神经网络框架TensorFlow，谷歌开发
序列结果下：
image.png
image.png
控制台结果如下：
G:\python_projectkotin\venv\Scripts\python.exe F:/vscode-python-kiton/数学/TensorFlow/zijiancpugpu-vs.py
2021-12-02 03:50:38.798149: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2021-12-02 03:50:38.798433: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
训练数据形状， (60000, 28, 28)
数据最大值 255
查看标签数值 [9 0 0 ... 3 0 5]
2021-12-02 03:50:45.909224: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-12-02 03:50:45.957119: E tensorflow/stream_executor/cuda/cuda_driver.cc:351] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected
2021-12-02 03:50:45.960296: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: KOTIN
2021-12-02 03:50:45.960534: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: KOTIN
2021-12-02 03:50:45.961982: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
flatten (Flatten) (None, 784) 0
_________________________________________________________________
dense (Dense) (None, 128) 100480
_________________________________________________________________
dense_1 (Dense) (None, 10) 1290
=================================================================
Total params: 101,770
Trainable params: 101,770
Non-trainable params: 0
_________________________________________________________________
查看自己写的代码的总体参数 None
Train on 60000 samples
Epoch 1/10
32/60000 [..............................] - ETA: 5:57 - loss: 2.4495 - accuracy: 0.0312
2112/60000 [>.............................] - ETA: 6s - loss: 1.0450 - accuracy: 0.6274
4288/60000 [=>............................] - ETA: 3s - loss: 0.8700 - accuracy: 0.6887
6432/60000 [==>...........................] - ETA: 2s - loss: 0.7774 - accuracy: 0.7240
8544/60000 [===>..........................] - ETA: 2s - loss: 0.7263 - accuracy: 0.7425
10624/60000 [====>.........................] - ETA: 2s - loss: 0.6925 - accuracy: 0.7569
12768/60000 [=====>........................] - ETA: 1s - loss: 0.6670 - accuracy: 0.7660
14912/60000 [======>.......................] - ETA: 1s - loss: 0.6416 - accuracy: 0.7748
17088/60000 [=======>......................] - ETA: 1s - loss: 0.6248 - accuracy: 0.7792
19232/60000 [========>.....................] - ETA: 1s - loss: 0.6133 - accuracy: 0.7842
21344/60000 [=========>....................] - ETA: 1s - loss: 0.6025 - accuracy: 0.7887
23520/60000 [==========>...................] - ETA: 1s - loss: 0.5909 - accuracy: 0.7927
25632/60000 [===========>..................] - ETA: 1s - loss: 0.5812 - accuracy: 0.7964
27712/60000 [============>.................] - ETA: 0s - loss: 0.5717 - accuracy: 0.7993
29792/60000 [=============>................] - ETA: 0s - loss: 0.5626 - accuracy: 0.8021
31936/60000 [==============>...............] - ETA: 0s - loss: 0.5544 - accuracy: 0.8049
34112/60000 [================>.............] - ETA: 0s - loss: 0.5491 - accuracy: 0.8070
36224/60000 [=================>............] - ETA: 0s - loss: 0.5423 - accuracy: 0.8089
38368/60000 [==================>...........] - ETA: 0s - loss: 0.5370 - accuracy: 0.8111
40448/60000 [===================>..........] - ETA: 0s - loss: 0.5328 - accuracy: 0.8125
42624/60000 [====================>.........] - ETA: 0s - loss: 0.5273 - accuracy: 0.8149
44736/60000 [=====================>........] - ETA: 0s - loss: 0.5232 - accuracy: 0.8160
46880/60000 [======================>.......] - ETA: 0s - loss: 0.5191 - accuracy: 0.8170
48992/60000 [=======================>......] - ETA: 0s - loss: 0.5162 - accuracy: 0.8183
51072/60000 [========================>.....] - ETA: 0s - loss: 0.5105 - accuracy: 0.8202
53248/60000 [=========================>....] - ETA: 0s - loss: 0.5062 - accuracy: 0.8219
54592/60000 [==========================>...] - ETA: 0s - loss: 0.5039 - accuracy: 0.8225
56640/60000 [===========================>..] - ETA: 0s - loss: 0.5005 - accuracy: 0.8239
58784/60000 [============================>.] - ETA: 0s - loss: 0.4967 - accuracy: 0.8250
