From 67f99f3354bd7beb04d16673f7fc7c89b24acf77 Mon Sep 17 00:00:00 2001 From: "Harle, Antoine (Contracteur)" Date: Thu, 14 Nov 2019 13:13:03 -0500 Subject: [PATCH] Resultats avec early stop sur data test --- higher/compare_res.py | 15 +- higher/model.py | 3 +- ...-LeNet)-10 epochs (dataug:0)- 10 in_it.png | Bin 0 -> 77003 bytes ...)-LeNet)-2 epochs (dataug:0)- 10 in_it.png | Bin 0 -> 56619 bytes ...LeNet)-200 epochs (dataug:0)- 10 in_it.png | Bin 0 -> 133185 bytes ...16-d28))-10 epochs (dataug:0)- 2 in_it.png | Bin 0 -> 108045 bytes ...-LeNet)-200 epochs (dataug:0)- 0 in_it.png | Bin 0 -> 37995 bytes ...LeNet)-200 epochs (dataug:0)- 10 in_it.png | Bin 0 -> 38595 bytes ...-LeNet)-200 epochs (dataug:0)- 0 in_it.png | Bin 0 -> 51536 bytes ...LeNet)-200 epochs (dataug:0)- 10 in_it.png | Bin 0 -> 82063 bytes ...-LeNet)-200 epochs (dataug:0)- 0 in_it.png | Bin 0 -> 49705 bytes ...LeNet)-200 epochs (dataug:0)- 10 in_it.png | Bin 0 -> 82382 bytes ...-LeNet)-200 epochs (dataug:0)- 0 in_it.png | 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10 in_it.json | 2777 ++++++++---- ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 1745 ++++++-- ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 3883 ++++++++++++---- ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 443 ++ ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 421 ++ ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 483 ++ ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 555 +++ ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 679 +++ ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 705 +++ ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 857 ++++ ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 871 ++++ ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 1083 +++++ ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 1023 +++++ ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 1123 +++++ ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 1027 +++++ ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 1244 ++++++ ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 1244 ++++++ ...LeNet)-200 epochs (dataug:0)- 0 in_it.json | 1299 ++++++ ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 1137 +++++ higher/res/TF_nb_tests_compare.png | Bin 218864 -> 112925 bytes higher/res/TF_seq_tests_compare.png | Bin 78607 -> 119145 bytes higher/res/WideResNet(s16-d28)-10 epochs.png | Bin 0 -> 35332 bytes ...LeNet)-10 epochs (dataug:0)- 10 in_it.json | 256 ++ ...-LeNet)-2 epochs (dataug:0)- 10 in_it.json | 72 + ...eNet)-200 epochs (dataug:0)- 10 in_it.json | 2280 ++++++++++ ...6-d28))-10 epochs (dataug:0)- 2 in_it.json | 256 ++ .../log/WideResNet (s16-d28)-10 epochs.json | 90 + higher/test_dataug.py | 26 +- 85 files changed, 42780 insertions(+), 6607 deletions(-) create mode 100644 higher/res/Aug_mod(Data_augV4(Uniform-14 TF x 2)-LeNet)-10 epochs (dataug:0)- 10 in_it.png create mode 100644 higher/res/Aug_mod(Data_augV4(Uniform-14 TF x 2)-LeNet)-2 epochs (dataug:0)- 10 in_it.png create mode 100644 higher/res/Aug_mod(Data_augV4(Uniform-14 TF x 2)-LeNet)-200 epochs (dataug:0)- 10 in_it.png create mode 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TF x 2)-LeNet)-200 epochs (dataug:0)- 10 in_it.json create mode 100644 higher/res/log/Aug_mod(Data_augV4(Uniform-14 TF x 2)-WideResNet (s16-d28))-10 epochs (dataug:0)- 2 in_it.json create mode 100644 higher/res/log/WideResNet (s16-d28)-10 epochs.json diff --git a/higher/compare_res.py b/higher/compare_res.py index ee6c373..9113e2a 100644 --- a/higher/compare_res.py +++ b/higher/compare_res.py @@ -20,23 +20,24 @@ if __name__ == "__main__": #plot_compare(filenames=files, fig_name="res/compare") ## Acc, Time, Epochs = f(n_tf) ## + #fig_name="res/TF_nb_tests_compare" fig_name="res/TF_seq_tests_compare" - inner_its = [0] + inner_its = [0, 10] dataug_epoch_starts= [0] - TF_nb = range(1,14+1) - N_seq_TF= [1] #, 2, 3, 4] + TF_nb = 