official/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/modeling/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/modeling/performance.py,sha256=A1GqctlEtpDTDF_-r8YG4AK_AJUu5uH3gnxTrAd5P38,2331
official/modeling/tf_utils.py,sha256=5tVvyzdeld0gcCz3t1ION9SNU0wmtew7iWS0qC0appE,5438
official/modeling/activations/__init__.py,sha256=VTQaHETsaI96gwc46niToNfXBpIkUisrx5lDNamBerM,956
official/modeling/activations/gelu.py,sha256=ZhK8RiCQIzcQ-KYIvbxTIM8MupKJm4LeZy44UEgT2rQ,1296
official/modeling/activations/gelu_test.py,sha256=gsnspVFryru5Q8ow0f1-IGqZMTWG8ATnpxSCJpMsFwc,1402
official/modeling/activations/swish.py,sha256=u8Gr1e8Kj-dXg5pjtzjwW_B2fcNLVYfm1b-pokTIHSY,2451
official/modeling/activations/swish_test.py,sha256=SkzVu_YUQXBH0A4nQwRxsWFKDpaIMesmwurWXppqyY0,1757
official/modeling/hyperparams/__init__.py,sha256=Qy5C80tKMegIpUOsaDkqDNf1cO321kcPboGmB0NS7yc,894
official/modeling/hyperparams/base_config.py,sha256=AXTS1bRoldSjE26R8EM2j4zJwkq32TSxkr1wgW4m57U,8964
official/modeling/hyperparams/base_config_test.py,sha256=f9i3QiWKiNapNXkbIRh1wmxT3lAWZnrnJpeZnntLu_I,9013
official/modeling/hyperparams/config_definitions.py,sha256=bIWKRKmZs4jujiGa57_32-FjeMLfs7gR7mb3QmeA050,6529
official/modeling/hyperparams/oneof.py,sha256=SbInXsax76kI5YL6gK5pnSp77aUv3rmL29fIVP_tfyo,2008
official/modeling/hyperparams/oneof_test.py,sha256=Upg6bcXDQ5KELeMlXcMk5OHwk5dRkYUakdGmA2VG7B8,2017
official/modeling/hyperparams/params_dict.py,sha256=MOcxH2dfP_sGYZsbMQR7v_-DpRxaVfScQ44uawjYvu0,15937
official/modeling/hyperparams/params_dict_test.py,sha256=3okacRwD0aub90uFX7iAMgvlBS43fxAJouyi7SU4Si8,12621
official/modeling/optimization/__init__.py,sha256=6K28ceBXwl9jQshpYb4hbhYQT8icVYQ7t9ydDoteeT4,369
official/modeling/optimization/lr_schedule.py,sha256=y7DW2dc5t-UlY7k9Fn3RrCiVpz8wxhhq8qdWnIvkf-Q,3779
official/modeling/optimization/optimizer_factory.py,sha256=tyY37s1AUE54gmFPRS5pNK6K3Ni6B0arPCbGBm6dhkk,4643
official/modeling/optimization/optimizer_factory_test.py,sha256=IuR4Q4QnUILXMiumNj0XDTxlktzmfxC0-Mo4KIh4JU0,7732
official/modeling/optimization/configs/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/modeling/optimization/configs/learning_rate_config.py,sha256=t2p2ln0Z2VIpNWDzOTBWTicQG8jd3rKniXuvuD10emQ,4982
official/modeling/optimization/configs/optimization_config.py,sha256=na5Z78ULcBOltRaJ_MCKeHxLH84iChASojE3QFrMF6U,3116
official/modeling/optimization/configs/optimization_config_test.py,sha256=uB7NgpP3xnvh7nOefX6GLx0oVOTmI1owoL7kyQ8CYJk,2164
official/modeling/optimization/configs/optimizer_config.py,sha256=MAVCQaaPhXTkCJlcEZV14H4q00T1EvMyAiWkJG5jZyc,4619
official/modeling/training/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/modeling/training/distributed_executor.py,sha256=037TQh2EqpImh9tVRXtJYsfzqAF95ale1lyaR4wWeGc,30220
official/nlp/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/nlp/optimization.py,sha256=RtuC0GfQTnogL9ieRvPPvyg-DKTTcO835qgL5ziyb8s,8809
official/nlp/albert/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/nlp/albert/configs.py,sha256=1c_B7g4PoIxvt-hdK_93qZeUfOZ8RXDTUJCVVWEt0QA,2261
official/nlp/albert/export_albert_tfhub.py,sha256=0PL3pP6w0jCMqDNNy9iZHKtmi5zSYTlwRCmNRER39jQ,3461
official/nlp/albert/export_albert_tfhub_test.py,sha256=SGMxkdH9etvfV3sTYlIuC5WFCRXIdwfdGuUBpO32pXE,3529
official/nlp/albert/run_classifier.py,sha256=BdzjHzfDJBNnANem_R3h_PiTmBhYuS5KoYjM6mYnnTE,2317
official/nlp/albert/run_squad.py,sha256=xN98WMeRSeS0Drsrdin_Fz9XyDEPseP89ES16QoUlzo,4916
official/nlp/albert/tf2_albert_encoder_checkpoint_converter.py,sha256=n6mOR3CrlmiVKXzmVm0QF1LKe_k5o7i9YPzREskcEsA,5086
official/nlp/bert/__init__.py,sha256=AbpHGcgLb-kRsJGnwFEktk7uzpZOCcBY74-YBdrKVGs,1
official/nlp/bert/bert_models.py,sha256=gEw-e4xq_hwqDjl5tGYI3l1rO7gQLIDWL5Y16NNGqt4,14428
official/nlp/bert/bert_models_test.py,sha256=rloPcdQP_wTSyQcfQBikDyAhjI9a6VcqYSj0n3coemM,4412
official/nlp/bert/common_flags.py,sha256=6rf9PaCO50CzsdKBUySaPTh2F8diGRsAIGnwZho5kB0,4234
official/nlp/bert/configs.py,sha256=yMMsz2cKpWgRsqdoUQZ1xFJZdjrC3c5i0igxXnj_kng,4357
official/nlp/bert/export_tfhub.py,sha256=15AzGPOzQXGiCiSUoBLLeoXI6nndDlXpIOXY-69XYFQ,4017
