
labml_nn/capsule_networks/mnist.py,sha256=yYSJUvshXEmdpCLG8BjwPKSRnqQBUlJGNeLF0PfRKY4,6679
labml_nn/cfr/__init__.py,sha256=NinOEIZ491h3knxYyyZZSyaws_e7YfECyMrkLKJ6HYs,27072
labml_nn/cfr/analytics.py,sha256=YUEC9fQZi_4Ae6fV1oddTcsfGz__W2UqzF8s9QfaLNQ,1894
labml_nn/cfr/infoset_saver.py,sha256=qiOv3ItEGlovd-H35WTFfg0snwDHCpprpniPJWL4KVo,814
labml_nn/cfr/kuhn/__init__.py,sha256=MNRqO3sNsGF-Bgfru4Vsta5bLZgzFiZB1JeJXfNfJCc,8183
labml_nn/conv_mixer/__init__.py,sha256=7G709XHOMth1GXPDVAx2n7UjJV473_RaaXdTQAJ05Gk,7640
labml_nn/conv_mixer/experiment.py,sha256=o40mXPojJL0PoVql9EujQYce5UmmszvGNFJVzHYlnZI,2573
labml_nn/diffusion/__init__.py,sha256=ALEgk3_wMtprJv9KXBUkSA5HZ5JfGYIOZ-6KLx86ubQ,206
labml_nn/diffusion/ddpm/__init__.py,sha256=OQx2y8L8HbISEZIcPEo-pB5PurWTP4np3xA9JnGWNT0,10847
labml_nn/diffusion/ddpm/evaluate.py,sha256=gueKA3GCGHnuKQcWtdvQLNLTirEziqnpPCwzWhUuz3Q,11678
labml_nn/diffusion/ddpm/experiment.py,sha256=T4KWEdbNtiYhFUNtf-vE2d-iRXgbykDmOAx1FPiH8QE,7126
labml_nn/diffusion/ddpm/unet.py,sha256=jkXOz6R5EYf0MLNNwozqUf1AA1FbGy7SmqDOKbjGjD4,14688
labml_nn/diffusion/ddpm/utils.py,sha256=NOeshTUAvDGQKLldV9bmJza8qxSnW1xKuAJLMCwFWnY,372
labml_nn/distillation/__init__.py,sha256=MouwDZp4DBJ7Peh3Gby2t7l5XQzFJrdxsFE0lFHjVjg,8572
labml_nn/distillation/large.py,sha256=ZZTGKmL-V0qMVupgqmSInc-fKiHcCrnXIlytJCe_sB8,2558
labml_nn/distillation/small.py,sha256=MptZxfeM9ue3MyZ_WqfyPARln05SPFe6MY1lZDHL-e0,2465
labml_nn/experiments/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
labml_nn/experiments/arithmetic_dataset.py,sha256=2jJ31WWEXRn7qvYZ2N8D5y79AvyhfQJbspl9hg6Gy58,8002
labml_nn/experiments/cifar10.py,sha256=_3wPspRZq0Coxa46WUejbxt0O10ko3juMtWQpFAt0RE,3521
labml_nn/experiments/mnist.py,sha256=RtczAsq_Gf3SawfhXiQHh4A9-kYPXAwgKumMDtPhNJM,3379
labml_nn/experiments/nlp_autoregression.py,sha256=WUby7dhSzhsxGCDvzLQQt9m-ROy_3sr81mm9EIFtHqI,10279
labml_nn/experiments/nlp_classification.py,sha256=kO3jTZXEOSBxl_gO5nKKbcg4l7DVGX3FSVp93AC9-ag,9168
labml_nn/gan/__init__.py,sha256=_zHCoJ6xLmwCf1s3EwS1DsP7_fGhorW87UGYN2sQ-wQ,449
labml_nn/gan/cycle_gan/__init__.py,sha256=1d5cxEADUwCYcsN5cyLelzg5Tl9_iTHODAsLGufcyls,29029
labml_nn/gan/dcgan/__init__.py,sha256=f5iZszjBGRyMJ4YhhXXPVX82tYvNiezMK_3ea8ZDQIc,3886
labml_nn/gan/original/__init__.py,sha256=5beomOaPyKV4IdykQxxPWNiXOO0GCKafs9t0XDrcimk,4917
labml_nn/gan/original/experiment.py,sha256=mPqZqA0YKfCq0aBCftQw6cpySqtDTGHnaHOfykxvMQs,7964