14#[len(TF.TF_dict)] #range(10,len(TF.TF_dict)+1) #[len(TF.TF_dict)] + N_seq_TF= [1, 2, 3, 4, 6] #[1] fig, ax = plt.subplots(ncols=3, figsize=(30, 8)) for in_it in inner_its: for dataug in dataug_epoch_starts: - n_tf = TF_nb + #n_tf = TF_nb #filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF)-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(n_tf, dataug, in_it) for n_tf in TF_nb] - filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(n_tf, 1, dataug, in_it) for n_tf in TF_nb] + #filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(n_tf, 1, dataug, in_it) for n_tf in TF_nb] - #n_tf = N_seq_TF + n_tf = N_seq_TF #filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(TF_nb, n_tf, dataug, in_it) for n_tf in N_seq_TF] - #filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-100 epochs (dataug:{})- {} in_it.json".format(TF_nb, n_tf, dataug, in_it) for n_tf in N_seq_TF] + filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(TF_nb, n_tf, dataug, in_it) for n_tf in N_seq_TF] all_data=[] diff --git a/higher/model.py b/higher/model.py index 3fd6435..7a10bce 100644 --- a/higher/model.py +++ b/higher/model.py @@ -55,6 +55,7 @@ class LeNet(nn.Module): #https://github.com/xternalz/WideResNet-pytorch/blob/master/wideresnet.py #https://github.com/arcelien/pba/blob/master/pba/wrn.py #https://github.com/szagoruyko/wide-residual-networks/blob/master/pytorch/resnet.py + class BasicBlock(nn.Module): def __init__(self, in_planes, out_planes, stride, dropRate=0.0): super(BasicBlock, self).__init__() @@ -145,4 +146,4 @@ class WideResNet(nn.Module): return super(WideResNet, self).__str__() def __str__(self): - return "WideResNet(s{}-d{})".format(self.kernel_size, self.depth) \ No newline at end of file + return "WideResNet(s{}-d{})".format(self.kernel_size, self.depth) diff --git a/higher/res/Aug_mod(Data_augV4(Uniform-14 TF x 2)-LeNet)-10 epochs (dataug:0)- 10 in_it.png 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b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 1)-LeNet)-200 epochs (dataug:0)- 10 in_it.json index 50edb0f..e29845c 100644 --- a/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 1)-LeNet)-200 epochs (dataug:0)- 10 in_it.json +++ b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 1)-LeNet)-200 epochs (dataug:0)- 10 in_it.json @@ -1,8 +1,8 @@ { - "Accuracy": 69.57, + "Accuracy": 67.31, "Time": [ - 57.89454772710967, - 0.6496335843324215 + 57.69659302938175, + 0.07572898561101372 ], "Device": "GeForce GTX 1060 with Max-Q Design", "Param_names": [ @@ -24,1681 +24,1267 @@ "Log": [ { "epoch": 1, - "train_loss": 2.352334499359131, - "val_loss": 2.2134766578674316, - "acc": 16.2, - "time": 57.156075316999704, + "train_loss": 2.2453691959381104, + "val_loss": 2.252627372741699, + "acc": 12.87, + "time": 57.623177114999635, "param": [ - 0.07751300930976868, - 0.01431206613779068, - 0.09699205309152603, - 0.07208564132452011, - 0.08958528190851212, - 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in_it.json b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 3)-LeNet)-200 epochs (dataug:0)- 0 in_it.json index 9f89533..6b76b55 100644 --- a/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 3)-LeNet)-200 epochs (dataug:0)- 0 in_it.json +++ b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 3)-LeNet)-200 epochs (dataug:0)- 0 in_it.json @@ -1,8 +1,8 @@ { - "Accuracy": 62.78, + "Accuracy": 69.29, "Time": [ - 51.7300376246445, - 0.8731297186207 + 52.36966983518383, + 0.6056947353774638 ], "Device": "GeForce GTX 1060 with Max-Q Design", "Param_names": [ @@ -24,10 +24,10 @@ "Log": [ { "epoch": 1, - "train_loss": 2.2985870838165283, - "val_loss": 2.2881712913513184, - "acc": 13.04, - "time": 51.86867559100028, + "train_loss": 2.298780679702759, + "val_loss": 2.292221784591675, + "acc": 11.58, + "time": 52.67441447100009, "param": [ 0.0714285746216774, 0.0714285746216774, @@ -47,10 +47,10 @@ }, { "epoch": 2, - "train_loss": 2.2657127380371094, - 