vicentin/__init__.py,sha256=Qcbi58npZ6iyA4PNSahPHNhHpkqWJ7OWWa8yiDGEwlU,197
vicentin/data_structures/__init__.py,sha256=mSBKPJMCiFiZQvD-V8iS9daoMr-QFNej66ABDIN31fA,234
vicentin/data_structures/graph.py,sha256=SXm_U0h2rXcgfhbHyUWqwOb32GkKD8I83BmBgZHvasg,13443
vicentin/data_structures/heap.py,sha256=c_SI29JPVn_Zocr4uALTDL1y_xVuwMgx123d2g9t_dI,11420
vicentin/data_structures/priority_queue.py,sha256=8L0L87nU02avr83Hb8TZPm7JYtzTuFo1fTjnkdSypuc,8369
vicentin/data_structures/queue.py,sha256=tF4lWPsO5czWvicM9IOQm996OJs14wBHZFGmQp3Osyg,4989
vicentin/data_structures/stack.py,sha256=mid4Fh2pS4SihDooQZG4YI1M5lQTYaWQc2clgxSO5h0,5027
vicentin/data_structures/tree.py,sha256=BycjU9oBX477K-LdcHs3hLI3fhwB6Z5ekr49WTwebdw,23691
vicentin/data_structures/trie.py,sha256=1rjpr9M275YFFtKSobZC8izySI0vJWmvA_BNM9LBq4I,4055
vicentin/data_structures/union_find.py,sha256=js2mEUNPqzRfaKQE0Ppj6bxzGWbPd8UNhrj7O1kFzAo,5528
vicentin/deep_learning/__init__.py,sha256=n6-zgfU1qTdgpBYEvo9NsYb_V1qhZRq1i_0nyB8LAog,29
vicentin/deep_learning/utils.py,sha256=2YBlk6F2itfYFeeGLE_0QmKrQDGxrTi8UDr9lo3eFhg,8123
vicentin/deep_learning/blocks/__init__.py,sha256=3EGIcJTosuBDdmV_0iZvbIEhsdkTRpW_Pm1lRc4p8M8,109
vicentin/deep_learning/blocks/cnn.py,sha256=jCJMRVf5BXuVVpXiLe9CqoEKO7YpfgnyYLLJQcGUye4,7030
vicentin/deep_learning/blocks/mlp.py,sha256=YQSZoszwj84uAq3QeIc6HXg_ZnxHAQ06klYNjKioF4s,3549
vicentin/deep_learning/blocks/smart_flatten.py,sha256=Ma312m7bkarcKKgQl_f_EkbRA_3hCaGFVb6p84Ve4UY,1119
vicentin/deep_learning/loss/BaseLoss.py,sha256=_tLmx7P37UCMK6WFg51eULsxtV2cl6MW-Wy1k3VV0M8,259
vicentin/deep_learning/loss/GaussianKLDivergenceLoss.py,sha256=nXU2IXO-xRKYO1grjd-FUDRYWLbkeKeLtJ8GRkZUbrE,1541
vicentin/deep_learning/loss/SupInfoNCE.py,sha256=BWjwk0kKald1T8NErYlLBYoXBVBDEIvt2yMwwfn-x5Y,1738
vicentin/deep_learning/loss/VAELoss.py,sha256=5CgDtGaKQQIp8pgtUcvkRp7eG5Olm6NGZ7ud2C7ZkL0,1392
vicentin/deep_learning/loss/WassersteinGANLoss.py,sha256=9vcEZl9DtYpCZtXEdLdVScQYuw4Y9TlZPa2YZDrivZk,1930
vicentin/deep_learning/loss/WeightedSumLoss.py,sha256=AtxSXGpGdbdNewsirOLuzEflSTIxKH-DJmwLfXS0C8c,1896
vicentin/deep_learning/loss/WrapTorchLoss.py,sha256=rHqYu7g9Er7EkVg-UzIX6xVaYPqba0kVesllRrvbX0c,323
vicentin/deep_learning/loss/__init__.py,sha256=oAUXQQopq-YDKN6eo02M-VG3J7gsh7722SVXAuO_3ak,351
vicentin/deep_learning/models/__init__.py,sha256=Z5iPejLmZFyTDAENNkKzikaDJl_hqvOAiV82wrf-mQM,104
vicentin/deep_learning/models/ae.py,sha256=W1W99WBAuFwzzRFzCNCuJZusEc28OcQSJe0oHoS_TqY,997