labml_nn/gan/stylegan/__init__.py,sha256=SZvmhB8TmbQa0KKbY2PO56fdDUE1GoD5sRECIY1C3uw,36635
labml_nn/gan/stylegan/experiment.py,sha256=2jLIzbWOeVEGTigGfQtuPbXcGlHCw5kW_T89-G_fWLs,17569
labml_nn/gan/wasserstein/__init__.py,sha256=07nG4kgZEOtu_PohO4EVz9vPewfRYsOYiFAPSJ1X9lo,4710
labml_nn/gan/wasserstein/experiment.py,sha256=qyGk4h9PO6jxgCwDLbrq4Vdf7t6Kt45KjY6etS9S5h0,1352
labml_nn/gan/wasserstein/gradient_penalty/__init__.py,sha256=1FHjsgnN1ui05RalZnmboFjr_LapJn-WIlDSip_yCT8,2837
labml_nn/gan/wasserstein/gradient_penalty/experiment.py,sha256=zisuNEam5JHYRdB3iPS0-b7jjP27Yy83G4XtLzFXxPc,2780
labml_nn/graphs/__init__.py,sha256=p1zvkSYeNPGMb5T-eJbawzk6r_eqci3ase-GtrFmxzg,268
labml_nn/graphs/gat/__init__.py,sha256=iStaWdwiGTtyNX6SQ6ulot_75LMyLKh-TWPGabOJ2Xs,9052
labml_nn/graphs/gat/experiment.py,sha256=rFjFzmTygXX5vw9LVKKESpeU16agawZijHTrEZCaChQ,10541
labml_nn/graphs/gatv2/__init__.py,sha256=AO3Ut4kioRF3YRwr1TWMRYst_31Bq4Xf9CFxJqniWLo,11031
labml_nn/graphs/gatv2/experiment.py,sha256=56f-c4eZ4xFeY5ctUSoMY1ah5Oyk1MBrLIIuVuZgvAc,3795
labml_nn/hypernetworks/__init__.py,sha256=XplC7lJIixwssdkgp6Ij4Z3ciTsjfSj0HLuucri7Ve8,160
labml_nn/hypernetworks/experiment.py,sha256=wpVJhsaXE-71Z5iQSl2AoRXRivh8LY-v6dwWwL92jws,2824
labml_nn/hypernetworks/hyper_lstm.py,sha256=ZaKkZXBxqLCBJj6OjAjARnB7qsNGekhM-dmBKPeQMOo,11725
labml_nn/lstm/__init__.py,sha256=Csn8KTV8n1lcD1Q2OA82Y69FPVq0ei73S0ieJxRJ-JY,5997
labml_nn/normalization/__init__.py,sha256=E-gihFTfL0BjNJUrhYyJXg4j4goN9WlzalPKQjN40uI,503
labml_nn/normalization/batch_channel_norm/__init__.py,sha256=u5W1YSHAoThfvz3h1PZ76Eo6_Z1fGd5PfP4dvDePZZ4,10012
labml_nn/normalization/batch_norm/__init__.py,sha256=sBA63yfEuwytUNcuk82He7t_pCds5uLcCqiID-QQ_lU,9723
labml_nn/normalization/batch_norm/cifar10.py,sha256=8CschuXNIm9z81RRxk0Sfi9n1FbUi66DSnPcz8PG67c,1629
labml_nn/normalization/batch_norm/mnist.py,sha256=w73OT9u9rUkOzSPAyATvqtTK3pxJnLUbG1ByrvOV9pU,2481
labml_nn/normalization/deep_norm/__init__.py,sha256=XJog7WLTmQONEBDARaBY0_Mbc1QZ0jE0WoCsu2OSwvo,7236
labml_nn/normalization/deep_norm/experiment.py,sha256=-R_IalhiWlP5p0qSry8KX_nFTmVvp8lHlOCvpG4TYNI,5414
labml_nn/normalization/group_norm/__init__.py,sha256=avzXJ1lgsn9_Ead2XLoR00HhSQ86K-5dUHERZu_doNM,6401
labml_nn/normalization/group_norm/experiment.py,sha256=6Zx9kxGhWBISfZ7M9GmG4DPbOnRJodZVgnXzX8f5908,2307
labml_nn/normalization/instance_norm/__init__.py,sha256=tvm_BzXkhamMy2B8ntV0leCpzUF-Hyy8XMkpbYgP6uY,4240