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b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 3)-LeNet)-200 epochs (dataug:0)- 10 in_it.json index 1e56c91..6b28acf 100644 --- a/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 3)-LeNet)-200 epochs (dataug:0)- 10 in_it.json +++ b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 3)-LeNet)-200 epochs (dataug:0)- 10 in_it.json @@ -1,8 +1,8 @@ { - "Accuracy": 69.11, + "Accuracy": 72.98, "Time": [ - 78.08223047358258, - 0.5503200656988899 + 79.70043755434342, + 2.006097667641948 ], "Device": "GeForce GTX 1060 with Max-Q Design", "Param_names": [ @@ -24,2094 +24,3083 @@ "Log": [ { "epoch": 1, - "train_loss": 2.325634479522705, - "val_loss": 2.2943084239959717, - "acc": 11.81, - "time": 78.0832904500021, + "train_loss": 2.3084332942962646, + "val_loss": 2.2963359355926514, + "acc": 18.4, + "time": 78.38466803299525, "param": [ - 0.0856720432639122, - 0.03581717982888222, - 0.08180592954158783, - 0.10177181661128998, - 0.07082220166921616, - 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b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 4)-LeNet)-200 epochs (dataug:0)- 10 in_it.json index 2cdff49..be95693 100644 --- a/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 4)-LeNet)-200 epochs (dataug:0)- 10 in_it.json +++ b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 4)-LeNet)-200 epochs (dataug:0)- 10 in_it.json @@ -1,8 +1,8 @@ { - "Accuracy": 63.53, + "Accuracy": 67.97, "Time": [ - 88.94892483952661, - 1.0218807223932278 + 88.2294865530204, + 0.38674680301087505 ], "Device": "GeForce GTX 1060 with Max-Q Design", "Param_names": [ @@ -24,1314 +24,2303 @@ "Log": [ { "epoch": 1, - "train_loss": 2.2937495708465576, - "val_loss": 2.2831532955169678, - "acc": 10.11, - "time": 88.53159136500108, + "train_loss": 2.384758234024048, + "val_loss": 2.2956037521362305, + "acc": 14.94, + "time": 88.8974955080048, "param": [ - 0.08208360522985458, - 0.07411950826644897, - 0.08739598095417023, - 0.07747599482536316, - 0.07225620001554489, - 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in_it.json index c6b54d9..3c16f30 100644 --- a/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 6)-LeNet)-200 epochs (dataug:0)- 0 in_it.json +++ b/higher/res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-14 TF x 6)-LeNet)-200 epochs (dataug:0)- 0 in_it.json @@ -1,8 +1,8 @@ { - "Accuracy": 60.18, + "Accuracy": 65.68, "Time": [ - 120.44632856826152, - 1.4812189264572635 + 84.02286914551695, + 0.8916275064098121 ], "Device": "GeForce GTX 1060 with Max-Q Design", "Param_names": [ @@ -24,10 +24,10 @@ "Log": [ { "epoch": 1, - "train_loss": 2.297180652618408, - "val_loss": 2.2862095832824707, - "acc": 10.290000000000001, - "time": 120.47809954900004, + "train_loss": 2.3058183193206787, + "val_loss": 2.2930076122283936, + "acc": 11.96, + "time": 83.74845831299899, "param": [ 0.0714285746216774, 0.0714285746216774, @@ -47,10 +47,10 @@ }, { "epoch": 2, - "train_loss": 2.292750358581543, - "val_loss": 2.265082597732544, - "acc": 16.900000000000002, - "time": 118.43831282200154, + 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0000000..4254cfc --- /dev/null +++ b/higher/res/log/WideResNet (s16-d28)-10 epochs.json @@ -0,0 +1,90 @@ +{ + "Accuracy": 54.8, + "Time": [ + 5.3848224994, + 0.2715924716188192 + ], + "Device": "TITAN RTX", + "Log": [ + { + "epoch": 0, + "train_loss": 1.9575108289718628, + "val_loss": 1.9943608045578003, + "acc": 25.56, + "time": 5.545910851999999, + "param": null + }, + { + "epoch": 1, + "train_loss": 1.6852270364761353, + "val_loss": 1.6786702871322632, + "acc": 35.81, + "time": 4.996102581000001, + "param": null + }, + { + "epoch": 2, + "train_loss": 1.5732556581497192, + "val_loss": 1.5089160203933716, + "acc": 40.41, + "time": 5.152823367, + "param": null + }, + { + "epoch": 3, + "train_loss": 1.5042539834976196, + "val_loss": 1.5381317138671875, + "acc": 42.35, + "time": 5.274372500999998, + "param": null + }, + { + "epoch": 