vicentin/deep_learning/models/siamese.py,sha256=147gMh-L6qZGlbv0Nwcu0TlAhIPP16D02Rdz4z8kj1o,4825
vicentin/deep_learning/models/vae.py,sha256=pcZGBWOIXQkF0L8lQqF0SmAkn_Tp2EAhBnSTrAl3Aec,3089
vicentin/deep_learning/train/DistillationTrainer.py,sha256=L41WGTx2wVrQpAbwBY4HvwGoTmg_Hsdfa7_hPqkT8kE,761
vicentin/deep_learning/train/GANTrainer.py,sha256=notGAU6nylQS1ziTuSF5nvaXlLBRom-g8rpA5yNEUtk,4028
vicentin/deep_learning/train/GenericTrainer.py,sha256=iZkaoBrdLrqauMmtMd71S9gIzOQvwuHFNjApNZXup4A,9662
vicentin/deep_learning/train/StandardTrainer.py,sha256=if35BKyDTUUzoX6eqNe5Cf9MBW_hh7trjdi_kv0ohIo,1122
vicentin/deep_learning/train/SupervisedTrainer.py,sha256=YI-DPQRdCHzqM7gMpMhv85EDVa8hudbAcFGid80C61g,1260
vicentin/deep_learning/train/VAETrainer.py,sha256=ykNsDt3x0yWgiuUNcyhLSttwPdUg-Y8y77ZUUxDSkpA,3113
vicentin/deep_learning/train/__init__.py,sha256=Uh8v7odQ1Njb5iCEEavpqvLuY-7egAPPV_FsWHUxOXs,261
vicentin/dp/__init__.py,sha256=FHEi6gOr6sWO8nrbP7rmnA-DmbE5lgaBxw9u1y2gnCk,54
vicentin/dp/knapsack.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
vicentin/dp/matrix_multiplication.py,sha256=I7E0U0KuxXDD4peZO9FgkVoSQ5VvzopZYD3xYFDk1vU,482
vicentin/dp/rod_cut.py,sha256=TP9oYQuAcZhTTdROOQB2raqll4mdOO4nRiva3Bb_OFU,409
vicentin/dp/str/__init__.py,sha256=mkH5J3yy61A11Li7EeWzGMqqgdtHgzvYPyJntSQDaE8,41
vicentin/dp/str/edit_distance.py,sha256=yAgvYy1kQkuKQ_JTXIOENqGm_hijB5PkLJ3Lt83fLmI,553
vicentin/graph/mst.py,sha256=FfRSJr0hRCJ9LTZCJN1eBS_drR62oATCOUEtLqizcLg,47
vicentin/graph/negative_cycle.py,sha256=x5wF0hPkOo5ivVsAuoRQV1AWS7r2N2DB0VqFCb_bSCI,2134
vicentin/graph/shortest_path.py,sha256=CiMSbpXI9zef_oM-VqB2DwfzhcEqS1I9xneFUnLlbag,5448
vicentin/image/__init__.py,sha256=YZVAoJfZpK_9ZeYXuo247Bb3geu89PsDoBU9d4DIY2M,99
vicentin/image/img2graph.py,sha256=agubv5BeKkKtJgZJg8afp24URCwzzeidI-46w3dTg3s,4154
vicentin/image/differentiation/__init__.py,sha256=HW84wJVNlrFDgH2cOdmPA6HVb_cXaBMFMemtwJgYkTE,55
vicentin/image/differentiation/diff.py,sha256=f9ZgLo_tIaop0xfw08hbEGbFAisUfZe40_X-RTRrb3A,4633
vicentin/image/differentiation/diff_np.py,sha256=VHTi3Aybrrjh5gjqQm0uOJmLbWGuz0NAzKIoD6O6Le0,4314
vicentin/image/differentiation/diff_torch.py,sha256=-_bZEh7Isv9HtFyFQd2yfXFHDx1ZxV_Vakr3QYVI7bg,4799
vicentin/image/regularization/__init__.py,sha256=n4Ud6knKaJGgrnYu05kB2XQstxxuemfWmV7iJhUfsnw,54
vicentin/image/regularization/regularization.py,sha256=vzQwoMJjGdRYHFpfBw0evkgKgQPrXgdF4Hp-BxzdvG0,1083
