5つのh5ファイルの重みが正しく更新されているかどうかを調べたく、
h5ファイルの中身を見たい！
【Python】kerasで保存したweightsをh5pyを使って取得する
を参考に、.keys(),.get(~)を見て試行錯誤した。
import h5py
for i in range(5):
print("------{}------".format(i+1))
file = h5py.File("./result_path/episode_{}0000.h5".format(i+1)) # ファイルの読み込み
model_weights = file["model_weights"]
layers = list(model_weights.keys())
# for layer in layers:
# print(model_weights[layer].keys())
layers = ["dense","hidden_1","hidden_2","hidden_3","log_var","mu"]
# print(model_weights["dense"].get("dense").get("bias:0")[()])
# print(model_weights["hidden_1"].get("hidden_1").get("bias:0")[()])
# print(model_weights["hidden_2"].get("hidden_2").get("bias:0")[()])
# print(model_weights["hidden_3"].get("hidden_3").get("bias:0")[()])
# print(model_weights["log_var"].get("log_var").get("bias:0")[()])
# print(model_weights["mu"].get("mu").get("bias:0")[()])
for layer in layers:
print(layer)
print(model_weights[layer].get(layer).get("bias:0")[()])
pc$ python3 weight.py
------1------
weight.py:5: H5pyDeprecationWarning: The default file mode will change to 'r' (
ead-only) in h5py 3.0. To suppress this warning, pass the mode you need to h5py
File(), or set the global default h5.get_config().default_file_mode, or set the
environment variable H5PY_DEFAULT_READONLY=1. Available modes are: 'r', 'r+', '
', 'w-'/'x', 'a'. See the docs for details.
file = h5py.File("./result/walker2d/20210122_143959_epi/episode_{}0000.h5".fo
mat(i+1))
dense
[-0.2993213 -0.32194233 0.11839359 -0.09928301 -0.31124848 -0.3751496
-0.3678569 0.1899587 -0.08569791 -0.01822463 0.02833614 0.01277389
-0.02882302 -0.06589823 0.03802811 -0.031959 -0.05847006 -0.0986212
-0.33697262 -0.05775459 -0.10717085 -0.34125197]
hidden_1
[ 0.01285853 -0.01230553 -0.00388967 -0.02433562 0.00179267 -0.01015067
0.01279763 0.00089996 0.00513106 -0.01144475 0.00831929 0.0088335
0.00711508 0.00678137 0.01632852 0.00094608]
hidden_2
[-0.01643273 0.01181548 0.01352771 -0.001769 -0.01567042 -0.01673872
0.001208 0.0133812 -0.00511519 -0.00952019 -0.02292812 0.01551038
-0.0003822 0.02179182 0.00771308 -0.01250312]
hidden_3
[ 0.00147426 0.01081525 -0.00514209 -0.03740762 -0.01695448 -0.02615813
-0.01724532 -0.01179097 -0.0363163 -0.01086682 0.0169599 -0.00024146
-0.01046261 -0.02178889 0.02703306 -0.00139732 -0.00190802 0.01164212
0.00064688 0.00502167 -0.00390945 -0.03841734 0.00580032 -0.02683658
0.01183896 -0.00594397 -0.03564184 -0.00268949 0.02109798 -0.00184922
0.01308736 0.0183714 -0.01773291 0.00852762 -0.02282826 0.00185806
-0.0178623 -0.02092414 -0.00946022 -0.012106 -0.0302344 -0.02267631
-0.02971576 -0.02076597 -0.01282861 -0.01714998 -0.00485182 -0.02255891
-0.00863784 0.00695363 0.02177046 -0.02126798 -0.02255806 0.02550721
0.00818296 0.00872978 -0.01019798 -0.0029075 -0.00304889 0.01568063]
log_var
[-0.26622045 -0.44091797 -0.2419649 -0.50653774 -0.36543489 -0.18883663]
mu
[ 0.05976096 0.03247268 0.00452811 -0.0034478 -0.03532023 0.04368779]
------2------
dense
[-0.42575213 -0.4498407 0.16496097 -0.25781444 -0.39711034 -0.45612583