labml_nn/normalization/instance_norm/experiment.py,sha256=pwRADtpGPMFKFreaMFe-2xZkWL1f3K305ilhEfVIXQ4,1824
labml_nn/normalization/layer_norm/__init__.py,sha256=NwAuhjDsTfXi6kkJbgIxRsdt8TDHeMl14hpCfpjAnCo,5232
labml_nn/normalization/weight_standardization/__init__.py,sha256=BpKOUEbuh8epoGMc1jeUoyrzZgUL2pYWjXq-UZVUsIc,3738
labml_nn/normalization/weight_standardization/conv2d.py,sha256=VfdRW3yfr0gWwnCsVGzpmL8A8k-2pnTO93BFKXXgwdE,1879
labml_nn/normalization/weight_standardization/experiment.py,sha256=LZlql_rOsKCzsVbZUFcTX48s8G8MkgU4y_r2ryNnnrc,1818
labml_nn/optimizers/__init__.py,sha256=r8Rh332xLYQch3Xns11mCfaLOfQv-2BCiqupAB1-LJs,8131
labml_nn/optimizers/ada_belief.py,sha256=3b9snYjSK_9GGm-r6TwLI4S5j4MgRpO1-Y_e-tmVl6s,6842
labml_nn/optimizers/adam.py,sha256=uUa1BuYCiSm6XgXNicllg-K2djfmTy24L5ybsBwXeRw,8615
labml_nn/optimizers/adam_warmup.py,sha256=AZ_8ke8iwrly1f_1QnF-KRP3azyxA-IeFN3qlRSkt80,2301
labml_nn/optimizers/adam_warmup_cosine_decay.py,sha256=nxNIFX-Iaq0LqklUu1u1NIrLQR6OkVO4V9PcX6dbhlI,3675
labml_nn/optimizers/amsgrad.py,sha256=rh1Gw-nlpyAW5g1fXDlOdNfNm8PZY-eqXA4PVXLYcRI,8038
labml_nn/optimizers/configs.py,sha256=hRHvV18KVjyKnLHLReNnPMqIiLYkyqZIc3L_H3s_pcE,4801
labml_nn/optimizers/mnist_experiment.py,sha256=vd1OhjP75OVOtip9HBdBk-SBb3ZwWf4mfEbxaeKickI,4063
labml_nn/optimizers/noam.py,sha256=QnVI1vvANdF2E51ycZp_610EPdCuPMmmsTx1WE_EpG0,3388
labml_nn/optimizers/performance_test.py,sha256=-B58KliDW93WYzwXpmK12E9tW77Zu_AdszQNjrhurDQ,1612
labml_nn/optimizers/radam.py,sha256=RKHMaXXN1AMIlsRPU0JtWEXWw5cRMRZPo4kMQD8_cfM,11265
labml_nn/recurrent_highway_networks/__init__.py,sha256=NHdiqk1XUkUiBcgBjT3u8gt8aYs6l6DrEnDvDM_xkVc,5729
labml_nn/resnet/__init__.py,sha256=aKuAXXxsXsaxnw8gLzNzRGXx7Cre-lDmH9uGxK4vfG4,13532
labml_nn/resnet/experiment.py,sha256=3FCFwcIRQnN24xJCiHmRXFFOEFEf5mHHVVv1DBBSF9I,2238
labml_nn/rl/__init__.py,sha256=Pr6BPgyAqF8gevMmdQVqLSaxGc3FHWPQVMgwtE5GKJk,826
labml_nn/rl/game.py,sha256=PIicY-Y8eOC-Lfnzad-lAwMOUQtQygTE_Kblowa-3OY,4661
labml_nn/rl/dqn/__init__.py,sha256=OIzY8qVrZm5NnOSCOvHcWeLypw7vWmC-E-KpwpN7TzI,6730
labml_nn/rl/dqn/experiment.py,sha256=RUPK1kStw0ysR1B130CEIjg9GC_bXQA3YuMksrDIO9Y,10965
labml_nn/rl/dqn/model.py,sha256=-GneUzhoPJB3q5kQ1pbrUeiU1wdUQqXmub3wKXg45I0,3639
labml_nn/rl/dqn/replay_buffer.py,sha256=7Qf55_SeBW3-Qf--wB-Wr0pX9XtXvYlEStsB1ix-8rI,10154
labml_nn/rl/ppo/__init__.py,sha256=qgS_FODw311rMJtYprBPp5q92YzhU98JoeihnzdI9NI,7599
labml_nn/rl/ppo/experiment.py,sha256=fYBCc7bBubEQdWUhUbsuiXwNuoVqK102D6TvB-uFZq0,14940