vicentin/image/regularization/regularization_np.py,sha256=SEersyxwhbL4XbeaMe5aD3VOhEBST3MDibOj73ec8W0,330
vicentin/image/regularization/regularization_torch.py,sha256=ARMxkYhc95G-OkbWt2MDUjiuRELXznJLDLYnhCTb5NY,333
vicentin/image/utils/__init__.py,sha256=PHw9PzFhZzG0ce7U1XgsxnyxP7CwL2i9SNtnVD9osdk,124
vicentin/image/utils/utils.py,sha256=j4xXH0WpyRdbTwpH5-XqiGO2KZzmwSeYJPxdxgNYRZg,16407
vicentin/image/utils/utils_np.py,sha256=MPH0OwjM8RNmNAl8RnVa5oI7LfEBYMFacoEnxJkLV-g,11830
vicentin/image/utils/utils_torch.py,sha256=9oiPyBo9P8vsBACmfhQIgIgM08gSK47ia0CgK1wVtFk,11687
vicentin/image/video/__init__.py,sha256=aGUkzD-0c0txZL-PorVpUxZLdriaS_PHLg6PewG5pds,27
vicentin/image/video/optical_flow/__init__.py,sha256=FXTdnqUVErFWTlZqR2UtY-uGYnLwJAtOE6fKV8zPt7o,39
vicentin/image/video/optical_flow/horn_schunck/__init__.py,sha256=FXTdnqUVErFWTlZqR2UtY-uGYnLwJAtOE6fKV8zPt7o,39
vicentin/image/video/optical_flow/horn_schunck/horn_schunck.py,sha256=kuBG9apOWv5HD8GjdEGKC0eIx32XaTckUzBVrKJKtX8,2776
vicentin/image/video/optical_flow/horn_schunck/horn_schunck_np.py,sha256=ckpYDo7x-IAfAMWVxzKXqJcQ_H18v5uwZyAHFpP5Sys,1504
vicentin/image/video/optical_flow/horn_schunck/horn_schunck_torch.py,sha256=diAgJupjTeKdkETmSF0VAX6su6ha5OuvBk5jHsaGZc0,1561
vicentin/kernels/__init__.py,sha256=HyEqqItI-NQzOsgF1Y5z1oI7npg5UnFDvtyla4t5xYU,275
vicentin/kernels/kernel.py,sha256=S_l9lFNTbp_m9i4Otd9wKPw0X2LZFwHv4ScgzGiNam4,4105
vicentin/kernels/kernel_np.py,sha256=cFyrR7emDpSoQJDoREOs9XNi6k-p-bawyZmuvMy1nT0,2710
vicentin/kernels/kernel_torch.py,sha256=CDr6WGD0DbrBl9svjzK8Y2SvKcudl1nRkc9eByxtoFw,1645
vicentin/kernels/linear_kernel.py,sha256=IUVFxVLV1JTT1-xav57JL2wdCM1oxvCRtcnKu7y_2gY,415
vicentin/kernels/phi_kernel.py,sha256=hTPvJphg3hZiWOryMFbQNPEW4aC_2sMm3zJ4SgFxoz4,524
vicentin/kernels/rbf_kernel.py,sha256=ROryQA62X8WATvfVQINwjPkLmVq46JXZlyCHXm9GY5k,1584
vicentin/kernels/rkhs_function.py,sha256=s4rS8ltD98a9WauVc7PkT4yFK__WAfJ0ztT0PzIFs2A,609
vicentin/machine_learning/__init__.py,sha256=_8S6aLGtd-15BqdYycbKJSl9HxA9tE85BdZUj-fNeaE,50
vicentin/machine_learning/predictor.py,sha256=cizPDrNWtjyVfTv_PN9k1dO9BrDvn6KNw6goDBQaqJE,352
vicentin/machine_learning/classification/__init__.py,sha256=u0EeNz7n0lFGZU5Uyt0jIKEXr2rS_9x-A0k-3BPvOmQ,29
vicentin/machine_learning/classification/SVM/__init__.py,sha256=Y0r7KW9CttvOr-hAZ265GxJeLNkIbhAxBg47aHnP5Rc,69
vicentin/machine_learning/classification/SVM/l2_svm.py,sha256=GN8MB7vi4nFBTxh6kVGgLBgCtenT3akNRStY6f-pj1c,1704