60000/60000 [==============================] - 2s 28us/sample - loss: 0.4947 - accuracy: 0.8257
Epoch 2/10
32/60000 [..............................] - ETA: 1s - loss: 0.3743 - accuracy: 0.8750
2112/60000 [>.............................] - ETA: 1s - loss: 0.3884 - accuracy: 0.8575
4256/60000 [=>............................] - ETA: 1s - loss: 0.3778 - accuracy: 0.8607
6272/60000 [==>...........................] - ETA: 1s - loss: 0.3752 - accuracy: 0.8619
8192/60000 [===>..........................] - ETA: 1s - loss: 0.3764 - accuracy: 0.8622
10112/60000 [====>.........................] - ETA: 1s - loss: 0.3782 - accuracy: 0.8624
12032/60000 [=====>........................] - ETA: 1s - loss: 0.3800 - accuracy: 0.8625
14080/60000 [======>.......................] - ETA: 1s - loss: 0.3772 - accuracy: 0.8630
16160/60000 [=======>......................] - ETA: 1s - loss: 0.3767 - accuracy: 0.8629
18176/60000 [========>.....................] - ETA: 1s - loss: 0.3819 - accuracy: 0.8614
20256/60000 [=========>....................] - ETA: 0s - loss: 0.3805 - accuracy: 0.8625
22400/60000 [==========>...................] - ETA: 0s - loss: 0.3811 - accuracy: 0.8617
24512/60000 [===========>..................] - ETA: 0s - loss: 0.3817 - accuracy: 0.8619
26592/60000 [============>.................] - ETA: 0s - loss: 0.3818 - accuracy: 0.8617
28704/60000 [=============>................] - ETA: 0s - loss: 0.3817 - accuracy: 0.8610
30848/60000 [==============>...............] - ETA: 0s - loss: 0.3799 - accuracy: 0.8622
32928/60000 [===============>..............] - ETA: 0s - loss: 0.3783 - accuracy: 0.8629
35040/60000 [================>.............] - ETA: 0s - loss: 0.3774 - accuracy: 0.8633
37120/60000 [=================>............] - ETA: 0s - loss: 0.3784 - accuracy: 0.8627
39264/60000 [==================>...........] - ETA: 0s - loss: 0.3777 - accuracy: 0.8626
41408/60000 [===================>..........] - ETA: 0s - loss: 0.3766 - accuracy: 0.8628
43392/60000 [====================>.........] - ETA: 0s - loss: 0.3765 - accuracy: 0.8629
45472/60000 [=====================>........] - ETA: 0s - loss: 0.3754 - accuracy: 0.8635
47616/60000 [======================>.......] - ETA: 0s - loss: 0.3750 - accuracy: 0.8638
49696/60000 [=======================>......] - ETA: 0s - loss: 0.3735 - accuracy: 0.8648
51808/60000 [========================>.....] - ETA: 0s - loss: 0.3729 - accuracy: 0.8648
53920/60000 [=========================>....] - ETA: 0s - loss: 0.3725 - accuracy: 0.8652
56064/60000 [===========================>..] - ETA: 0s - loss: 0.3725 - accuracy: 0.8653
58176/60000 [============================>.] - ETA: 0s - loss: 0.3727 - accuracy: 0.8654
60000/60000 [==============================] - 1s 24us/sample - loss: 0.3722 - accuracy: 0.8658
Epoch 3/10
32/60000 [..............................] - ETA: 1s - loss: 0.3212 - accuracy: 0.8438
2080/60000 [>.............................] - ETA: 1s - loss: 0.3320 - accuracy: 0.8659
4224/60000 [=>............................] - ETA: 1s - loss: 0.3536 - accuracy: 0.8655
6336/60000 [==>...........................] - ETA: 1s - loss: 0.3397 - accuracy: 0.8741
8416/60000 [===>..........................] - ETA: 1s - loss: 0.3368 - accuracy: 0.8752
10496/60000 [====>.........................] - ETA: 1s - loss: 0.3326 - accuracy: 0.8760
12608/60000 [=====>........................] - ETA: 1s - loss: 0.3325 - accuracy: 0.8761
14720/60000 [======>.......................] - ETA: 1s - loss: 0.3325 - accuracy: 0.8755
16768/60000 [=======>......................] - ETA: 1s - loss: 0.3325 - accuracy: 0.8760
18880/60000 [========>.....................] - ETA: 0s - loss: 0.3317 - accuracy: 0.8765
20928/60000 [=========>....................] - ETA: 0s - loss: 0.3312 - accuracy: 0.8766
23040/60000 [==========>...................] - ETA: 0s - loss: 0.3320 - accuracy: 0.8763
25088/60000 [===========>..................] - ETA: 0s - loss: 0.3313 - accuracy: 0.8763