-0.49852094 0.2791475 -0.04682539 0.0053675 0.10432086 -0.05520683
-0.09059926 0.07662117 -0.06888733 -0.04932804 -0.05911314 -0.21280894
-0.45909563 -0.18084827 -0.11217871 -0.42897993]
hidden_1
[ 0.0169547 0.00135951 -0.00641266 -0.01012402 0.00021668 -0.00809189
0.00516283 -0.00121518 0.01503234 -0.0133448 0.02960026 0.00107891
-0.00836505 0.01001229 0.00759052 0.00075823]
hidden_2
[-0.03121149 0.01105501 0.00353613 0.00630521 -0.03281696 -0.03234349
0.00590976 0.01714135 -0.03656695 0.01059771 -0.01879915 0.0182774
-0.01051105 0.01707695 -0.00700341 0.00888611]
hidden_3
[-0.00174479 -0.00838945 -0.03810974 -0.01638342 0.00310101 0.00047198
-0.01974851 -0.02552811 0.00858791 -0.00421809 0.00086814 -0.00352836
-0.00398448 -0.0075184 0.03037225 -0.00200673 -0.00742958 -0.00661159
-0.01234769 0.01912175 0.00099004 0.00580208 -0.01445077 -0.01215665
0.01352465 -0.00839235 -0.01136181 -0.0150891 0.00322541 0.00430215
0.00805547 0.01957959 -0.00584291 0.01372828 -0.01055162 -0.00989193
-0.03023658 -0.03651182 -0.00137293 -0.00502513 -0.00477335 -0.03991703
-0.00154987 0.00352569 -0.01544962 -0.01001886 -0.00758626 -0.04234054
0.01167532 0.02955389 0.02831114 0.0034275 -0.01159023 0.01606458
0.00734266 -0.00485118 -0.01415251 0.01226815 -0.006758 0.02537185]
log_var
[-0.2284169 -0.3882995 -0.23325028 -0.48085243 -0.29607776 -0.05214483]
mu
[ 0.09707549 -0.02336518 0.03843829 -0.0059326 -0.06028875 0.16774386]
------3------
dense
[-0.3609201 -0.4038263 0.18953307 -0.3221238 -0.34733847 -0.39199328
-0.50452036 0.3464602 -0.07979373 0.09677191 0.06821929 -0.02858738
-0.08285121 -0.02647901 -0.06329241 -0.0464786 -0.05543575 -0.27278653
-0.43914935 -0.15375452 -0.09366758 -0.39211708]
hidden_1
[ 0.01637724 -0.00586867 -0.00091257 -0.0220271 0.00989103 -0.00159342
0.01516735 0.01175526 0.01859576 -0.01689171 -0.01568438 -0.00529172
0.00313585 0.0109848 0.01243033 -0.00219891]
hidden_2
[-0.01441067 0.03176265 -0.00455891 0.01592212 0.00100191 -0.00104676
0.00113423 0.01372305 -0.02879625 0.01738748 0.00476962 0.01931044
-0.01249406 0.004782 -0.00502662 0.00121921]
hidden_3
[ 0.02300977 -0.01313633 0.00602289 0.00586655 -0.01930383 -0.00678339
-0.01294483 -0.00265931 -0.01821144 -0.00046318 0.0075395 -0.00424121
-0.00837085 -0.01992738 0.0501219 0.02281669 0.00978312 0.00380054
-0.02079066 -0.01900988 -0.00998911 -0.02499146 -0.01035645 -0.01753384
-0.00778861 -0.00391977 -0.01730437 -0.0149233 0.02815877 0.01600625
0.01011903 0.01202185 0.0095513 -0.01818707 -0.01557177 -0.0093669
-0.05587415 -0.01565717 -0.00363236 -0.00386564 -0.01481221 -0.02848075
-0.00265851 -0.01358179 0.00700456 -0.0005413 -0.00315622 -0.02419036
-0.00215404 0.00882866 0.02737095 0.00691985 0.00981182 -0.00604119
0.02055109 -0.00220829 -0.00786867 0.00056195 -0.00128857 0.05296057]
log_var
[-0.18568064 -0.42112157 -0.10640209 -0.4720275 -0.3076731 -0.05898004]
mu
[ 0.12181789 -0.07251222 0.10192874 -0.02079329 0.00843742 0.11063012]
------4------
dense