vicentin/machine_learning/classification/SVM/l2_svm_np.py,sha256=BqL3vZZgJkJpQzEBFuyTuIfsypkAM_-uHppXy6NvHy4,949
vicentin/machine_learning/classification/SVM/l2_svm_torch.py,sha256=XbDzJX2667sjEzKpeJ1v9lINzSEJpcB7ckcZZ9ECYnY,1090
vicentin/machine_learning/classification/SVM/smo.py,sha256=QcW_u7PEZtFIMSGLmu7gyJbS7kQTOOFhtmw0tGWgz_g,1576
vicentin/machine_learning/classification/SVM/smo_np.py,sha256=tZHap-Ub3rxTbacU87E96V3ilUt-EI3NEIfx5ZpvCeo,2476
vicentin/machine_learning/classification/SVM/smo_torch.py,sha256=SMo1QQ4iEsalmk9h9pE3jv2WzGj6EoP2VFGmoLuiWZw,3079
vicentin/machine_learning/classification/SVM/svm.py,sha256=NDpNOa7leqsorpeH8Ft7Aw9_EdD49Cqol2YJV7QXg-E,2850
vicentin/machine_learning/classification/SVM/svm_np.py,sha256=MTVfBTK64yg8Yk-fSpSecZP_f6xblT0QEy9WNCDc7Pg,1221
vicentin/machine_learning/classification/SVM/svm_torch.py,sha256=FdDnrtDFZQpXLkqTuYiTRw9xqZct3LVUN9ey6Sp-6qw,1332
vicentin/machine_learning/regression/__init__.py,sha256=SnNyIdfIzZeL-SwT3mAvCX9Oh5EcZiLcD0ABMXbeVnc,47
vicentin/machine_learning/regression/logistic_regression.py,sha256=N1a-qMymxOAoav14jeV21gd5HBbGiexzBYRktq1qrig,1641
vicentin/machine_learning/regression/ridge_regression.py,sha256=ImA041toAjvj1eT-Kp4WzJt5vDCz9pIfuu8MIS5xhtI,4835
vicentin/misc/__init__.py,sha256=0vEDjl7pPGvmyR6y_gk-EoTYstI31XwJQVAZWvgGOKQ,76
vicentin/misc/polynomial.py,sha256=8KTvYtMKj-xRHQSdW1PzTPwPGYoEFkOz40gvwOAfR5k,982
vicentin/misc/subsequence.py,sha256=_tyNtn0dmcV-Quvtb6o4Y-Yya_-LjmKZAlf43FClOco,1769
vicentin/optimization/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
vicentin/optimization/minimization/__init__.py,sha256=F7jKyGWeEI2R6WZGqHvvFG5YpEc9E7LWEQKKZuImeKk,408
vicentin/optimization/minimization/barrier_method/__init__.py,sha256=JsIFNdN1NQi6YhUQyKXO53BtcSo1SCcX4TcBCZ8EBYw,36
vicentin/optimization/minimization/barrier_method/barrier.py,sha256=t2cDfjUwr8qxzsi69IJJeT-6QOFEvhGUJgbeBZegTz4,6323
vicentin/optimization/minimization/barrier_method/barrier_np.py,sha256=wTtDJGdLdrcv3V3GFoGUnvxgfinwcEd3Xk-vU-d8X0w,4212
vicentin/optimization/minimization/barrier_method/barrier_torch.py,sha256=KcItYS39TbY-8TxoFy-qtJnmqERFVE-WNQnsD4QV_ec,3133
vicentin/optimization/minimization/conjugate_gradient/__init__.py,sha256=2MkE42SZ3thY_nTh-izfhz1mg2maHGSPSpFMAWN307k,51
vicentin/optimization/minimization/conjugate_gradient/conjugate_gradient.py,sha256=_Fss2lZKZF80dmrWjPsSkC1oMG0bXshSx-jCblqYwWM,1893