27168/60000 [============>.................] - ETA: 0s - loss: 0.3300 - accuracy: 0.8772
29280/60000 [=============>................] - ETA: 0s - loss: 0.3303 - accuracy: 0.8767
31392/60000 [==============>...............] - ETA: 0s - loss: 0.3327 - accuracy: 0.8764
33472/60000 [===============>..............] - ETA: 0s - loss: 0.3322 - accuracy: 0.8768
35584/60000 [================>.............] - ETA: 0s - loss: 0.3328 - accuracy: 0.8769
37728/60000 [=================>............] - ETA: 0s - loss: 0.3326 - accuracy: 0.8771
39872/60000 [==================>...........] - ETA: 0s - loss: 0.3322 - accuracy: 0.8771
41888/60000 [===================>..........] - ETA: 0s - loss: 0.3323 - accuracy: 0.8771
43968/60000 [====================>.........] - ETA: 0s - loss: 0.3327 - accuracy: 0.8770
45888/60000 [=====================>........] - ETA: 0s - loss: 0.3318 - accuracy: 0.8775
47968/60000 [======================>.......] - ETA: 0s - loss: 0.3327 - accuracy: 0.8772
50048/60000 [========================>.....] - ETA: 0s - loss: 0.3333 - accuracy: 0.8767
52160/60000 [=========================>....] - ETA: 0s - loss: 0.3326 - accuracy: 0.8769
54208/60000 [==========================>...] - ETA: 0s - loss: 0.3330 - accuracy: 0.8768
56288/60000 [===========================>..] - ETA: 0s - loss: 0.3328 - accuracy: 0.8771
58400/60000 [============================>.] - ETA: 0s - loss: 0.3325 - accuracy: 0.8776
60000/60000 [==============================] - 1s 24us/sample - loss: 0.3336 - accuracy: 0.8775
Epoch 4/10
32/60000 [..............................] - ETA: 1s - loss: 0.3212 - accuracy: 0.9062
2176/60000 [>.............................] - ETA: 1s - loss: 0.3168 - accuracy: 0.8810
4256/60000 [=>............................] - ETA: 1s - loss: 0.3032 - accuracy: 0.8884
6304/60000 [==>...........................] - ETA: 1s - loss: 0.3039 - accuracy: 0.8861
8416/60000 [===>..........................] - ETA: 1s - loss: 0.3089 - accuracy: 0.8838
10560/60000 [====>.........................] - ETA: 1s - loss: 0.3106 - accuracy: 0.8844
12672/60000 [=====>........................] - ETA: 1s - loss: 0.3097 - accuracy: 0.8849
14784/60000 [======>.......................] - ETA: 1s - loss: 0.3119 - accuracy: 0.8840
16896/60000 [=======>......................] - ETA: 1s - loss: 0.3134 - accuracy: 0.8828
19008/60000 [========>.....................] - ETA: 0s - loss: 0.3130 - accuracy: 0.8830
21120/60000 [=========>....................] - ETA: 0s - loss: 0.3133 - accuracy: 0.8835
23200/60000 [==========>...................] - ETA: 0s - loss: 0.3126 - accuracy: 0.8848
25344/60000 [===========>..................] - ETA: 0s - loss: 0.3160 - accuracy: 0.8835
27456/60000 [============>.................] - ETA: 0s - loss: 0.3152 - accuracy: 0.8833
29600/60000 [=============>................] - ETA: 0s - loss: 0.3155 - accuracy: 0.8833
31744/60000 [==============>...............] - ETA: 0s - loss: 0.3145 - accuracy: 0.8838
33888/60000 [===============>..............] - ETA: 0s - loss: 0.3141 - accuracy: 0.8844
36032/60000 [=================>............] - ETA: 0s - loss: 0.3143 - accuracy: 0.8845
38080/60000 [==================>...........] - ETA: 0s - loss: 0.3155 - accuracy: 0.8844
40192/60000 [===================>..........] - ETA: 0s - loss: 0.3148 - accuracy: 0.8846
42304/60000 [====================>.........] - ETA: 0s - loss: 0.3151 - accuracy: 0.8849
44448/60000 [=====================>........] - ETA: 0s - loss: 0.3149 - accuracy: 0.8849
46592/60000 [======================>.......] - ETA: 0s - loss: 0.3147 - accuracy: 0.8849
48704/60000 [=======================>......] - ETA: 0s - loss: 0.3136 - accuracy: 0.8852
50816/60000 [========================>.....] - ETA: 0s - loss: 0.3134 - accuracy: 0.8852
52960/60000 [=========================>....] - ETA: 0s - loss: 0.3126 - accuracy: 0.8856
55072/60000 [==========================>...] - ETA: 0s - loss: 0.3131 - accuracy: 0.8854