official/nlp/bert/export_tfhub_test.py,sha256=4ynVECT2VoOZkLViZjEC2f5GIXPsrKztFkyoIhP1x4w,4732
official/nlp/bert/input_pipeline.py,sha256=xOZiKv3W-qXFIazL--mR2EHWKvg8Un1h-OlZzmddV7w,9497
official/nlp/bert/model_saving_utils.py,sha256=E2SpyEXNwNabDhx7OoZQRC-u4lHc_9maSAsdRs_K0E4,3280
official/nlp/bert/model_training_utils.py,sha256=2w6opKxOd-ASXVppZLRCrI9YAS8_af5b-Lun6azqGoA,23704
official/nlp/bert/model_training_utils_test.py,sha256=rp8PtdFgal5CB15g62qQBOCGv0Yu8URiJ5shLntZ0uY,11772
official/nlp/bert/run_classifier.py,sha256=dN5CXDIGkG0F44fZqj2guuqbI8ch9niBh37DZmhvrS8,16253
official/nlp/bert/run_pretraining.py,sha256=ys8DSKhzOEtpFm58fVmPdDJ_wrODWr4SmoUp0gKhB8Q,7381
official/nlp/bert/run_squad.py,sha256=BiYy12_0CCvqU3HTCY5yP10JHcXnWLZII7ZisluI5YM,5586
official/nlp/bert/run_squad_helper.py,sha256=xfocOmeaSrf-njn7VitAHC1e2Lpqbjy15xLIxA1GmGo,17248
official/nlp/bert/squad_evaluate_v1_1.py,sha256=PhOIrSWoch6AyStpfZqyR0Xf8qbbV-81Z6Y99JJNQ_M,3911
official/nlp/bert/squad_evaluate_v2_0.py,sha256=wGfbm3VrfI75MsTDoY8DDVA2D6k5UtneHcCDrcqe-DI,8813
official/nlp/bert/tf1_checkpoint_converter_lib.py,sha256=CAgH0kiRLpqxVecbvYRhrTA-VbFmYaVI1_aPFkKGhS4,7721
official/nlp/bert/tf2_encoder_checkpoint_converter.py,sha256=iDpCa_3qp6KNwm4mlqmTwdqV2bV7nPdAPBRS46c7M_g,4061
official/nlp/bert/tokenization.py,sha256=UP6AB-vqLeVqWiaFTl4Z4kt7Bdx99UIucYRxnrhyqVY,16775
official/nlp/bert/tokenization_test.py,sha256=dImkj4K1Hluu-KZyUCvpfjTqyl4H7FTCHFWL8CpU0k4,5406
official/nlp/data/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/nlp/data/classifier_data_lib.py,sha256=h9KuYu0Blp0onFOCWiX_KudGBVhBip64UCeI3RHKUSQ,31734
official/nlp/data/create_finetuning_data.py,sha256=el9Z742ytH268sO6N9xfxkTWGD4E7PwpATgB_zLqdu4,10106
official/nlp/data/create_pretraining_data.py,sha256=1iFeEeg__IdVaoU0B2MFEZei1a3PJM_S00qcGad1hgs,17211
official/nlp/data/squad_lib.py,sha256=hpy4qbdsUl3wyX2M5Hbm7PoEWT17IMf4sSAXtw_jOeA,33460
official/nlp/data/squad_lib_sp.py,sha256=9XBJpGhQvAEiP6pwSzwwNAnrLCMEM5F7N_4xLDXRSpc,31764
official/nlp/modeling/__init__.py,sha256=AbpHGcgLb-kRsJGnwFEktk7uzpZOCcBY74-YBdrKVGs,1
official/nlp/modeling/layers/__init__.py,sha256=sPdYtMKn3hmi7CgBf41_PBJd9EnwZyToYyUX5s3PZtA,1621
official/nlp/modeling/layers/attention.py,sha256=hkVT326AGzvbWdo1_xdXE9fog4e_r7M8lhcM-RNj2bc,21642
official/nlp/modeling/layers/attention_test.py,sha256=FirEeqhimwuk8LjkQX-5jw1kOVdQ87bo7zgW3jeOWGU,10664
official/nlp/modeling/layers/cls_head.py,sha256=lACe_hpRRGRrvUvJ7ztBNaxifTq6Xv-Q9iYwCdCrUSI,3206
official/nlp/modeling/layers/cls_head_test.py,sha256=_mEk4_9fo9RCfLDJubuCXOpSEnOAqk_4VEtFl0YU8e4,1581
official/nlp/modeling/layers/dense_einsum.py,sha256=OeWUKmtT0N7mMJhZ2XN9H9m_XdbeGLGBBUsNNnJNUhM,7153
official/nlp/modeling/layers/dense_einsum_test.py,sha256=Z_7nTb9cFhvghftg_Jidj_AsjhByLOMhficIyB82UH4,5499
official/nlp/modeling/layers/gated_feedforward.py,sha256=efZrjQhzXwnyipd1X5WHf8-nHOhLymLmNkD6eQ8XcaM,8558
official/nlp/modeling/layers/gated_feedforward_test.py,sha256=pvZHR9u8YkDvpmYBlNrb05CvmIPNUEmw6lxaKo91lug,5013
official/nlp/modeling/layers/masked_softmax.py,sha256=c8ksn7Q8R-w-Ga7oRMBwsDhanmG_O1UWa0oSbaR9PMo,2883
official/nlp/modeling/layers/masked_softmax_test.py,sha256=W73ipb_qUagweHBtzFyPU5JPb7yV4AOqWX4q77D03o4,4499
official/nlp/modeling/layers/on_device_embedding.py,sha256=c3uQ2Hzh-JJBv_CyjTKe5_5I1of4B1xcR4NuU5DlxME,3561
official/nlp/modeling/layers/on_device_embedding_test.py,sha256=u3gkxspgzZl7SKLRwtvK4C37WgqasrZk81RdkGIK0OQ,8098
official/nlp/modeling/layers/position_embedding.py,sha256=m4gZfovhOfEZT3v5VjPhEZIWhIpAo6ivvhADq7FfKFg,4841
official/nlp/modeling/layers/position_embedding_test.py,sha256=JXDUR9uv1ZjLBmxTZfhZxurWYzM4GBiwqiHbe16Jb50,4574
official/nlp/modeling/layers/rezero_transformer.py,sha256=mfB0d_2BSSqMEFsQdNHiQuH5etjL733jvHI47areO7o,10732
official/nlp/modeling/layers/rezero_transformer_test.py,sha256=Et1_OcGXpWmHm8PWKpYzD1GZSBwxjCctfxlgX8MGApc,5249
official/nlp/modeling/layers/self_attention_mask.py,sha256=iUNM3Z2c5JwNEzM2MYhvlzhIvSQkZndd1sGgPNet0SI,2326
official/nlp/modeling/layers/talking_heads_attention.py,sha256=lnPr_EF7LEXH_RFRQT2Mj9vTYVk3kv_A2cK3AZ9_ZR4,8793