labml_nn/rl/ppo/gae.py,sha256=enJITaut5ybedYq23vHcApClYrNiYvDalZlMlmJH6Ks,3039
labml_nn/sketch_rnn/__init__.py,sha256=vOaE7Ftz2srs-cWmvKxwGseX3RSTLpaYJ80iIl64hsE,25117
labml_nn/transformers/__init__.py,sha256=RHcEK27bc7B7ICYA0uuxq50zrFeoFJLeYRVY-DM-WAo,4254
labml_nn/transformers/configs.py,sha256=5sLTkwGFCS185-SvDWimV3Ho42gcvz3Y7lcD6TvD9jk,10352
labml_nn/transformers/feed_forward.py,sha256=gflYSqrA8lQLvg6jsHgwUXGHPM6V-k_ZXjqaW2xivcg,3590
labml_nn/transformers/label_smoothing_loss.py,sha256=QP9LzSw0u8vTpuzEq7sXxxE3o_amFTR64zC-XMWWNzE,2210
labml_nn/transformers/mha.py,sha256=Ree1vxZw5PiRJzWT2XiT95HeLDeyq4v1hRZfnfL8cY0,7486
labml_nn/transformers/models.py,sha256=gjMNex7zjNqQqROA3F8M_QrGLFG5V04jqfZGBA8U3_I,7982
labml_nn/transformers/positional_encoding.py,sha256=SJrAnjpH2StktzCyU4GakJzbIMKKjDO-HzLwySkQJNw,2328
labml_nn/transformers/relative_mha.py,sha256=16WrdIGm5vuac79saVwwHyh99bZeA7u1CQ3OQpFhCNA,187
labml_nn/transformers/utils.py,sha256=jTBgaH7Y2vYg1bZpJX68yXXYiDLg3rAFZedZl47eFqI,538
labml_nn/transformers/aft/__init__.py,sha256=3JWVW1KFc2BQjAOAZvq5g5TP6cPbrurwuEe0Ae3A3Cs,8624
labml_nn/transformers/aft/experiment.py,sha256=AbnZlBR-wDxfrmL2EcTWP8U3OV6ZWKEzGDtAVndg5EU,4988
labml_nn/transformers/alibi/__init__.py,sha256=BTyKUWOYrxX2-Hgfc9XwNt0PzOYqttlLWfG3nh2J5xY,4383
labml_nn/transformers/alibi/experiment.py,sha256=mWvnuLncxJLVtZxs4KAgm7MNqYN_v4lRCM69dVsfRn8,5100
labml_nn/transformers/basic/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
labml_nn/transformers/basic/autoregressive_experiment.py,sha256=0ymjptzhHGSSzR9S23V_Nzelsl8Hktvo6ZJUS9e0ekg,4682
labml_nn/transformers/compressive/__init__.py,sha256=5yR5I_NXVYp5DTsEvV_cI8uOFk-7TSOAJOxqfnsbJS0,13794
labml_nn/transformers/compressive/experiment.py,sha256=u4j4LfpWFtZocaQXpZenFwI8RtA6_IoYA5b3MxhlgNc,13020
labml_nn/transformers/fast_weights/__init__.py,sha256=hWLf9PeYZT7RXsm5QyEde_KCDD6mVAwchjin4DLWcrA,13297
labml_nn/transformers/fast_weights/experiment.py,sha256=T-2YygqtsI9vY2gGjGh-Uc-mSs6yw4twz0KnR_R3-Lc,3876
labml_nn/transformers/fast_weights/token_wise.py,sha256=vFFU1OmVhs6ezW0ZbmBHD9T-0_WMzCmsIcyhqE3mf7k,4213
labml_nn/transformers/feedback/__init__.py,sha256=2cdBzBVio3AoKhWbbjPmwLYl-5OmZ50IKFWQzoYgQcc,19933
labml_nn/transformers/feedback/experiment.py,sha256=H1R-y96NAkn0FwK3nhWiJNCL2CY3ex-q6BhDrAgVOt8,4929
labml_nn/transformers/fnet/__init__.py,sha256=B718tlPzKNMSBm-mTc7aAAqFoiVnj56LQ8BVpxD6gOU,3500