57216/60000 [===========================>..] - ETA: 0s - loss: 0.3114 - accuracy: 0.8860
59296/60000 [============================>.] - ETA: 0s - loss: 0.3111 - accuracy: 0.8861
60000/60000 [==============================] - 1s 24us/sample - loss: 0.3108 - accuracy: 0.8863
Epoch 5/10
32/60000 [..............................] - ETA: 1s - loss: 0.3649 - accuracy: 0.8438
2176/60000 [>.............................] - ETA: 1s - loss: 0.2805 - accuracy: 0.8915
4288/60000 [=>............................] - ETA: 1s - loss: 0.2906 - accuracy: 0.8937
6432/60000 [==>...........................] - ETA: 1s - loss: 0.2973 - accuracy: 0.8905
8544/60000 [===>..........................] - ETA: 1s - loss: 0.2966 - accuracy: 0.8902
10624/60000 [====>.........................] - ETA: 1s - loss: 0.2918 - accuracy: 0.8917
12704/60000 [=====>........................] - ETA: 1s - loss: 0.2951 - accuracy: 0.8904
14784/60000 [======>.......................] - ETA: 1s - loss: 0.2940 - accuracy: 0.8910
16928/60000 [=======>......................] - ETA: 1s - loss: 0.2983 - accuracy: 0.8898
19008/60000 [========>.....................] - ETA: 0s - loss: 0.2969 - accuracy: 0.8900
21120/60000 [=========>....................] - ETA: 0s - loss: 0.2990 - accuracy: 0.8895
23200/60000 [==========>...................] - ETA: 0s - loss: 0.2991 - accuracy: 0.8897
25312/60000 [===========>..................] - ETA: 0s - loss: 0.2982 - accuracy: 0.8899
27456/60000 [============>.................] - ETA: 0s - loss: 0.2976 - accuracy: 0.8899
29568/60000 [=============>................] - ETA: 0s - loss: 0.2963 - accuracy: 0.8908
31712/60000 [==============>...............] - ETA: 0s - loss: 0.2956 - accuracy: 0.8911
33824/60000 [===============>..............] - ETA: 0s - loss: 0.2951 - accuracy: 0.8912
35968/60000 [================>.............] - ETA: 0s - loss: 0.2960 - accuracy: 0.8913
38048/60000 [==================>...........] - ETA: 0s - loss: 0.2954 - accuracy: 0.8913
40160/60000 [===================>..........] - ETA: 0s - loss: 0.2956 - accuracy: 0.8914
42304/60000 [====================>.........] - ETA: 0s - loss: 0.2945 - accuracy: 0.8920
44448/60000 [=====================>........] - ETA: 0s - loss: 0.2939 - accuracy: 0.8923
46560/60000 [======================>.......] - ETA: 0s - loss: 0.2955 - accuracy: 0.8916
48672/60000 [=======================>......] - ETA: 0s - loss: 0.2946 - accuracy: 0.8919
50752/60000 [========================>.....] - ETA: 0s - loss: 0.2939 - accuracy: 0.8920
52928/60000 [=========================>....] - ETA: 0s - loss: 0.2933 - accuracy: 0.8921
55040/60000 [==========================>...] - ETA: 0s - loss: 0.2931 - accuracy: 0.8923
57152/60000 [===========================>..] - ETA: 0s - loss: 0.2935 - accuracy: 0.8922
59296/60000 [============================>.] - ETA: 0s - loss: 0.2941 - accuracy: 0.8918
60000/60000 [==============================] - 1s 24us/sample - loss: 0.2944 - accuracy: 0.8917
Epoch 6/10
32/60000 [..............................] - ETA: 1s - loss: 0.2428 - accuracy: 0.8750
2144/60000 [>.............................] - ETA: 1s - loss: 0.2666 - accuracy: 0.9030
4128/60000 [=>............................] - ETA: 1s - loss: 0.2768 - accuracy: 0.9000
6144/60000 [==>...........................] - ETA: 1s - loss: 0.2669 - accuracy: 0.9033
8224/60000 [===>..........................] - ETA: 1s - loss: 0.2649 - accuracy: 0.9020
10336/60000 [====>.........................] - ETA: 1s - loss: 0.2724 - accuracy: 0.8988
12352/60000 [=====>........................] - ETA: 1s - loss: 0.2746 - accuracy: 0.8981
14432/60000 [======>.......................] - ETA: 1s - loss: 0.2750 - accuracy: 0.8984
16480/60000 [=======>......................] - ETA: 1s - loss: 0.2717 - accuracy: 0.8990
18624/60000 [========>.....................] - ETA: 1s - loss: 0.2705 - accuracy: 0.8998
20768/60000 [=========>....................] - ETA: 0s - loss: 0.2712 - accuracy: 0.8999