4, + "train_loss": 1.4542087316513062, + "val_loss": 1.481497883796692, + "acc": 40.17, + "time": 5.025118689999999, + "param": null + }, + { + "epoch": 5, + "train_loss": 1.3443793058395386, + "val_loss": 1.3244030475616455, + "acc": 45.61, + "time": 5.223940236000004, + "param": null + }, + { + "epoch": 6, + "train_loss": 1.3861349821090698, + "val_loss": 1.2120888233184814, + "acc": 46.14, + "time": 5.778372300999997, + "param": null + }, + { + "epoch": 7, + "train_loss": 1.1211127042770386, + "val_loss": 1.1805596351623535, + "acc": 48.79, + "time": 5.614833493000006, + "param": null + }, + { + "epoch": 8, + "train_loss": 1.1572871208190918, + "val_loss": 1.1212867498397827, + "acc": 52.79, + "time": 5.512548168999999, + "param": null + }, + { + "epoch": 9, + "train_loss": 1.0941531658172607, + "val_loss": 1.2294477224349976, + "acc": 54.8, + "time": 5.724202804000001, + "param": null + } + ] +} \ No newline at end of file diff --git a/higher/test_dataug.py b/higher/test_dataug.py index 667169e..de65d64 100644 --- a/higher/test_dataug.py +++ b/higher/test_dataug.py @@ -64,12 +64,12 @@ if __name__ == "__main__": print('-'*9) ''' #### Augmented Model #### - #''' + ''' t0 = time.process_time() tf_dict = {k: TF.TF_dict[k] for k in tf_names} #tf_dict = TF.TF_dict - aug_model = Augmented_model(Data_augV4(TF_dict=tf_dict, N_TF=2, mix_dist=0.0), LeNet(3,10)).to(device) - #aug_model = Augmented_model(Data_augV4(TF_dict=tf_dict, N_TF=2, mix_dist=0.0), WideResNet(num_classes=10, wrn_size=160)).to(device) + #aug_model = Augmented_model(Data_augV4(TF_dict=tf_dict, N_TF=2, mix_dist=0.0), LeNet(3,10)).to(device) + aug_model = Augmented_model(Data_augV4(TF_dict=tf_dict, N_TF=2, mix_dist=0.0), WideResNet(num_classes=10, wrn_size=160)).to(device) print(str(aug_model), 'on', device_name) #run_simple_dataug(inner_it=n_inner_iter, epochs=epochs) log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=1, loss_patience=10) @@ -86,15 +86,15 @@ if __name__ == "__main__": print('Execution Time : %.00f (s?)'%(time.process_time() - t0)) print('-'*9) - #''' - #### TF number tests #### ''' + #### TF number tests #### + #''' res_folder="res/TF_nb_tests/" - epochs= 200 - inner_its = [10] + epochs= 100 + inner_its = [0, 10] dataug_epoch_starts= [0] - TF_nb = range(1,len(TF.TF_dict)+1) #[len(TF.TF_dict)] - N_seq_TF= [1] #[1, 2, 3, 4] + TF_nb = [len(TF.TF_dict)] #range(10,len(TF.TF_dict)+1) #[len(TF.TF_dict)] + N_seq_TF= [2, 3, 4, 6] try: os.mkdir(res_folder) @@ -114,17 +114,17 @@ if __name__ == "__main__": aug_model = Augmented_model(Data_augV4(TF_dict=ntf_dict, N_TF=n_tf, mix_dist=0.0), LeNet(3,10)).to(device) print(str(aug_model), 'on', device_name) #run_simple_dataug(inner_it=n_inner_iter, epochs=epochs) - log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=10, loss_patience=10) + log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=10, loss_patience=None) #### - plot_res(log, fig_name=res_folder+"{}-{} epochs (dataug:{})- {} in_it".format(str(aug_model),epochs,dataug_epoch_start,n_inner_iter)) + plot_res(log, fig_name=res_folder+"{}-{} epochs (dataug:{})- {} in_it".format(str(aug_model),epochs,dataug_epoch_start,n_inner_iter), param_names=keys) print('-'*9) times = [x["time"] for x in log] out = {"Accuracy": max([x["acc"] for x in log]), "Time": (np.mean(times),np.std(times)), "Device": device_name, "Param_names": aug_model.TF_names(), "Log": log} - print(str(aug_model),": acc", out["Accuracy"], "in (ms):", out["Time"][0], "+/-", out["Time"][1]) + print(str(aug_model),": acc", out["Accuracy"], "in (s?):", out["Time"][0], "+/-", out["Time"][1]) with open(res_folder+"log/%s.json" % "{}-{} epochs (dataug:{})- {} in_it".format(str(aug_model),epochs,dataug_epoch_start,n_inner_iter), "w+") as f: json.dump(out, f, indent=True) print('Log :\"',f.name, '\" saved !') print('-'*9) - ''' \ No newline at end of file + #''' \ No newline at end of file

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