labml_nn/transformers/fnet/experiment.py,sha256=73tdQrbWqtssGEhAo62RNd8tMxQFCV9rZwMCMlYXHco,4328
labml_nn/transformers/glu_variants/__init__.py,sha256=6b5uNMMLnOy7PWcm2LS3zI0wT80gHEKL5bMJROthZJw,359
labml_nn/transformers/glu_variants/experiment.py,sha256=-tmOdzIInsAmlxB8r1xox8UOQh8AR-j16xuUbdfDTAc,4296
labml_nn/transformers/glu_variants/simple.py,sha256=kuRONPIAtQZWT4a34oQpOae78yQUsscSTHzlURx9G0U,11980
labml_nn/transformers/gmlp/__init__.py,sha256=39Mt3bmHvdojFOyRAo804BE4TyHmeKdGOZQv1tYD54g,6158
labml_nn/transformers/gmlp/experiment.py,sha256=Ujqxe3Uhxyr9G9hfO1MgLo-BFesO1t-ZcTS6N6Z7Le0,3281
labml_nn/transformers/gpt/__init__.py,sha256=vnduF3KCbl65m0PNFHy725edoomF-4k6fNB4pLP8Tyo,8709
labml_nn/transformers/hour_glass/__init__.py,sha256=H4M6_ukvzoYQfBNlwhWFkvMJ8n2vxvw6AEzeNpm1GKA,10348
labml_nn/transformers/hour_glass/experiment.py,sha256=OxD-Q2M2o5-GZw-f0bKTi_TPFILmPm1qdl-n-G0RjZc,4822
labml_nn/transformers/knn/__init__.py,sha256=qYSyuyVujWjG4l8KOOm-jMk4ndMIQMp0maRM6OBDhwc,1974
labml_nn/transformers/knn/build_index.py,sha256=0mczWS84WZC66zykHEqA4jzdEaIMhJwYewQnA8Xf26o,5712
labml_nn/transformers/knn/eval_knn.py,sha256=0AwZKEWjOmd44D5GJEvMIz8nvAkbJLN9lXiJfOvi4VQ,5916
labml_nn/transformers/knn/train_model.py,sha256=swP-2KiEO05tBuWzyHH3ZCvMEBNsDH59Yxa6PdEe76A,4481
labml_nn/transformers/mlm/__init__.py,sha256=XOZUWrt5WZZaDTilhfPJhV3KlfZMsskrYGcJ7d4uk1A,6405
labml_nn/transformers/mlm/experiment.py,sha256=0N6-DzU7UuLENFt_3wXXMGvU_1tXCDYxZINUJdgDqoI,10183
labml_nn/transformers/mlp_mixer/__init__.py,sha256=sb7vmahiyT9tQzO1lRjGrKrFDUSPbvOgU-67KB-uOXw,2956
labml_nn/transformers/mlp_mixer/experiment.py,sha256=VokvnvAfTdJeBIBYKuQo0yFaHBzHbX7OLIsyr_Q60yM,3030
labml_nn/transformers/primer_ez/__init__.py,sha256=jYNyRhr8JaEFRVCTXDIdNNtj0yjzzmYYMBKIlc1AJKA,5008
labml_nn/transformers/primer_ez/efficient.py,sha256=Z6W8EpJAbBmsx0l7NX6p9TlW8WytG3pRBOu_YazripI,2197
labml_nn/transformers/primer_ez/experiment.py,sha256=CDURim2Igt91cleq3c1JwbFglAx2-BsRoN5kgL2JzVU,4300
labml_nn/transformers/primer_ez/variations.py,sha256=sVQZhmEd3e2567H2fXcGuBmMRYMt3Q2RW5k5fLCcTHI,5575
labml_nn/transformers/retro/__init__.py,sha256=2ZPvFEolvoADMHDQnoB0IrNUiy6IpSc9t-aDAJoNd7w,1555
labml_nn/transformers/retro/bert_embeddings.py,sha256=CQCkbAxcFsWimQV4rqJjCYYC3Xuey1hfJCfbhgIh_mo,5243
labml_nn/transformers/retro/database.py,sha256=v3XHfueqaY6Yv6SPXgkecS5UlUGrwADR8LliNvne-ts,5973
labml_nn/transformers/retro/dataset.py,sha256=DlimiL-gygmtE0dP9WzGEfrx3mtwzC5aF0dR2sqyrEU,4109