official/nlp/modeling/layers/talking_heads_attention_test.py,sha256=RhUxetm2UNhcHw4Ted1BXBrCC15JlfWWOVU-eH-DjTA,4090
official/nlp/modeling/layers/transformer.py,sha256=IKhFBTh-2yeIeUMNQDAYh1CLuURmD2F_oLmzwI55KnQ,10679
official/nlp/modeling/layers/transformer_scaffold.py,sha256=oBm4wmaKFNpk0xeh4_lkZgwKp70Epb4A3xQNfwaG4YY,12177
official/nlp/modeling/layers/transformer_scaffold_test.py,sha256=jlTtueo8m3q2dQqrlhocpGAQl0mOkNWxbKvVTaeWstw,21798
official/nlp/modeling/layers/transformer_test.py,sha256=dCXST63181lg8VMqg26a_UFq8PpX9MgdKh161BWH66M,9363
official/nlp/modeling/layers/util.py,sha256=MpxP3z-wfu_48RxqVi9j2PkLacJX_taZPPEjIcwihKE,1836
official/nlp/modeling/losses/__init__.py,sha256=4uryr7_r2Mauvn4_2GLFNHXnjyOoWk0-Bb-GIpkVnQk,1042
official/nlp/modeling/losses/weighted_sparse_categorical_crossentropy.py,sha256=_0VOjR138GJaWonezczMyJ-Bmc152C9ppFTt_TE-Whk,4278
official/nlp/modeling/losses/weighted_sparse_categorical_crossentropy_test.py,sha256=V9h1i9_JXZqIV3ywkC4vM8Y7mIfjBnILznzfd9pq6Rw,16536
official/nlp/modeling/models/__init__.py,sha256=sIf5Ojo-U6viC5R3xNpx5fPhldvnyYH5QxM0AP1BJVY,1024
official/nlp/modeling/models/bert_classifier.py,sha256=HVTVNJxzd7rxCU1JD0GCX_gckFrZD3trMX2z4qiyT30,3499
official/nlp/modeling/models/bert_classifier_test.py,sha256=oOpa8wSlm43ASa7f48zWbgzeZDDyV814HM1tcxhuRvg,4653
official/nlp/modeling/models/bert_pretrainer.py,sha256=eEMnpcfRSFLcSj-QBV5tOrpuQsbxSJJW_ovkpj1i4mw,5400
official/nlp/modeling/models/bert_pretrainer_test.py,sha256=GbBzPBJ1-hhPTbXj9Ys2gXsMsjDaJBQeWBppnuLQ4Jw,5038
official/nlp/modeling/models/bert_span_labeler.py,sha256=jlEz8LOcnMbG_HekgKyxIzbciI2t5Pcp3lcqHX6ls7M,3763
official/nlp/modeling/models/bert_span_labeler_test.py,sha256=8DwLMt4S4FjN-RiCpSMzNdBUWAoTPUXI7lq-gkDzc6s,5369
official/nlp/modeling/models/bert_token_classifier.py,sha256=Hqb_vqHzirTe_9bAUMOndz6XGGqp7lprd0uCOkOC9_g,3565
official/nlp/modeling/models/bert_token_classifier_test.py,sha256=MZuydwsVH1IGwv2651L8yPC2je1X18-sCxjtzTd9ifE,4770
official/nlp/modeling/networks/__init__.py,sha256=MkB45mN25Y-6CNDNeXnJi19x4zeiime8m8rNoRfHbcU,1266
official/nlp/modeling/networks/albert_transformer_encoder.py,sha256=OTc3m-QVWzg9zUUCfdj25pqzBtMAALST25lsINIMXG8,7874
official/nlp/modeling/networks/albert_transformer_encoder_test.py,sha256=Day_4G-JGe3taxafXSq4uaSn8th4FK9bIIvLkdKgtvU,7119
official/nlp/modeling/networks/classification.py,sha256=upMTd-UioFeHZP5Grqnb_LRSli3lTWNadZ3bYTefnhM,2943
official/nlp/modeling/networks/classification_test.py,sha256=WnjLdM7-Xw6H7THyfKBUOwG-xaYVmR_37X3JajqbdPw,7401
official/nlp/modeling/networks/encoder_scaffold.py,sha256=Jtil72GFG8CxKXV_vEsIP9_1cYf0P1ia_tHWgvdWz_g,11351
official/nlp/modeling/networks/encoder_scaffold_test.py,sha256=wVk80I2AUIsbABdGrCTREuxHUTYnxz8PseDgHl27-qo,23927
official/nlp/modeling/networks/masked_lm.py,sha256=gGn5SPFQerDIvv-Cbq6dDhyfmFgItcBY0usF-XSV7-s,7428
official/nlp/modeling/networks/masked_lm_test.py,sha256=6O4CMYONleuJKKso5T8Gj4U09zjastmTFrEw6gAYBwI,9060
official/nlp/modeling/networks/span_labeling.py,sha256=1yjjM02b_LBp5w6BhR2hc9ASkB_lnol-b3WbJMq-rdo,3362
official/nlp/modeling/networks/span_labeling_test.py,sha256=uexaHX1Ui05u3FFtEU2G40kiLgtgJgfpjCW2Sq2HCc8,7476
official/nlp/modeling/networks/token_classification.py,sha256=69mKnvYFsSow990G2Z_EDQ61JA_12vV_ijOAVCW3RtU,2981
official/nlp/modeling/networks/token_classification_test.py,sha256=J-6eQT3rty1pVI0cMm2wjSAViIys-S3odiunkTBTkAQ,8135
official/nlp/modeling/networks/transformer_encoder.py,sha256=Vsa-EklbfZPXL0bp00HxkrINybqH3_FzZ2eP_gyNuak,9354
official/nlp/modeling/networks/transformer_encoder_test.py,sha256=1mVTQrs6nWjafQwiw-poZGjKOgM9k7pPyYVVgupcH_s,9778
official/nlp/nhnet/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/nlp/nhnet/configs.py,sha256=BKuAsrYJ7NlJ15si5HsdZF5hSlHjhQcO8ATLhFZB73Y,3302
official/nlp/nhnet/configs_test.py,sha256=GRL_efcE9v1finOfwPLTTmfkbjCT5sb7MusViHwjkKQ,3192
official/nlp/nhnet/decoder.py,sha256=aeFNSd7xPTS86oE92zvy8_n84C1wtTtu_LoBrYBfpsU,21805
official/nlp/nhnet/decoder_test.py,sha256=m4Pw7sScMcPgOd0zzV8hXPzLJqeP0efnvcqlO2c0wdQ,7598
official/nlp/nhnet/evaluation.py,sha256=U1TP6EU-ENa4hojzXzPoS-BJluY7mG24Y-S7UPrvLZ0,6329
