/simplenet

simple neural network demo

Primary LanguagePython

#目的 为了理解深度学习框架的大致机理

  0%|          | 0/60000 [00:00<?, ?it/s][6, 6, 6, 6, 6, 6, 6, 6, 6, 6] [4, 8, 8, 3, 7, 9, 3, 3, 1, 7]
accuracy  0.0
  2%|▏         | 990/60000 [00:02<02:23, 410.07it/s][4, 0, 3, 7, 7, 0, 2, 1, 8, 4] [9, 0, 8, 8, 5, 5, 2, 1, 8, 4]
accuracy  0.5
  3%|▎         | 1992/60000 [00:04<02:22, 406.00it/s][6, 1, 1, 8, 7, 0, 4, 3, 3, 9] [6, 1, 1, 8, 7, 0, 9, 5, 5, 8]
accuracy  0.6
  5%|▍         | 2984/60000 [00:07<02:40, 355.51it/s][4, 8, 2, 2, 7, 2, 8, 4, 9, 8] [4, 8, 2, 2, 7, 2, 8, 9, 9, 8]
accuracy  0.9
  7%|▋         | 3976/60000 [00:10<02:17, 408.80it/s][4, 8, 7, 3, 3, 8, 2, 3, 8, 6] [4, 8, 8, 3, 3, 8, 2, 5, 9, 6]
accuracy  0.7
  8%|▊         | 4994/60000 [00:13<02:51, 321.01it/s][6, 9, 5, 7, 2, 4, 5, 6, 0, 3] [6, 9, 5, 7, 2, 4, 5, 6, 0, 3]
accuracy  1.0
 10%|█         | 6000/60000 [00:15<02:25, 372.24it/s][3, 6, 7, 7, 6, 0, 1, 2, 4, 3] [3, 6, 7, 7, 6, 0, 1, 2, 4, 3]
accuracy  1.0
 12%|█▏        | 6988/60000 [00:18<04:07, 214.20it/s][0, 9, 5, 8, 6, 2, 1, 5, 6, 8] [0, 7, 5, 8, 6, 2, 1, 5, 6, 8]
accuracy  0.9
 13%|█▎        | 7977/60000 [00:21<02:07, 407.82it/s][8, 2, 9, 6, 4, 7, 9, 7, 5, 0] [2, 2, 9, 6, 9, 7, 9, 7, 3, 0]
accuracy  0.7
 15%|█▍        | 8995/60000 [00:24<02:05, 407.40it/s][2, 8, 5, 5, 1, 4, 6, 8, 4, 1] [2, 8, 5, 5, 1, 4, 6, 8, 4, 1]
accuracy  1.0
 17%|█▋        | 9986/60000 [00:26<02:19, 357.46it/s][9, 8, 0, 6, 4, 5, 9, 1, 3, 3] [9, 3, 0, 6, 4, 5, 9, 1, 3, 3]
accuracy  0.9
 18%|█▊        | 10970/60000 [00:29<02:10, 376.03it/s][9, 8, 2, 7, 1, 2, 8, 6, 6, 0] [9, 8, 2, 7, 1, 2, 8, 6, 6, 0]
accuracy  1.0
 20%|█▉        | 11971/60000 [00:32<02:35, 308.63it/s][7, 7, 7, 6, 3, 6, 9, 4, 4, 2] [7, 7, 7, 6, 3, 6, 9, 4, 4, 2]
accuracy  1.0
 22%|██▏       | 12984/60000 [00:35<01:59, 394.82it/s][1, 1, 0, 3, 6, 1, 3, 6, 9, 7] [1, 1, 0, 3, 6, 1, 3, 6, 9, 7]
accuracy  1.0
 23%|██▎       | 13964/60000 [00:38<02:13, 343.94it/s][3, 8, 7, 1, 7, 8, 7, 6, 1, 0] [3, 9, 7, 1, 7, 8, 7, 6, 1, 0]