labml_nn/transformers/retro/model.py,sha256=pLZSOrlHUikqUWJVeGcC7J1zHhgcCpvDbXvHuYWAWek,22375
labml_nn/transformers/retro/train.py,sha256=QGrtu7l5bq1Bmzo_h2zH2465XcgDihrzlbxgvS9-cVU,7297
labml_nn/transformers/rope/__init__.py,sha256=6PjyyyMtK3sl3TT6JkqnrA7qP6AjMrnl-o6Auud3ooY,8281
labml_nn/transformers/rope/experiment.py,sha256=K84VF8nFhzhaO9QJaVnGgihFyYyiQzVszgVSzCc1zs4,3132
labml_nn/transformers/rope/value_pe/__init__.py,sha256=oFZBDCbbn3BXTy1JO8t2nsJ_2_nAtb-dbkY9PLuM9vA,9354
labml_nn/transformers/rope/value_pe/arithmetic_experiment.py,sha256=K-bU-zieDhw7orlTsvc3Z0voCXIpctdaczjFm6PagIE,2881
labml_nn/transformers/rope/value_pe/experiment.py,sha256=rnLUo2QyKUxk2xkEWpwMVzeNrl4l7nvRhHqNoqX_G28,2970
labml_nn/transformers/switch/__init__.py,sha256=JZ66sHsy98kbUZ5uiiQsIF-gG4NBQ4SNKhGpwM4Et-s,10278
labml_nn/transformers/switch/experiment.py,sha256=jAV3rrFlaU2lNq3opyzrvkIfVVrAR5OwwbppCYORv9I,8818
labml_nn/transformers/vit/__init__.py,sha256=MQlssaDefBYwE7myEErKQwkBQRUYW6L--TQFNffjzFA,8062
labml_nn/transformers/vit/experiment.py,sha256=XvrKDh-Pnb8MIldWaWzW8kIP6haG0AILOG3yDBMF6GU,2861
labml_nn/transformers/xl/__init__.py,sha256=ELUlcpFmX3p1TN6cLTeNRWZ8cPMA7yXrMeYvelPZOSk,5474
labml_nn/transformers/xl/experiment.py,sha256=rnnP-eNw-iUA7_b0GxnbmTdh067aluHQyLQwRzpfsaw,8779
labml_nn/transformers/xl/relative_mha.py,sha256=hP4dclRyenx4bvvxy-xbEgrJzDuje60h922lURYS-A4,6390
labml_nn/uncertainty/__init__.py,sha256=sjUswlKv02xeyEg82-scfzT7xnlqtvzY7RpjvD7nN4Y,383
labml_nn/uncertainty/evidence/__init__.py,sha256=cVZ3ls8Tk1eH-M1SYiCOzIzthoWT08FuQqmyCpzqozc,12716
labml_nn/uncertainty/evidence/experiment.py,sha256=v5qF8jJVSTBkhIY7iDEbsw8k_gGfdKJJPqeDs6teXzg,7288
labml_nn/utils/__init__.py,sha256=vb8UzLZ37o2jRaIjJmQrO96fP9YEKht_ODl47DoCaVU,1550
labml_nn/utils/tokenizer.py,sha256=SGO0HSSMrP-K4CoS28ZweKPUwemEPXjKO7D-qbrfRNo,961
utils/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
utils/diagrams.py,sha256=Lw7blOuW4Ty7n5QmWXGeD3NbcQHCysPp2D_nQ8jInSQ,5517
utils/papers_list.py,sha256=1FqIUg3YVkKWnX6y4VSqTDqKSZekmnCU0BsBaUqV1As,2496
utils/sitemap.py,sha256=Zp_m4pTp7mRFOMe2d_iOHvqSfSq-QusWFcvO9fZyehI,1486
labml_nn-0.4.123.dist-info/METADATA,sha256=0RN1szxqMHegvOkaCBZVJDXIfWC1UU1MNw200RjeptU,12286
labml_nn-0.4.123.dist-info/WHEEL,sha256=G16H4A3IeoQmnOrYV4ueZGKSjhipXx8zc8nu9FGlvMA,92
labml_nn-0.4.123.dist-info/top_level.txt,sha256=Fh9Z588ERJZcyAsMmOUliiG8264Fl6WSupGu5iLLyr0,15
labml_nn-0.4.123.dist-info/RECORD,,