official/nlp/nhnet/input_pipeline.py,sha256=b5XWqi5HZG6kalr8j7MWl8S2N81Owxx1Z5FpfMOTC_E,9292
official/nlp/nhnet/models.py,sha256=0ri22oYKP2QzQxJIvpwb5TaqjXadaei-JPVCMcWL57g,23345
official/nlp/nhnet/multi_channel_attention.py,sha256=UXyNg7ChCHkeg_hYH5ULzUaqqJInDiQnn4oQF8uXA-o,6089
official/nlp/nhnet/multi_channel_attention_test.py,sha256=Sbw-xObxXbIcxZ_a30ppdGvi5_UMwVSwnCVh5uok2RM,2011
official/nlp/nhnet/optimizer.py,sha256=0C0dr79qqfpFbGP4M4hMwo2MPYDP_hPbGa60DCX0jMA,3030
official/nlp/nhnet/raw_data_process.py,sha256=P4B67wzeHS7eu-yAdNE4kQGulXXzEHAywom__aVcniY,3828
official/nlp/nhnet/raw_data_processor.py,sha256=JZS0yryFApB1FfydDOG4xr0PpZkO6_Anjwd7qXSOz9E,9334
official/nlp/nhnet/trainer.py,sha256=7qbwq1T_VmfgWR8U7oJJ3w7NMIVuP35z3M9Ckf1c88c,8616
official/nlp/nhnet/trainer_test.py,sha256=XpIh06yrGw_MslGHYZ1wLWLGwmLjUhZwJZF9p-WTOF8,3390
official/nlp/nhnet/utils.py,sha256=u2UFw9zbQ-naWhHJ2ysVqAEWUqnqpthI3EqNUBbOlyI,3521
official/nlp/transformer/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/nlp/transformer/attention_layer.py,sha256=7Dk8immlFwAbhHfeZa7D_JhJoYcvz-X4mUPM1nCReVI,6953
official/nlp/transformer/beam_search.py,sha256=FCqZXwRDwtHCvTquRzb-hyHKarBzbjQ_F32JMwKZbbU,5467
official/nlp/transformer/beam_search_v1.py,sha256=Yj4b1QIJZiBZLAIEZdrveF8to7sKgxu0YTJwZB4PAdI,27301
official/nlp/transformer/beam_search_v1_test.py,sha256=XxWgECKKCxOXOJtEi0N5AbaxWlbxbYqqk_P8-QMIbrs,3370
official/nlp/transformer/compute_bleu.py,sha256=013UgTM3JueRNgfn3_8U8e9GE-l3qTGNIoDZ7Y3srmc,5173
official/nlp/transformer/compute_bleu_test.py,sha256=H5UgbLbicajfE7FIJMyx_wrdsgJzSB_LPC6FfCDunWc,2347
official/nlp/transformer/data_download.py,sha256=2NHG4RGbTY7iyY_zg6ldoG-KAcmw_1Ne7xm2ny1PZxM,15381
official/nlp/transformer/data_pipeline.py,sha256=sGfQUGc9itwALWSJZMHDRUOOIpARbjJKftv0pgjFqV8,12996
official/nlp/transformer/embedding_layer.py,sha256=vezRJR5yovi8Rszi2hMxX14ekJS0jC4x1pIZbzVxA6k,3842
official/nlp/transformer/ffn_layer.py,sha256=jkxrmzwHBYFV8lTlGa8j7IkfBaspPKeOQSFeV2A5tSE,2570
official/nlp/transformer/metrics.py,sha256=H7e1KeSVkUkxR6QW2y80P7vijFgUDfLKTLuum8xA56Q,7196
official/nlp/transformer/misc.py,sha256=aBJCMHbVYNMh3iMvLNqYOPbFeN4GDkvxhny7H72xPkY,10088
official/nlp/transformer/model_params.py,sha256=njFMLgmNuvgBtN9DID7CoaxLbYiS4KVI_9CQp9bQicg,3021
official/nlp/transformer/model_utils.py,sha256=0eAYJ7F9pZL9pZq6UW3nZ9jeu4xNSnLzjeCH-PHTNS0,4572
official/nlp/transformer/model_utils_test.py,sha256=yRC4vBAro6uGZbFU1cPaJfXrxWWWOUgT7j6zgkRLFSM,2235
official/nlp/transformer/optimizer.py,sha256=isuW5AH-PXWZviBamVkEt0f1X_-gpWGnaBCUM0ZAuvU,5161
official/nlp/transformer/transformer.py,sha256=fqTXluenFdPJbdPT78tllSJW7CeypmqqbIMn05sqsYY,22223
official/nlp/transformer/transformer_layers_test.py,sha256=41tMIqryJl4Yq2nNvXT7QoIalF1YhCfLMBrmOWWG90s,3468
official/nlp/transformer/transformer_main.py,sha256=7VrB-GweIOu0Y8BHl5R_v_GdrndbjgywDaiBiJ1Oks4,19000
official/nlp/transformer/transformer_main_test.py,sha256=F5i_1uCDUvZQ-x25Zbqi6OZ1N8-xMrJ_9ObfIOF4HP0,6547
official/nlp/transformer/transformer_test.py,sha256=0Yz-tWTADBibXQ_W7x09L4uqXrVpt7ux9bGL8FE6WTg,2584
official/nlp/transformer/translate.py,sha256=FrtwgnNcR21pnIh5wsx80No2i192Oh7cxQHgNgnp1As,7408
official/nlp/transformer/utils/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/nlp/transformer/utils/metrics.py,sha256=FnsXmgS39stza0-E0-N-MHeTEbpeE1tl6UmxHMpgj90,16579
official/nlp/transformer/utils/tokenizer.py,sha256=imT2e4KFBPlX9FyBE5CGwEIs_BK8jD3CgKO8iLTd-wk,24597
official/nlp/transformer/utils/tokenizer_test.py,sha256=gH2wQXzT1PX6wMKY5P_DTPC1g4L5Uq6EK1Bu_HcPWl0,6735
official/nlp/xlnet/__init__.py,sha256=AbpHGcgLb-kRsJGnwFEktk7uzpZOCcBY74-YBdrKVGs,1
official/nlp/xlnet/classifier_utils.py,sha256=ZiOeoSR0a5_XDji_6kPwGlUqgTSvyr0FD7ebZckgigQ,5497
official/nlp/xlnet/common_flags.py,sha256=MOzG2ZAuiJsNbopxHKvv1H24aUOK6AAysrHLv0ocVGw,5605
official/nlp/xlnet/data_utils.py,sha256=hHOfwx6_7iKjQL1eDa_kCF6nThx73fLtuVMbnb69_tA,30481
official/nlp/xlnet/optimization.py,sha256=8vf55K2pcu4jiFLrywlOmDhTUT0c5RN8LJTaXd-QTmk,4000
official/nlp/xlnet/preprocess_classification_data.py,sha256=z9BunExYaErluu6hM5Axfl87oQkgpB7UsOd-LYphczA,15508