vicentin/optimization/minimization/conjugate_gradient/conjugate_gradient_np.py,sha256=Y-e0uEN_oYeIJ-VFilHWyxQRMJcI8blMEEbDTojtyYA,825
vicentin/optimization/minimization/conjugate_gradient/conjugate_gradient_torch.py,sha256=YcHdr7tIlT32lbnjWiZXPWgjiUg-qPSM2Q_-li7cpzA,957
vicentin/optimization/minimization/gradient_descent/__init__.py,sha256=stMLlyfNAmYsz5F_l5E5sf_r8gNRfsH0vj2O5ZlJevY,47
vicentin/optimization/minimization/gradient_descent/gradient_descent.py,sha256=CKv10foQf6rFO6jKJ_T5XtAEPBAQBkqgwuToh5Q8gzM,4101
vicentin/optimization/minimization/gradient_descent/gradient_descent_np.py,sha256=_MGd3AbUNXdiHbsTfC9rsywk6yntIl8hMaPkOv7V2Yg,1439
vicentin/optimization/minimization/gradient_descent/gradient_descent_torch.py,sha256=RN31Gfpegnhnc7ghTyEXkxp8Z2BKp-ljxqmSltpj_-o,1627
vicentin/optimization/minimization/ista/__init__.py,sha256=qB0PEX3OV9yeeIhTNHbU11kuMWBobT21MVGjOEQs1Wg,23
vicentin/optimization/minimization/ista/ista.py,sha256=wshBHXs2RphFUlP6HrI1g-BY0sPguCjsDRT3rDtgmgI,3041
vicentin/optimization/minimization/ista/ista_np.py,sha256=17-6kJC9VN0Wi1PqzyvO4HO6kbj4Rc_DCFcGu3V06Xw,802
vicentin/optimization/minimization/ista/ista_torch.py,sha256=-5S56Spdkp-BGDxcDKvKDyEJiX5OlSlwtkSThWciiMA,833
vicentin/optimization/minimization/newton_method/__init__.py,sha256=lIju7X-ePSJFishxoW3t6u3xMgr5LzhDbM-1zBfiHtQ,44
vicentin/optimization/minimization/newton_method/newton.py,sha256=0zG1S6U9cGuTRF43qSKImxj88BnG2O56ONEG7Q9-bXM,6018
vicentin/optimization/minimization/newton_method/newton_np.py,sha256=x77IiHzpuhWQ9jx8mVHJHGRVsgAoym7zskRAdW1aiA4,3397
vicentin/optimization/minimization/newton_method/newton_torch.py,sha256=Q9YuyeKRS0HeiuStdS7fWYdr3R0j69L-p1DOYphe-B0,4057
vicentin/optimization/minimization/nonlinear_conjugate_gradient/__init__.py,sha256=8OnYhbHyzcsFpAPJeVrpc4ZXG_lhOIreslH6dcW3ku0,46
vicentin/optimization/minimization/nonlinear_conjugate_gradient/ncg.py,sha256=qs_BTthAdVBLqFS5BoFIYSbQ_BP6fyGJBhS7RHfFlfs,3600
vicentin/optimization/minimization/nonlinear_conjugate_gradient/ncg_np.py,sha256=weI-OiLD7wvD6DGYFmNyY9dxDJXK207IgEnslq7OEBE,1800
vicentin/optimization/minimization/nonlinear_conjugate_gradient/ncg_torch.py,sha256=0RQ_fysw6eF7XW8Ragxlz5Fupwoxt1BqQ05OluTmvaQ,2061
vicentin/optimization/minimization/projected_gradient_descent/__init__.py,sha256=UhbTn0yt63mg7brRN4ikewaCLf-m4RyGG4_2QaCNT2A,59
vicentin/optimization/minimization/projected_gradient_descent/projected_gradient.py,sha256=7qgiJqcSVo278j0w-afvnl9SrbBASvun8bIbtl-ML_c,2164