[-0.45512405 -0.4792948 0.19997866 -0.4356516 -0.43723622 -0.44441482
-0.6207231 0.390794 -0.20586368 0.24317113 0.08350939 -0.01324948
-0.23957846 -0.10354955 -0.11590306 -0.1011933 -0.03096447 -0.33722648
-0.52121156 0.02860512 -0.06179736 -0.4931039 ]
hidden_1
[ 0.0098588 -0.00885933 -0.01049567 -0.02240602 0.01429007 -0.00334164
0.02016274 0.01544681 0.01102758 0.02213593 0.00463183 0.00502532
-0.00267633 -0.01370771 0.01710366 -0.02348411]
hidden_2
[-0.01441815 0.00403282 -0.02799178 0.00785748 -0.00535665 -0.03183194
-0.01195905 -0.00031165 -0.04085694 -0.02425708 -0.00241232 0.04176614
-0.02035664 0.03019036 0.0062063 0.05299307]
hidden_3
[-0.05234769 0.00370329 -0.09656766 -0.05031026 -0.02526811 0.02819046
0.04432523 -0.07284088 -0.04559707 0.03193165 0.00657521 0.03995736
0.02470329 -0.03026467 0.02126475 -0.05329533 -0.04604874 -0.01832408
0.02986939 0.03204302 0.02071415 0.02890907 0.01348515 -0.01197762
0.035567 -0.00641954 -0.01039144 -0.0226956 -0.02152967 -0.01170264
0.05216637 0.06210339 -0.02049457 -0.03548224 -0.11461961 0.03478845
-0.03264535 -0.05490202 0.02964461 -0.01698051 -0.04792651 -0.06926097
0.00341674 -0.00304062 -0.01643956 -0.09868644 -0.04623813 -0.12408376
0.0737886 0.02389593 0.03864462 0.00275503 0.02826896 0.02527355
0.00502198 0.00127364 -0.04877707 0.07355893 0.00095519 0.01632655]
log_var
[-0.2149527 -0.43429127 -0.12096979 -0.4642315 -0.24396077 -0.19962847]
mu
[ 0.11146773 -0.04464803 0.08049753 0.05853469 -0.05219817 0.20106995]
------5------
dense
[-0.514686 -0.51815444 0.16813129 -0.4805155 -0.51214296 -0.48490146
-0.69934314 0.40153962 -0.16017234 0.21786498 0.07586032 0.06848594
-0.2371331 -0.15719014 -0.163361 -0.02760048 -0.07600322 -0.37585324
-0.5784061 0.00175215 -0.08469447 -0.5798797 ]
hidden_1
[ 0.01126834 -0.01231832 -0.00937062 -0.02195915 0.01400331 -0.03649899
0.01753567 0.01351106 0.00537443 -0.02163706 0.02746029 0.00847202
-0.00236308 -0.00263122 0.0118852 -0.00533856]
hidden_2
[-0.03975146 0.02691265 0.00718811 0.01240622 -0.02857937 0.03555348
-0.00756482 -0.00221284 -0.03636038 -0.02479281 -0.01452929 0.03175795
-0.01004493 0.03761677 0.01006705 -0.00341219]
hidden_3
[-0.02854635 0.01539811 -0.06664139 -0.04924892 -0.03209276 -0.01373351
-0.02575772 -0.06562782 -0.04508246 0.01164096 0.03203472 0.00851271
-0.01285799 -0.038576 0.03442601 -0.03492095 -0.00730774 -0.02902594
0.01413057 0.01179908 0.03825828 -0.0167208 -0.02566672 -0.01650032
0.00543993 0.02678551 -0.02480492 -0.02948821 0.01369712 -0.00691305
0.02009066 0.01754091 -0.03031769 0.01738846 -0.0574885 0.04089386
-0.02611405 -0.065906 0.00831986 -0.03634514 -0.00802476 -0.09968716
-0.02643104 0.00783725 -0.04775301 -0.0802675 -0.02175665 -0.10979362
0.02718254 0.01011948 0.03617569 0.0068545 0.00662172 0.05393337
0.03099504 0.0210703 -0.01106016 0.0718689 -0.01067457 0.0026848 ]
log_var
[-0.21639466 -0.42551097 -0.11998599 -0.4593208 -0.26696658 -0.23223357]
mu
[ 0.11872804 -0.04876811 0.09173425 0.09657543 -0.0226907 0.21999218]