official/nlp/xlnet/preprocess_pretrain_data.py,sha256=3kbFHyhCoNkyajNKcFu1Z3uCw3EI5UsOmZwNMVyJQEg,32493
official/nlp/xlnet/preprocess_squad_data.py,sha256=s0O3UOiVcUT7XjPjs6BwZx8eZ45C_-rcUir7Ri9s-mo,4213
official/nlp/xlnet/preprocess_utils.py,sha256=xpFUUFJpJNgI2AVMxmH7bTGXE4NqG51-fBPmVj1PL9Q,3807
official/nlp/xlnet/run_classifier.py,sha256=9NadO0_BrNuOIO2asPN7phRtwaXYGeg-NrJjJCCt2qw,7417
official/nlp/xlnet/run_pretrain.py,sha256=L9pcN8K8wyw0I63TdrUqf5zlQwHiqXiIAlGdbUv1ZB0,6250
official/nlp/xlnet/run_squad.py,sha256=G5rDtNoOWyzluQ80akm8t8HTxYkwh0s8VClQGFhObqE,12035
official/nlp/xlnet/squad_utils.py,sha256=tOafmFmTZg-5UctZhnFbA9x1u9bhCRtejXbjhwEyLzA,32311
official/nlp/xlnet/training_utils.py,sha256=D1rHg0erZqlvz2gc9zhORA31lPgu_9G5xuXLCI5zhLI,11954
official/nlp/xlnet/xlnet_config.py,sha256=PNfS7aCWs6Bt8R3T2BsdIQESezCcLg4NmPYdoFLY_zY,6110
official/nlp/xlnet/xlnet_modeling.py,sha256=LSGoxGrotlRfLVjFgdBzAPgvuwzcBkWiOdxzymX8OKs,46062
official/nlp/xlnet/xlnet_modeling_test.py,sha256=CVjn_3J1VpfwqJAxp3qXINUMowTGplerNhMaKEsk24E,1869
official/recommendation/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/recommendation/constants.py,sha256=tDoGZ8TIt134CLl082kTi75Q45dWxIpy_zJyZxvxqJk,2979
official/recommendation/create_ncf_data.py,sha256=PuljSRMJuCOr72YfxToasiQyK1QZaY0Vi5jbWB6Qxaw,4189
official/recommendation/data_pipeline.py,sha256=WkhEX3Zz9OAY4gNkFk1grTBLVza-rX0fuxAAhIx0lX8,37063
official/recommendation/data_preprocessing.py,sha256=dbGeDP9lP7IxqRWy89l4EDYvV8hjgeCeGffurM4NUiA,10544
official/recommendation/data_test.py,sha256=WchjlXDtQBLO5c301OLtedKfq0qNYMpWThXKicLWeps,12897
official/recommendation/movielens.py,sha256=K64ff_PpTTfpKkgnLKRunhTq_pH1DF_VpapdM7UOTJo,9794
official/recommendation/ncf_common.py,sha256=v_jnSWeFZBTHUXXhzgQ-bd4K6MFfMo0T_Q2WNw6OOa0,12365
official/recommendation/ncf_input_pipeline.py,sha256=bvXXeGFFs6a18K8hGGU-HVx2Gh3da1_RqM0uAhuFksU,7132
official/recommendation/ncf_keras_main.py,sha256=raeJZGQYweCadfjwycAnmoiPs5wG7EIrXJLQhSvVwag,19555
official/recommendation/ncf_test.py,sha256=36R9UOp0uBW31HTypvO4emGk-Du4crRyQ-v71rZ-omA,4327
official/recommendation/neumf_model.py,sha256=HeBjFL4sZrshPRtC9qxJGEBCAahEBRR4CWrTHt6eNtI,17025
official/recommendation/popen_helper.py,sha256=moFOPlnWDGsOtZ3gOBQNB2eMvIYuq8GTXaDJgqY6U-E,1997
official/recommendation/stat_utils.py,sha256=vAj0vP1S1N_9kaWMJDEVxcURIpOn8yeWX_f1vg63jIg,3179
official/staging/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/staging/training/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/staging/training/controller.py,sha256=r7zzo3kjX50Y-B436_pkD7ShH9mpo1vho1D6nzzTZUw,13999
official/staging/training/controller_test.py,sha256=zJpxjiprCovU3b_1bqyIOou1NLa6J0mVZHPQ1ft_qWQ,11049
official/staging/training/grad_utils.py,sha256=HHZUPUrsqHt3HJFExi5rCGs7oCPLaSMtqKSO9-HVUzw,6284
official/staging/training/runnable.py,sha256=SOrowN_RiCCndbe-5hoOM-Iq9M550zRoI_dKKUEleA8,3162
official/staging/training/standard_runnable.py,sha256=15FLE7KI3bEiC4geZyZVRD06r3pMZExQlS57T6eTC6s,5941
official/staging/training/utils.py,sha256=FW1GI4ZH-MgVYYCGL5gVsTWhgoddidF6h-RHS77-ihk,11076
official/utils/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/utils/hyperparams_flags.py,sha256=Hjuc5iT4VAXWEvphT6Dlt3KzP3AvPVreOu0Rdgxb0jo,4846
official/utils/registry.py,sha256=RiJS3zFuq0oL2wKz4xwJpcy7UWbPGUNZYnTkUTWP4is,3819
official/utils/registry_test.py,sha256=1d88Kh5y0HFKTJAtdI4TYTJFMBM-z2V8hn1ybV_CIC8,2560
official/utils/flags/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/utils/flags/_base.py,sha256=HBggR95npz1B6pDl6ccRMI9SVsU1MsdHif-K4U_YFdA,6314
official/utils/flags/_benchmark.py,sha256=LmxyqA9NLClE4USWpy0fhjaA8e-iXJ9tCsu9QtPmvXY,4181
official/utils/flags/_conventions.py,sha256=1slsPwObKTMEAU8B7xQI4Hotyoln86ewGFW7FCxM03k,1834
official/utils/flags/_device.py,sha256=Iupn3YB9L3YMWExzw6S5DJUw2hCTYZINSW8sGz2nSH0,2988
official/utils/flags/_distribution.py,sha256=yE16gTxgIgsF2mLewOXFHtfHK9TcIG7t1q8vyyvtiIo,1868
official/utils/flags/_misc.py,sha256=yZsHpsyQjvkUw2zBSOOI1EE8OFAAvyKgzQ0Nx7Jswfc,1715
official/utils/flags/_performance.py,sha256=3JuniNg6Eww2zkhPVOuSuCQZSNrPkXXGtZFmWISxMew,12151