accuracy  0.9
 25%|██▍       | 14973/60000 [00:42<02:28, 302.32it/s][4, 6, 1, 2, 0, 2, 9, 6, 1, 6] [4, 6, 1, 2, 0, 2, 9, 8, 1, 6]
accuracy  0.9
 27%|██▋       | 15989/60000 [00:45<01:55, 380.75it/s][8, 4, 0, 3, 9, 1, 9, 1, 0, 3] [8, 4, 0, 3, 9, 1, 9, 1, 0, 3]
accuracy  1.0
 28%|██▊       | 17002/60000 [00:48<01:50, 389.91it/s][1, 6, 4, 0, 7, 1, 1, 5, 8, 2] [1, 6, 8, 0, 7, 1, 1, 5, 8, 2]
accuracy  0.9
 30%|██▉       | 17963/60000 [00:50<01:46, 396.38it/s][3, 0, 8, 6, 9, 7, 8, 6, 8, 1] [3, 0, 8, 6, 9, 3, 8, 6, 8, 1]
accuracy  0.9
 32%|███▏      | 18979/60000 [00:53<01:40, 408.38it/s][5, 6, 7, 3, 4, 3, 5, 2, 2, 9] [5, 6, 5, 3, 4, 3, 5, 2, 2, 9]
accuracy  0.9
 33%|███▎      | 19987/60000 [00:55<01:42, 391.43it/s][5, 5, 8, 7, 2, 9, 6, 4, 7, 9] [5, 5, 8, 7, 2, 9, 3, 4, 7, 9]
accuracy  0.9
 35%|███▍      | 20997/60000 [00:58<01:42, 381.69it/s][5, 9, 3, 5, 5, 9, 3, 1, 3, 0] [5, 4, 3, 5, 5, 9, 3, 1, 3, 0]
accuracy  0.9
 37%|███▋      | 22000/60000 [01:01<01:50, 344.17it/s][4, 3, 1, 9, 7, 2, 9, 8, 2, 2] [4, 3, 1, 9, 7, 2, 9, 8, 2, 3]
accuracy  0.9
 38%|███▊      | 22999/60000 [01:03<01:33, 397.68it/s][4, 2, 5, 5, 4, 0, 2, 4, 6, 1] [4, 2, 5, 5, 4, 0, 2, 4, 6, 1]
accuracy  1.0
 40%|███▉      | 23977/60000 [01:06<01:48, 330.62it/s][2, 2, 6, 0, 2, 4, 4, 9, 1, 2] [2, 3, 6, 0, 2, 4, 4, 9, 1, 2]
accuracy  0.9
 42%|████▏     | 25002/60000 [01:09<01:34, 370.64it/s][8, 1, 8, 1, 2, 4, 1, 2, 2, 3] [8, 7, 8, 7, 2, 4, 1, 2, 2, 3]
accuracy  0.8
 43%|████▎     | 25972/60000 [01:11<01:32, 365.93it/s][2, 4, 5, 3, 0, 6, 8, 9, 2, 5] [2, 4, 5, 3, 0, 6, 8, 9, 2, 5]
accuracy  1.0
 45%|████▍     | 26967/60000 [01:14<01:24, 391.63it/s][2, 1, 3, 7, 5, 8, 1, 3, 4, 5] [2, 1, 3, 7, 5, 8, 1, 3, 4, 5]
accuracy  1.0
 47%|████▋     | 27994/60000 [01:17<01:26, 368.13it/s][8, 1, 3, 1, 0, 7, 6, 8, 1, 3] [8, 1, 3, 1, 0, 7, 6, 8, 1, 3]
accuracy  1.0
 48%|████▊     | 28982/60000 [01:19<01:18, 395.21it/s][9, 9, 9, 8, 3, 3, 0, 3, 4, 2] [9, 9, 9, 8, 3, 3, 0, 3, 4, 2]
accuracy  1.0