22784/60000 [==========>...................] - ETA: 0s - loss: 0.2711 - accuracy: 0.9001
24896/60000 [===========>..................] - ETA: 0s - loss: 0.2715 - accuracy: 0.9000
26976/60000 [============>.................] - ETA: 0s - loss: 0.2720 - accuracy: 0.8994
29088/60000 [=============>................] - ETA: 0s - loss: 0.2730 - accuracy: 0.8992
31232/60000 [==============>...............] - ETA: 0s - loss: 0.2737 - accuracy: 0.8985
33280/60000 [===============>..............] - ETA: 0s - loss: 0.2725 - accuracy: 0.8991
35424/60000 [================>.............] - ETA: 0s - loss: 0.2737 - accuracy: 0.8987
37536/60000 [=================>............] - ETA: 0s - loss: 0.2738 - accuracy: 0.8987
39680/60000 [==================>...........] - ETA: 0s - loss: 0.2737 - accuracy: 0.8986
41792/60000 [===================>..........] - ETA: 0s - loss: 0.2742 - accuracy: 0.8984
43840/60000 [====================>.........] - ETA: 0s - loss: 0.2750 - accuracy: 0.8985
45952/60000 [=====================>........] - ETA: 0s - loss: 0.2769 - accuracy: 0.8980
48064/60000 [=======================>......] - ETA: 0s - loss: 0.2770 - accuracy: 0.8980
50176/60000 [========================>.....] - ETA: 0s - loss: 0.2781 - accuracy: 0.8976
52320/60000 [=========================>....] - ETA: 0s - loss: 0.2774 - accuracy: 0.8979
54432/60000 [==========================>...] - ETA: 0s - loss: 0.2767 - accuracy: 0.8982
56512/60000 [===========================>..] - ETA: 0s - loss: 0.2778 - accuracy: 0.8975
58656/60000 [============================>.] - ETA: 0s - loss: 0.2787 - accuracy: 0.8973
60000/60000 [==============================] - 1s 24us/sample - loss: 0.2790 - accuracy: 0.8972
Epoch 7/10
32/60000 [..............................] - ETA: 3s - loss: 0.2386 - accuracy: 0.9062
2080/60000 [>.............................] - ETA: 1s - loss: 0.2425 - accuracy: 0.9115
4192/60000 [=>............................] - ETA: 1s - loss: 0.2627 - accuracy: 0.9034
6272/60000 [==>...........................] - ETA: 1s - loss: 0.2653 - accuracy: 0.9034
8384/60000 [===>..........................] - ETA: 1s - loss: 0.2667 - accuracy: 0.9024
10464/60000 [====>.........................] - ETA: 1s - loss: 0.2677 - accuracy: 0.9019
12608/60000 [=====>........................] - ETA: 1s - loss: 0.2671 - accuracy: 0.9016
14752/60000 [======>.......................] - ETA: 1s - loss: 0.2678 - accuracy: 0.9015
16896/60000 [=======>......................] - ETA: 1s - loss: 0.2678 - accuracy: 0.9014
19040/60000 [========>.....................] - ETA: 0s - loss: 0.2688 - accuracy: 0.9001
21152/60000 [=========>....................] - ETA: 0s - loss: 0.2733 - accuracy: 0.8984
23200/60000 [==========>...................] - ETA: 0s - loss: 0.2746 - accuracy: 0.8976
25344/60000 [===========>..................] - ETA: 0s - loss: 0.2738 - accuracy: 0.8984
27488/60000 [============>.................] - ETA: 0s - loss: 0.2735 - accuracy: 0.8988
29568/60000 [=============>................] - ETA: 0s - loss: 0.2735 - accuracy: 0.8988
31680/60000 [==============>...............] - ETA: 0s - loss: 0.2727 - accuracy: 0.8991
33824/60000 [===============>..............] - ETA: 0s - loss: 0.2729 - accuracy: 0.8988
35936/60000 [================>.............] - ETA: 0s - loss: 0.2715 - accuracy: 0.8994
38112/60000 [==================>...........] - ETA: 0s - loss: 0.2713 - accuracy: 0.8998
40256/60000 [===================>..........] - ETA: 0s - loss: 0.2711 - accuracy: 0.8994
42400/60000 [====================>.........] - ETA: 0s - loss: 0.2709 - accuracy: 0.8995
44544/60000 [=====================>........] - ETA: 0s - loss: 0.2704 - accuracy: 0.8995
46688/60000 [======================>.......] - ETA: 0s - loss: 0.2709 - accuracy: 0.8992
48832/60000 [=======================>......] - ETA: 0s - loss: 0.2699 - accuracy: 0.8996
51008/60000 [========================>.....] - ETA: 0s - loss: 0.2686 - accuracy: 0.8999