vicentin/optimization/minimization/projected_gradient_descent/projected_gradient_np.py,sha256=GEMI8gC-8uqYDqoGoHppp-8p120pcEzgSS2zRiVyuY8,652
vicentin/optimization/minimization/projected_gradient_descent/projected_gradient_torch.py,sha256=3WdknpffGYYg_k4y4cCdKQ9iFuadWLsf-AGp8PhqJMU,620
vicentin/optimization/minimization/proximal_gradient_descent/__init__.py,sha256=i3N6jgsGRl4r-xFyzEh7GgoOP7wH7zqG1v97lOleLt4,57
vicentin/optimization/minimization/proximal_gradient_descent/proximal_gradient.py,sha256=tr9e9Eby3JLri9a2hA67fPxzariSeaSbgp-RkJZXo9E,3285
vicentin/optimization/minimization/proximal_gradient_descent/proximal_gradient_np.py,sha256=9eX-aNSYlNbobhj9OjNVw171_jy86MAaOI6nVVnO3G8,1654
vicentin/optimization/minimization/proximal_gradient_descent/proximal_gradient_torch.py,sha256=BkVEhuFn74vrGtm2Hh7ZKJT0OEHDokS7E6qyREMCdYE,1936
vicentin/optimization/problems/__init__.py,sha256=oWBGYzqr21w788n_ZNBSxtakkjIXapcPRjSReJryFmk,162
vicentin/optimization/problems/LP/__init__.py,sha256=_2TiVkuEkHckLszWoVxAN1J63amjWK8Re5-Y25LhOG8,19
vicentin/optimization/problems/LP/lp.py,sha256=_NQfY_Hfl2stqHhxxM3UmU-FUI_esRv8NsCZxoDLaQU,2956
vicentin/optimization/problems/LP/lp_np.py,sha256=YcrmQQk5nqKhImMo4omj8pZQvozLrbPksutT5fdX1Go,1193
vicentin/optimization/problems/LP/lp_torch.py,sha256=mTWPVLC8h_WvQ5RCwqayxdeRMw5RyVZzu7oiJzXIuo4,908
vicentin/optimization/problems/QP/__init__.py,sha256=wSEYjH97P1xABb-I3aTSEy0NyqE7IfPl0wDa2-_Ov8w,19
vicentin/optimization/problems/QP/qp.py,sha256=dhxez0gQvQtUC0wN0OY-ituqvhhAdwLRG6RB0Wu2LjA,3094
vicentin/optimization/problems/QP/qp_np.py,sha256=-IpF326yiBPFLbKFqsqOzzWQJ7GQSG_LIoqYLMPTGjc,1359
vicentin/optimization/problems/QP/qp_torch.py,sha256=RG2zQWbh9iNH6EDLRzWz6czNKSJ3S_wP3ROehki1X0o,1062
vicentin/optimization/problems/SDP/__init__.py,sha256=QwlRhU4O0IQ80mj_HOw_gOJ3FGtQ_OUoYITlAWDLE84,31
vicentin/optimization/problems/SDP/sdp.py,sha256=htxh99A0EMGYhBXnCQ1_f3KMUM2JVnNkqIxtqBa2dZQ,8614
vicentin/optimization/problems/SDP/sdp_np.py,sha256=g4yV-klTay_nUpodjCdJ-2NTu27WfPKaXLpAXWhdyg4,5684
vicentin/optimization/problems/SDP/sdp_torch.py,sha256=7WM9fVHoJP20yWWYM8k2V5CnLYOj9zzrTNLRsZVxuz4,4998
vicentin/optimization/problems/SOCP/__init__.py,sha256=OtaC94Xp47uYSODi-zqNjJV-97-MYjxbXDZ9-YQL5gI,23
vicentin/optimization/problems/SOCP/socp.py,sha256=bF04pr6-APG2Uy6tcxZRRH1NHt0i-gjlbzsfngOWHXA,4019
vicentin/optimization/problems/SOCP/socp_np.py,sha256=Ula5jm2NzKeA83qM__fDQx1z77yYi2Ln6L47lznjHgk,1942