 50%|████▉     | 29982/60000 [01:22<01:13, 407.43it/s][5, 8, 2, 2, 7, 6, 0, 7, 2, 0] [5, 8, 2, 2, 4, 2, 0, 7, 3, 0]
accuracy  0.7
 52%|█████▏    | 30967/60000 [01:24<01:11, 404.29it/s][1, 6, 7, 4, 5, 7, 8, 3, 8, 6] [1, 6, 3, 4, 5, 7, 8, 9, 9, 6]
accuracy  0.7
 53%|█████▎    | 31998/60000 [01:27<01:29, 313.45it/s][1, 3, 3, 5, 9, 1, 0, 1, 9, 6] [1, 3, 3, 5, 9, 1, 0, 1, 4, 6]
accuracy  0.9
 55%|█████▍    | 32975/60000 [01:30<01:21, 331.36it/s][7, 0, 3, 0, 5, 3, 2, 7, 4, 0] [7, 0, 3, 0, 5, 3, 2, 7, 4, 0]
accuracy  1.0
 57%|█████▋    | 33976/60000 [01:33<01:04, 404.15it/s][4, 3, 5, 6, 2, 5, 9, 7, 6, 2] [4, 3, 5, 6, 2, 5, 9, 7, 6, 2]
accuracy  1.0
 58%|█████▊    | 34994/60000 [01:36<01:03, 394.39it/s][1, 5, 2, 4, 6, 8, 2, 8, 9, 1] [1, 5, 2, 4, 6, 8, 2, 8, 9, 1]
accuracy  1.0
 60%|█████▉    | 35965/60000 [01:38<00:58, 413.51it/s][9, 4, 6, 0, 6, 6, 8, 9, 0, 5] [9, 4, 6, 0, 6, 6, 8, 9, 0, 5]
accuracy  1.0
 62%|██████▏   | 36971/60000 [01:41<00:56, 411.12it/s][8, 1, 3, 4, 7, 4, 1, 7, 1, 2] [8, 1, 3, 4, 7, 4, 1, 7, 1, 2]
accuracy  1.0
 63%|██████▎   | 37983/60000 [01:43<00:53, 414.43it/s][9, 7, 9, 7, 3, 4, 0, 4, 2, 4] [9, 7, 9, 5, 3, 9, 5, 4, 2, 4]
accuracy  0.7
 65%|██████▍   | 38988/60000 [01:46<00:51, 408.07it/s][7, 6, 9, 7, 9, 8, 1, 8, 8, 4] [7, 6, 9, 7, 9, 8, 4, 8, 8, 4]
accuracy  0.9
 67%|██████▋   | 39998/60000 [01:48<00:49, 402.56it/s][8, 3, 0, 3, 0, 8, 8, 9, 4, 4] [8, 3, 0, 3, 0, 8, 9, 9, 4, 4]
accuracy  0.9
 68%|██████▊   | 40969/60000 [01:50<00:46, 410.06it/s][8, 9, 7, 0, 3, 5, 2, 0, 8, 9] [8, 9, 7, 0, 3, 5, 2, 0, 8, 9]
accuracy  1.0
 70%|██████▉   | 41971/60000 [01:53<00:45, 396.20it/s][2, 8, 3, 1, 8, 8, 5, 8, 0, 5] [2, 8, 3, 1, 8, 8, 5, 8, 0, 5]
accuracy  1.0
 72%|███████▏  | 42967/60000 [01:56<00:46, 364.62it/s][1, 6, 3, 2, 1, 5, 3, 7, 1, 6] [1, 6, 3, 2, 1, 5, 3, 7, 6, 6]
accuracy  0.9
 73%|███████▎  | 43993/60000 [01:59<00:40, 397.78it/s][4, 4, 8, 2, 2, 2, 6, 2, 7, 2] [4, 4, 8, 2, 2, 2, 6, 2, 7, 2]
accuracy  1.0