53056/60000 [=========================>....] - ETA: 0s - loss: 0.2679 - accuracy: 0.9000
55200/60000 [==========================>...] - ETA: 0s - loss: 0.2674 - accuracy: 0.9000
57376/60000 [===========================>..] - ETA: 0s - loss: 0.2661 - accuracy: 0.9002
59456/60000 [============================>.] - ETA: 0s - loss: 0.2663 - accuracy: 0.9001
60000/60000 [==============================] - 1s 24us/sample - loss: 0.2664 - accuracy: 0.9002
Epoch 8/10
32/60000 [..............................] - ETA: 1s - loss: 0.2911 - accuracy: 0.9375
2144/60000 [>.............................] - ETA: 1s - loss: 0.2324 - accuracy: 0.9165
4288/60000 [=>............................] - ETA: 1s - loss: 0.2474 - accuracy: 0.9097
6368/60000 [==>...........................] - ETA: 1s - loss: 0.2515 - accuracy: 0.9081
8480/60000 [===>..........................] - ETA: 1s - loss: 0.2529 - accuracy: 0.9079
10528/60000 [====>.........................] - ETA: 1s - loss: 0.2516 - accuracy: 0.9077
12640/60000 [=====>........................] - ETA: 1s - loss: 0.2451 - accuracy: 0.9089
14720/60000 [======>.......................] - ETA: 1s - loss: 0.2465 - accuracy: 0.9077
16832/60000 [=======>......................] - ETA: 1s - loss: 0.2464 - accuracy: 0.9079
18976/60000 [========>.....................] - ETA: 0s - loss: 0.2476 - accuracy: 0.9080
21120/60000 [=========>....................] - ETA: 0s - loss: 0.2521 - accuracy: 0.9059
23264/60000 [==========>...................] - ETA: 0s - loss: 0.2541 - accuracy: 0.9053
25408/60000 [===========>..................] - ETA: 0s - loss: 0.2538 - accuracy: 0.9057
27584/60000 [============>.................] - ETA: 0s - loss: 0.2535 - accuracy: 0.9058
29632/60000 [=============>................] - ETA: 0s - loss: 0.2547 - accuracy: 0.9055
31712/60000 [==============>...............] - ETA: 0s - loss: 0.2538 - accuracy: 0.9060
33824/60000 [===============>..............] - ETA: 0s - loss: 0.2548 - accuracy: 0.9059
35936/60000 [================>.............] - ETA: 0s - loss: 0.2560 - accuracy: 0.9052
38048/60000 [==================>...........] - ETA: 0s - loss: 0.2565 - accuracy: 0.9050
40160/60000 [===================>..........] - ETA: 0s - loss: 0.2568 - accuracy: 0.9052
42240/60000 [====================>.........] - ETA: 0s - loss: 0.2567 - accuracy: 0.9051
44416/60000 [=====================>........] - ETA: 0s - loss: 0.2550 - accuracy: 0.9058
46560/60000 [======================>.......] - ETA: 0s - loss: 0.2552 - accuracy: 0.9057
48672/60000 [=======================>......] - ETA: 0s - loss: 0.2555 - accuracy: 0.9057
50784/60000 [========================>.....] - ETA: 0s - loss: 0.2556 - accuracy: 0.9053
52960/60000 [=========================>....] - ETA: 0s - loss: 0.2557 - accuracy: 0.9055
55040/60000 [==========================>...] - ETA: 0s - loss: 0.2563 - accuracy: 0.9054
57216/60000 [===========================>..] - ETA: 0s - loss: 0.2562 - accuracy: 0.9054
59360/60000 [============================>.] - ETA: 0s - loss: 0.2560 - accuracy: 0.9056
60000/60000 [==============================] - 1s 24us/sample - loss: 0.2560 - accuracy: 0.9054
Epoch 9/10
32/60000 [..............................] - ETA: 1s - loss: 0.2425 - accuracy: 0.9062
2144/60000 [>.............................] - ETA: 1s - loss: 0.2481 - accuracy: 0.9095
4256/60000 [=>............................] - ETA: 1s - loss: 0.2460 - accuracy: 0.9117
6368/60000 [==>...........................] - ETA: 1s - loss: 0.2443 - accuracy: 0.9117
8544/60000 [===>..........................] - ETA: 1s - loss: 0.2488 - accuracy: 0.9099
10688/60000 [====>.........................] - ETA: 1s - loss: 0.2492 - accuracy: 0.9103
12800/60000 [=====>........................] - ETA: 1s - loss: 0.2468 - accuracy: 0.9109
14912/60000 [======>.......................] - ETA: 1s - loss: 0.2456 - accuracy: 0.9108
17056/60000 [=======>......................] - ETA: 1s - loss: 0.2484 - accuracy: 0.9094