official/utils/flags/core.py,sha256=Xo2JA5Q7dF_dNjmgNjBrirbkfLIvyBDfZBkHVw2pfss,4616
official/utils/flags/flags_test.py,sha256=-kd7HwqoEYAAtoJbuOGbaMOiqsAc7IrqroGWR0bt19Q,5643
official/utils/misc/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/utils/misc/callstack_sampler.py,sha256=WdFYJ14HIV2JdALQXVIIn8Ks8c2Vw9jmK1e1Go5LkT8,1640
official/utils/misc/distribution_utils.py,sha256=7YInCQ8fDEGSPD8eFbdkJ-ba0V6j8QqLyb9TTAqvbVo,7432
official/utils/misc/distribution_utils_test.py,sha256=FIl_sG9as-5NFI3-BDRfHnwtfzC57zePV-KtZr6_gHk,1915
official/utils/misc/keras_utils.py,sha256=Njq4zrAnwKFfTfb0Ch1r1PoxsqVeiacMKF1IlmQdP9Y,6672
official/utils/misc/model_helpers.py,sha256=6fOQvUbDcEP4ZTAdLrtSAJmCRjEyVmOlhZQzxVfF60Y,3419
official/utils/misc/model_helpers_test.py,sha256=1ktB8PDzEcQ_2q1-pl4hWexV0wri5T11Mmntiids-r0,4837
official/utils/misc/tpu_lib.py,sha256=dJgRWqT2U2GWuU02InyvrTYHsxxt7mlsezzu_I6LQJk,1230
official/utils/testing/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/utils/testing/integration.py,sha256=CfhQiuAIR4PTnGYl-EoFWdjO3VjiM6MCjgq1NF8884o,2339
official/vision/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/vision/detection/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/vision/detection/main.py,sha256=KbUmgvPnW4qnxP4wnnO3KI7pPDUQCJA7dVO6JAF83Ns,9024
official/vision/detection/configs/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/detection/configs/base_config.py,sha256=UvM4Y1m3zXitAQRgpIbvETFkkc_jEgKhLK2be7xSJMM,4465
official/vision/detection/configs/factory.py,sha256=Lf1SwR7puuAVop0fez7ZMLUBI-Npg7eEQLHlGWlRUwo,1581
official/vision/detection/configs/maskrcnn_config.py,sha256=nsn8R9IXk4oGThJWSHJKNSMpFKOGurc8-YliMOsJ_tk,3443
official/vision/detection/configs/retinanet_config.py,sha256=KwQVkllhEDRi6RNt4UHyTbfnrRAP0ZwrYFRgWqk8Zo0,1891
official/vision/detection/configs/shapemask_config.py,sha256=gNbOyuQ7jzap2AT_QT83bew3LUS2Sk5XKahMZMxkpWo,3295
official/vision/detection/dataloader/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/detection/dataloader/anchor.py,sha256=y7uwFXkhh4LRY-qhr1WfWjD2kCOZacEjNmed8pZbwhc,12763
official/vision/detection/dataloader/factory.py,sha256=_gGVxxSs6jL44DPpn8tcxuuqXbRYvzCaRhv-owZShpQ,4932
official/vision/detection/dataloader/input_reader.py,sha256=TQGY9iZIh9Z7myikwr3TbeZTz-Bsia_oLg52zZOSke8,3776
official/vision/detection/dataloader/maskrcnn_parser.py,sha256=ABXc508EGfOapSNscXOMyLqoy2sBApgve19hQzIeQNg,15827
official/vision/detection/dataloader/mode_keys.py,sha256=Lu-U0NEEBBWISDmdD_vA0urJGLgpbuIb9C3xx9hK504,1141
official/vision/detection/dataloader/retinanet_parser.py,sha256=SnNwMkuCmnCbzQBANv35776yJqb6D3CVpSjlrTmZv3Q,17737
official/vision/detection/dataloader/shapemask_parser.py,sha256=T7D3QCh3jha3JwMGAD3gP9QRWdwEipoFU9DLsOFSPT8,22412
official/vision/detection/dataloader/tf_example_decoder.py,sha256=RNoCeGKin-lVW9_gdjIWSjpcVzU7EJwayK4BhdtweqE,6299
official/vision/detection/evaluation/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/detection/evaluation/coco_evaluator.py,sha256=T_OA2qxUJvJ1iB5ysXgq_Vcqn9UhOeLOsTw2hkG1SYM,13435
official/vision/detection/evaluation/coco_utils.py,sha256=fVXPuJ6k1HqhdokmqHXDv7alndPCqusoNqNH5RrvXgg,15250
official/vision/detection/evaluation/factory.py,sha256=HX1az15aFYFoN4o4yLXAmtIRVYxSfGUQhjtraVY2TYU,1607
official/vision/detection/executor/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/detection/executor/detection_executor.py,sha256=L1cokt4HTJKKUC6nFWlpPwT55WCTEZVzp35ORqVoWZY,6358
official/vision/detection/modeling/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/detection/modeling/base_model.py,sha256=Bfet0JgY5ndrQM5Rg8QKX4dFx_FnizxsiZql6qPAGhc,4638
official/vision/detection/modeling/checkpoint_utils.py,sha256=Nvyhz_oFz1JAEV-baTnX4CkowT0eQSYKHCX75uhu7vk,4669
official/vision/detection/modeling/factory.py,sha256=26VT_ZI2tRZT7BVBb9dVaD5aJCjudIhoBloDtK-1v_c,1338
official/vision/detection/modeling/learning_rates.py,sha256=YI-Rs2MXgsPW138Gky9x9ReKdJWTIuF0dJvMvoLHpQ4,3889
official/vision/detection/modeling/losses.py,sha256=v7ZD0tOHfvYA3SZSAKs0t22y1U1FQVSzakhEUzUtFG4,23115