vicentin/optimization/problems/SOCP/socp_torch.py,sha256=uvdw4XwwRGUsaDzPlF-3YdqdfMWuH5UDSZx0UPQGptw,1406
vicentin/optimization/problems/optimal_matrix_conditioning/__init__.py,sha256=YqDjzfFWSbp6DJ6xfMNY9oqHBa3CA0IPKICOGdtv2Ko,45
vicentin/optimization/problems/optimal_matrix_conditioning/omc.py,sha256=V6IXAEANZrzQPUF5WLTrY9ActJVTuMlol3KaajGRm6Q,2639
vicentin/optimization/problems/optimal_matrix_conditioning/omc_np.py,sha256=v3IrZ-VxeW87Qxsjt-3mpK73Y_JB-9sUXU0qNN5KGbk,1748
vicentin/optimization/problems/optimal_matrix_conditioning/omc_torch.py,sha256=AHXtRVDzTA8KG9Bjpk7_o4on3WWUJzC4wLzqbei67P4,1744
vicentin/optimization/root_finding/__init__.py,sha256=YU7mj42ezkX3CIWPCB3wMDyWrVdNSkv11rAvwRfTGCQ,43
vicentin/optimization/root_finding/newton_raphson/__init__.py,sha256=YU7mj42ezkX3CIWPCB3wMDyWrVdNSkv11rAvwRfTGCQ,43
vicentin/optimization/root_finding/newton_raphson/newton_raphson.py,sha256=fAzl1NoZ8tmZIcSgcnzjHHm_MA2yo__cV4I9_XeuMfs,3724
vicentin/optimization/root_finding/newton_raphson/newton_raphson_np.py,sha256=BiYB1tGL6Q5cswuOPHdCIYqJBsDVKc94P1H7R81X1fQ,874
vicentin/optimization/root_finding/newton_raphson/newton_raphson_torch.py,sha256=z44PJ_nHJ8vDYlUbMcZsibNPtTPfks8BtCl89sMbpeM,964
vicentin/papers/Grad_CAM/__init__.py,sha256=D3xJn7QbpNyOnBwjw5PEFpw8ZBdFPZ2T4EacKyyuoBE,3967
vicentin/papers/SimCLR/__init__.py,sha256=ofikOCXPBBi-e5ulggyCkkU0C5QVqF8ZJPWdWTk_Gjc,1559
vicentin/papers/SimCLR/model.py,sha256=7niKigqrY19LoLiPL6HEeBmHXPDhNkUmB6HbrDw3vc4,2322
vicentin/papers/SimCLR/trainer.py,sha256=igEnZ_LqUNZgsXVTBqYegN-AWwe62cnT5obWOsgAt2A,3773
vicentin/papers/SimCLR/transform.py,sha256=GkUp4_prwZuw-_uKgpqKA3UQ5wD4GSKDin6Eq5yOQtA,2672
vicentin/sorting/__init__.py,sha256=aj1uDvE9rZT1azyWIWqp5Hde3k5HA9ygG92uBfK2WUE,31
vicentin/sorting/heapsort.py,sha256=nXCFU7WSiiwjG9UUxPcVWB1kkPYE3SHkREFFAK22Lk0,215
vicentin/utils/__init__.py,sha256=4jt7F5ce7g-3-EUTpOMQbJebEcpUVfDETde7sfs87Bg,35
vicentin/utils/dispatcher.py,sha256=IPzC2wGbOFyEzKSsqsSiJF2u9ROBCEAwfvH23-llCIM,3444
vicentin-1.4.3.dist-info/licenses/LICENSE,sha256=gA7ktZz73_sH-rNVP7xvxhKdjSLh6UCX1zRfEcQHSW0,1072
vicentin-1.4.3.dist-info/METADATA,sha256=AlRRU6FFOm4jOFdUEgmB_GNo2zpmIlVZd11CPA7F4nE,9445
vicentin-1.4.3.dist-info/WHEEL,sha256=YCfwYGOYMi5Jhw2fU4yNgwErybb2IX5PEwBKV4ZbdBo,91
vicentin-1.4.3.dist-info/top_level.txt,sha256=2GF2YgTUzUTqeS0vlnOAD0Yc3rQH47-WMj-HtJs6Lug,9
vicentin-1.4.3.dist-info/RECORD,,