19168/60000 [========>.....................] - ETA: 0s - loss: 0.2495 - accuracy: 0.9079
21312/60000 [=========>....................] - ETA: 0s - loss: 0.2497 - accuracy: 0.9077
23360/60000 [==========>...................] - ETA: 0s - loss: 0.2484 - accuracy: 0.9078
25504/60000 [===========>..................] - ETA: 0s - loss: 0.2512 - accuracy: 0.9071
27616/60000 [============>.................] - ETA: 0s - loss: 0.2489 - accuracy: 0.9081
29792/60000 [=============>................] - ETA: 0s - loss: 0.2473 - accuracy: 0.9086
31840/60000 [==============>...............] - ETA: 0s - loss: 0.2465 - accuracy: 0.9088
33984/60000 [===============>..............] - ETA: 0s - loss: 0.2463 - accuracy: 0.9089
36096/60000 [=================>............] - ETA: 0s - loss: 0.2463 - accuracy: 0.9087
38240/60000 [==================>...........] - ETA: 0s - loss: 0.2452 - accuracy: 0.9089
40384/60000 [===================>..........] - ETA: 0s - loss: 0.2463 - accuracy: 0.9084
42368/60000 [====================>.........] - ETA: 0s - loss: 0.2469 - accuracy: 0.9079
44352/60000 [=====================>........] - ETA: 0s - loss: 0.2465 - accuracy: 0.9076
46272/60000 [======================>.......] - ETA: 0s - loss: 0.2460 - accuracy: 0.9079
48192/60000 [=======================>......] - ETA: 0s - loss: 0.2458 - accuracy: 0.9080
50112/60000 [========================>.....] - ETA: 0s - loss: 0.2470 - accuracy: 0.9073
52096/60000 [=========================>....] - ETA: 0s - loss: 0.2466 - accuracy: 0.9075
54112/60000 [==========================>...] - ETA: 0s - loss: 0.2457 - accuracy: 0.9080
56192/60000 [===========================>..] - ETA: 0s - loss: 0.2457 - accuracy: 0.9081
58176/60000 [============================>.] - ETA: 0s - loss: 0.2461 - accuracy: 0.9078
60000/60000 [==============================] - 1s 24us/sample - loss: 0.2463 - accuracy: 0.9077
Epoch 10/10
32/60000 [..............................] - ETA: 1s - loss: 0.2127 - accuracy: 0.9375
1984/60000 [..............................] - ETA: 1s - loss: 0.2267 - accuracy: 0.9133
4032/60000 [=>............................] - ETA: 1s - loss: 0.2326 - accuracy: 0.9110
6112/60000 [==>...........................] - ETA: 1s - loss: 0.2386 - accuracy: 0.9098
8160/60000 [===>..........................] - ETA: 1s - loss: 0.2347 - accuracy: 0.9130
10208/60000 [====>.........................] - ETA: 1s - loss: 0.2380 - accuracy: 0.9103
12256/60000 [=====>........................] - ETA: 1s - loss: 0.2388 - accuracy: 0.9092
14304/60000 [======>.......................] - ETA: 1s - loss: 0.2362 - accuracy: 0.9100
16384/60000 [=======>......................] - ETA: 1s - loss: 0.2358 - accuracy: 0.9104
18464/60000 [========>.....................] - ETA: 1s - loss: 0.2386 - accuracy: 0.9097
20544/60000 [=========>....................] - ETA: 0s - loss: 0.2411 - accuracy: 0.9090
22656/60000 [==========>...................] - ETA: 0s - loss: 0.2418 - accuracy: 0.9092
24800/60000 [===========>..................] - ETA: 0s - loss: 0.2407 - accuracy: 0.9092
26816/60000 [============>.................] - ETA: 0s - loss: 0.2398 - accuracy: 0.9094
28864/60000 [=============>................] - ETA: 0s - loss: 0.2404 - accuracy: 0.9091
30848/60000 [==============>...............] - ETA: 0s - loss: 0.2400 - accuracy: 0.9093
32960/60000 [===============>..............] - ETA: 0s - loss: 0.2402 - accuracy: 0.9093
35072/60000 [================>.............] - ETA: 0s - loss: 0.2394 - accuracy: 0.9097
37056/60000 [=================>............] - ETA: 0s - loss: 0.2397 - accuracy: 0.9097
39008/60000 [==================>...........] - ETA: 0s - loss: 0.2393 - accuracy: 0.9099
41120/60000 [===================>..........] - ETA: 0s - loss: 0.2399 - accuracy: 0.9095
43200/60000 [====================>.........] - ETA: 0s - loss: 0.2394 - accuracy: 0.9101
45344/60000 [=====================>........] - ETA: 0s - loss: 0.2391 - accuracy: 0.9104
47424/60000 [======================>.......] - ETA: 0s - loss: 0.2403 - accuracy: 0.9097