official/vision/detection/modeling/maskrcnn_model.py,sha256=9yZ-it802Uz7sTm9hWw4hPs2BmX2Dk8Bv29oLhkzNzw,13676
official/vision/detection/modeling/optimizers.py,sha256=DeKD33Xk8Yfkt9TI_VGSm4LorrF8LwRUBG8gu5FWDV4,1815
official/vision/detection/modeling/retinanet_model.py,sha256=l6YVcAw3g8ENu4UH2J4BH0KlT8UvWsz3d3fR5drp_os,6912
official/vision/detection/modeling/shapemask_model.py,sha256=CD8eCO7Q1X7f6oTT-XraUh4Q3ja2wJuQactNRaqd-6Y,12459
official/vision/detection/modeling/architecture/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/detection/modeling/architecture/factory.py,sha256=uwwHQXukluE1ydgouBQx3vzgNZBEuVdIsndXwoq-uu0,6040
official/vision/detection/modeling/architecture/fpn.py,sha256=XCbR02KWNdIGklNcLBKTYUeF-BidRd8BCQezqpFhMm8,6091
official/vision/detection/modeling/architecture/heads.py,sha256=Qr455gU3d74x264r0Z5HVi0Oph5aC_0uwferWYOTL10,40376
official/vision/detection/modeling/architecture/identity.py,sha256=8tuWcNWuTxXJG5Cw1TKjlBfSAdicvwN5WZE4JwwKt58,1054
official/vision/detection/modeling/architecture/nn_ops.py,sha256=a4mIc4UpPLMP2HI3e2Kr8TBOn68bEiw9ytHElouoGzM,3933
official/vision/detection/modeling/architecture/resnet.py,sha256=rLC6m2bghcnyDo9bqEY0zWvGCnX3tQJbrzszbFgrrc4,12901
official/vision/detection/ops/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/detection/ops/nms.py,sha256=Yvq-8pUOvxTmQ3qsSRXhmYUYKkYPuOQmAFbt-KMCMZw,8288
official/vision/detection/ops/postprocess_ops.py,sha256=_C26VDIW9Uare_zJd1B4W784jLK1Dd5LrlOnS-AEu4Y,17973
official/vision/detection/ops/roi_ops.py,sha256=OzIQcvZjy5nJRrC6vjaT3jHP-BHOKHLVGoz3-DC50iM,11133
official/vision/detection/ops/spatial_transform_ops.py,sha256=fMgkiwLfat8J2-txin4g3Snq2_wc-XcPm0fkUf1YCgY,26068
official/vision/detection/ops/target_ops.py,sha256=KWEacqZBZtbb2Hbx3xyN7ZC2X1WUBcIgNDZVY4hUU8Q,18912
official/vision/detection/utils/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/detection/utils/box_utils.py,sha256=QxwUBX4vIOM5EuHX-embNwznZMDomyph4LA12EbfdV0,20533
official/vision/detection/utils/class_utils.py,sha256=IuPkYzvlO9cMCQzfOO6WpKiKChwpEcLZPKEk-tswEYA,1545
official/vision/detection/utils/dataloader_utils.py,sha256=Z23gGQzFbb8aNzHjD5RGmUsU6H6OXp3lDWFPxLrqe6M,1655
official/vision/detection/utils/input_utils.py,sha256=2fXhsqyejorKkGYMMSEPf2N4xPm-6m-rxXWRFpI7uy4,14545
official/vision/detection/utils/mask_utils.py,sha256=OcNBMBiLI1yLH3Tl5zTub-bBIiZZLjeHAKVXGm2t0qg,6976
official/vision/detection/utils/object_detection/__init__.py,sha256=TQ3vWdbSZYHcAHvtYAluI94_iUOxBqEgnCDJptqCNvI,689
official/vision/detection/utils/object_detection/argmax_matcher.py,sha256=pr_pZ-N8oSQ_b71P8nzZiqo3Yp7XKq4OAElEWszXC9w,9111
official/vision/detection/utils/object_detection/balanced_positive_negative_sampler.py,sha256=_lwx3epqZhXNoePHq7H4X6-44U69M-v5YF-mxIMc7kQ,12159
official/vision/detection/utils/object_detection/box_coder.py,sha256=OksVPe9Hbi4tzo0zJCA6fvrbfLxMTLbtSPrXgiUGBQ0,4910
official/vision/detection/utils/object_detection/box_list.py,sha256=MBv9UoJWwco7ux5ThjarQmCprrUpOq8lRQdGQIUnE6Q,6820
official/vision/detection/utils/object_detection/box_list_ops.py,sha256=UGemeui-4HuT7-N8v5sRMO697Eeycr17iAfiaX_I0hI,41746
official/vision/detection/utils/object_detection/faster_rcnn_box_coder.py,sha256=frnuc3PHnWqdkQXlMgdNpsamFN8PR_8sd18ibSXLuGM,3907
official/vision/detection/utils/object_detection/matcher.py,sha256=4lCBDQ-fTIsVq82FfUgaAk5SrVJYsYmGXLuRXe79TIc,8884
official/vision/detection/utils/object_detection/minibatch_sampler.py,sha256=v1nUyklcduHKOd9r4X4of94CN9mQ9l2cV5CLopuMBT8,3167
official/vision/detection/utils/object_detection/ops.py,sha256=-ikPKwRYswigx70D2AdjIN-GIe_DI-AT06qTMEC0dVk,3305
official/vision/detection/utils/object_detection/preprocessor.py,sha256=J0BV7Ji7iM_WXahMTx6Qoj5XnNgRbPyFhGHtuySDFS8,20492
official/vision/detection/utils/object_detection/region_similarity_calculator.py,sha256=ueVQ0af7Ujbf6jNPs3X0vYmyjosaxJOIah4ue5o_SIc,4625
official/vision/detection/utils/object_detection/shape_utils.py,sha256=n2gb4llBJ3_cqXeWY58gjSHUYdvZ0dC64M68VGSQPMQ,3723
official/vision/detection/utils/object_detection/target_assigner.py,sha256=8sLzFeyg0WarcLqq_XxoCzBA2GAAh1jIcnsyKrlRwJQ,14118