 75%|███████▍  | 44968/60000 [02:01<00:37, 397.40it/s][9, 0, 7, 5, 3, 3, 5, 3, 2, 5] [9, 0, 7, 5, 2, 3, 5, 3, 2, 5]
accuracy  0.9
 77%|███████▋  | 45974/60000 [02:03<00:34, 406.30it/s][7, 6, 5, 8, 2, 8, 5, 9, 1, 2] [7, 6, 5, 8, 2, 8, 5, 9, 1, 2]
accuracy  1.0
 78%|███████▊  | 46996/60000 [02:06<00:30, 423.69it/s][8, 0, 9, 3, 1, 3, 7, 0, 6, 0] [8, 5, 9, 3, 1, 3, 7, 0, 6, 0]
accuracy  0.9
 80%|███████▉  | 47989/60000 [02:08<00:35, 339.53it/s][0, 2, 3, 3, 0, 2, 9, 8, 3, 5] [0, 2, 3, 3, 0, 2, 9, 8, 3, 5]
accuracy  1.0
 82%|████████▏ | 48965/60000 [02:11<00:26, 412.72it/s][7, 4, 1, 8, 4, 3, 1, 5, 6, 5] [7, 4, 1, 8, 4, 3, 1, 5, 6, 5]
accuracy  1.0
 83%|████████▎ | 49964/60000 [02:14<00:25, 388.64it/s][2, 1, 9, 2, 5, 1, 3, 1, 3, 0] [2, 1, 9, 2, 5, 1, 3, 1, 3, 0]
accuracy  1.0
 85%|████████▍ | 50963/60000 [02:16<00:24, 368.21it/s][8, 8, 4, 4, 6, 1, 2, 9, 9, 7] [8, 8, 4, 4, 6, 1, 2, 9, 9, 7]
accuracy  1.0
 87%|████████▋ | 51977/60000 [02:19<00:24, 330.60it/s][1, 1, 0, 3, 0, 7, 4, 0, 5, 6] [1, 1, 2, 3, 0, 7, 4, 0, 5, 6]
accuracy  0.9
 88%|████████▊ | 52990/60000 [02:22<00:18, 386.90it/s][1, 1, 3, 7, 6, 2, 1, 6, 1, 1] [1, 1, 3, 7, 6, 2, 1, 6, 1, 1]
accuracy  1.0
 90%|████████▉ | 53986/60000 [02:24<00:15, 378.51it/s][2, 2, 6, 6, 5, 9, 4, 7, 9, 5] [2, 4, 6, 6, 5, 9, 4, 7, 9, 5]
accuracy  0.9
 92%|█████████▏| 54985/60000 [02:27<00:13, 385.55it/s][4, 9, 9, 8, 9, 4, 1, 1, 0, 6] [4, 9, 9, 8, 9, 4, 1, 1, 0, 6]
accuracy  1.0
 93%|█████████▎| 55987/60000 [02:30<00:11, 349.07it/s][6, 1, 2, 8, 9, 4, 0, 3, 0, 5] [6, 1, 2, 8, 9, 4, 0, 3, 0, 5]
accuracy  1.0
 95%|█████████▍| 56985/60000 [02:33<00:08, 342.22it/s][3, 4, 1, 6, 7, 3, 0, 7, 1, 0] [3, 4, 1, 6, 7, 3, 0, 7, 1, 0]
accuracy  1.0
 97%|█████████▋| 57982/60000 [02:36<00:05, 388.39it/s][2, 1, 3, 1, 1, 9, 1, 2, 2, 3] [2, 1, 2, 1, 1, 9, 1, 2, 2, 3]
accuracy  0.9
 98%|█████████▊| 58974/60000 [02:39<00:02, 385.45it/s][1, 9, 9, 3, 4, 0, 4, 7, 1, 1] [1, 9, 5, 3, 4, 0, 4, 7, 1, 1]
accuracy  0.9
100%|██████████| 60000/60000 [02:42<00:00, 370.12it/s]