49536/60000 [=======================>......] - ETA: 0s - loss: 0.2397 - accuracy: 0.9099
51648/60000 [========================>.....] - ETA: 0s - loss: 0.2405 - accuracy: 0.9096
53760/60000 [=========================>....] - ETA: 0s - loss: 0.2402 - accuracy: 0.9097
55840/60000 [==========================>...] - ETA: 0s - loss: 0.2397 - accuracy: 0.9099
57792/60000 [===========================>..] - ETA: 0s - loss: 0.2394 - accuracy: 0.9099
59776/60000 [============================>.] - ETA: 0s - loss: 0.2394 - accuracy: 0.9101
60000/60000 [==============================] - 1s 25us/sample - loss: 0.2394 - accuracy: 0.9101
32/10000 [..............................] - ETA: 12s - loss: 0.2838 - accuracy: 0.8750
2944/10000 [=======>......................] - ETA: 0s - loss: 0.3345 - accuracy: 0.8815
6144/10000 [=================>............] - ETA: 0s - loss: 0.3683 - accuracy: 0.8734
9248/10000 [==========================>...] - ETA: 0s - loss: 0.3605 - accuracy: 0.8746
10000/10000 [==============================] - 0s 20us/sample - loss: 0.3568 - accuracy: 0.8757
0.8757
Traceback (most recent call last):
File "F:/vscode-python-kiton/数学/TensorFlow/zijiancpugpu-vs.py", line 63, in <module>
from sklearn.metrics import accuracy_score
File "D:\ruanjian\anaconda202002\lib\site-packages\sklearn\__init__.py", line 82, in <module>
from .base import clone
File "D:\ruanjian\anaconda202002\lib\site-packages\sklearn\base.py", line 20, in <module>
from .utils import _IS_32BIT
File "D:\ruanjian\anaconda202002\lib\site-packages\sklearn\utils\__init__.py", line 27, in <module>
from .fixes import np_version
File "D:\ruanjian\anaconda202002\lib\site-packages\sklearn\utils\fixes.py", line 18, in <module>
import scipy.stats
File "D:\ruanjian\anaconda202002\lib\site-packages\scipy\stats\__init__.py", line 384, in <module>
from .stats import *
File "D:\ruanjian\anaconda202002\lib\site-packages\scipy\stats\stats.py", line 179, in <module>
from scipy.spatial.distance import cdist
File "D:\ruanjian\anaconda202002\lib\site-packages\scipy\spatial\__init__.py", line 99, in <module>
from .qhull import *
ImportError: DLL load failed: 找不到指定的模块。
Process finished with exit code 1
代码如下：
#机器学习神经网络
# here put the import lib
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '-1' #不用GPU 使用CPU
import tensorflow as tf
from tensorflow import keras
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
mnist = keras.datasets.fashion_mnist
(X_train, y_train),(X_test,y_test) = mnist.load_data()
print("训练数据形状，" , X_train.shape)
print("数据最大值 " , np.max(X_train))
print("查看标签数值 " , y_train)
class_names =['top','trouser','pullover','dress','coat','sandal','shirt','sneaker','bag','ankle boot']#定义10个类别的名称
plt.figure()#可视化
plt.imshow(X_train[1])#【】里面的数据可以自己输入随便一个画出第几个的图
plt.colorbar()#加一个颜色条
plt.show()
#将数据集归一化 即降低数据集的值
X_train = X_train/255.0
X_test = X_test/255.0
plt.figure()#可视化
plt.imshow(X_train[1])#【】里面的数据可以自己输入随便一个画出第几个的图
plt.colorbar()#加一个颜色条
plt.show()
#可以看出值被缩放到0到1之间
from tensorflow.python.keras.models import Sequential #导入训练模型
from tensorflow.python.keras.layers import Flatten,Dense#导入神经网络的第一层和第二层
model = Sequential()
model.add(Flatten(input_shape = (28,28)))#此行代码是将图的大小数据转换成一维的数据
model.add(Dense(128,activation = 'relu'))#定义第一层神经网络有128个单元，并且选择的激活函数是ReLu函数，也可以是其他函数性sigmoid函数
# 这里要是不懂可以查看吴恩达老师深度学习的3.6节课
model.add(Dense(10,activation = 'softmax'))#定义输出层，有10类所以输出10，激活函数是max函数
print("查看自己写的代码的总体参数 " , model.summary())#查看自己写的代码的总体参数
#模型补充
model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',metrics=['accuracy'])#定义损失函数
#使用的优化器名叫AdamOptimizer，使用的损失函数是稀疏分类交叉熵
model.fit(X_train,y_train,epochs = 10)#进行训练，epochs是显示运行多少次
test_loss, test_acc = model.evaluate(X_test,y_test)#利用测试集测试训练下的模型的准确度
print(test_acc)
#预测模型精确度
from sklearn.metrics import accuracy_score
y_pred = model.predict_classes(X_test)
print(accuracy_score(y_test, y_pred))
#print(tf.test.is_gpu_available())
网友评论