official/vision/detection/utils/object_detection/visualization_utils.py,sha256=c1ZvNnFFgzBXx5tuRGQG_HT7j8FUnnqhg7tJgybAetI,29252
official/vision/image_classification/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/vision/image_classification/augment.py,sha256=FeiyCfo7nmE4JGO6CyhhHafoFu5b03-8Z45WtOHDJ88,34790
official/vision/image_classification/augment_test.py,sha256=7NYU8PnwoAKBxRfofu4RpbfTLd2hGFmBmFmft6TUep0,4736
official/vision/image_classification/callbacks.py,sha256=Zi3NzpxLuB0j8uRADmONO4IBOgRNcFN-Ske77w7z0nI,9124
official/vision/image_classification/classifier_trainer.py,sha256=j3OKRLlorOzbRo_j3tTkJZkdafJ42rBZdnxGUct1YxI,16170
official/vision/image_classification/classifier_trainer_test.py,sha256=lGCFR-P25Kl3tkILoeuB1aE-kee3mEqIcbHbQpl_GtA,13218
official/vision/image_classification/dataset_factory.py,sha256=ea4prj0Zq3k3mbM_-yQihxwycmB9xxR46MdR7FXAY3M,18760
official/vision/image_classification/learning_rate.py,sha256=YrDBmJzOwaLacbj3dxIu_ld0yKh_cXSzdKUFggRwVuA,4495
official/vision/image_classification/learning_rate_test.py,sha256=JpaUT9yQvgML29KqSzhaPcua3DDIrUpLB4U6LTOwuS0,2976
official/vision/image_classification/mnist_main.py,sha256=gaggMUdA5AONTng7eyoBaDEu1dOGAsgSD9zIDF6aiXQ,5985
official/vision/image_classification/mnist_test.py,sha256=SC-G3WxmSRq5YV49IreMyNIMSnBeb_0eABOyG0iigow,2691
official/vision/image_classification/optimizer_factory.py,sha256=z-2kijH-wNwmASSnhqilY9n2IocpddKFPhBSYyxLR5A,14450
official/vision/image_classification/optimizer_factory_test.py,sha256=JzJ4nsBoUXlZy0XpMNrvwlv58kR0773XneeLm_Gfd34,3916
official/vision/image_classification/preprocessing.py,sha256=NtThNKO9nMFMB0kUa6pQuQtBkkoffdwjxmQKsmcAzww,13601
official/vision/image_classification/test_utils.py,sha256=h4nsjQXNwFqrgHtPVJ0OwrHMpGVujlkLDKsaMhGX2Lc,1452
official/vision/image_classification/configs/__init__.py,sha256=nxhM3rvGukp5ZXNRrf2sIpdE6z0_03tR8ds56y_SVgs,689
official/vision/image_classification/configs/base_configs.py,sha256=G1LWIcV7FTKLH6t6i_3RP5bazJft0b0JB7khoP9MShI,7937
official/vision/image_classification/configs/configs.py,sha256=u3vf3FkEFNOG3keloeFnNNA-c4unx4X01XqU7aNNcGc,5185
official/vision/image_classification/efficientnet/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/vision/image_classification/efficientnet/common_modules.py,sha256=fP3_zeFcydY2Czue3rsPN5N79cN_FXFBtgbXaOMA6vE,4682
official/vision/image_classification/efficientnet/efficientnet_config.py,sha256=8izxwSWl4oP65BTbSrNdNU1Iv3aXOTjvuCqRwmvV3uQ,3001
official/vision/image_classification/efficientnet/efficientnet_model.py,sha256=SCUwHVc5kXdKxVw4mwQlsNXJLduZcNRtMxdKpahelh4,17397
official/vision/image_classification/efficientnet/tfhub_export.py,sha256=gYfnH9j9us12WBT8jvah8IVwJoIuIbm8dlCk1dmsgok,2485
official/vision/image_classification/resnet/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
official/vision/image_classification/resnet/common.py,sha256=rPFFTDBVlQlm64CIKbAZeNiFaOseJyv_uSp3LbFyiyM,16397
official/vision/image_classification/resnet/imagenet_preprocessing.py,sha256=HsUEB-bfD0cStOswN8LwpIOvWYc8sutUjiPA8eyQuj4,21268
official/vision/image_classification/resnet/resnet_config.py,sha256=x8uDHokVoK6iiyzMFTxX9u9wUqfgXtTANjZfWBqMMOE,2395
official/vision/image_classification/resnet/resnet_ctl_imagenet_main.py,sha256=m1ghYbUsGwLp0IbKzHYaf4rkyds9AFAqoIHzNrfoZV8,7085
official/vision/image_classification/resnet/resnet_model.py,sha256=EFwXnOmQbWQmWMiWlrEe1VdvXdaHA_XzGlFfseDWE5k,11118
official/vision/image_classification/resnet/resnet_runnable.py,sha256=5xU2oCDtvYB27GoJH3WObSh7L8i3LD7-GT10pynpc2g,8572
official/vision/image_classification/resnet/tfhub_export.py,sha256=AiuXObXvY_egG0WP4UIE2ljIxhGN_MpYgfKVW43r0cU,2299
tf_models_nightly-2.2.0.dev20200603.dist-info/METADATA,sha256=NTIncGUa48UJ3Cd58CQweg-7R-KrhGJxZ8bKWI4Hz44,1374
tf_models_nightly-2.2.0.dev20200603.dist-info/RECORD,,
tf_models_nightly-2.2.0.dev20200603.dist-info/WHEEL,sha256=gduuPyBvFJQSQ0zdyxF7k0zynDXbIbvg5ZBHoXum5uk,110
tf_models_nightly-2.2.0.dev20200603.dist-info/dependency_links.txt,sha256=Qc7dWtXawN_GaX4Hlfk41c-qiIHlXtDONeVJTjTiyi8,82
tf_models_nightly-2.2.0.dev20200603.dist-info/top_level.txt,sha256=nQPMwYzZlWnm95mJ5TIaHyvyPVR_zEfEsUi0JeF8CuE,9
