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  1. dataset_5/train_2837_a_2.npy +3 -0
  2. dataset_5/train_2844_a_2.npy +3 -0
  3. dataset_5/train_2873_a_2.npy +3 -0
  4. dataset_5/train_2878_a_2.npy +3 -0
  5. dataset_5/train_2888_a_2.npy +3 -0
  6. dataset_5/train_288_a_2.npy +3 -0
  7. dataset_5/train_2912_a_2.npy +3 -0
  8. dataset_5/train_2946_a_2.npy +3 -0
  9. dataset_5/train_2977_a_2.npy +3 -0
  10. dataset_5/train_3048_a_2.npy +3 -0
  11. dataset_5/train_3054_a_2.npy +3 -0
  12. dataset_5/train_3100_a_2.npy +3 -0
  13. dataset_5/train_3101_a_2.npy +3 -0
  14. dataset_5/train_3112_a_2.npy +3 -0
  15. dataset_5/train_3114_a_2.npy +3 -0
  16. dataset_5/train_3122_a_2.npy +3 -0
  17. dataset_5/train_3123_a_2.npy +3 -0
  18. dataset_5/train_3151_a_2.npy +3 -0
  19. dataset_5/train_3152_a_2.npy +3 -0
  20. dataset_5/train_3154_a_2.npy +3 -0
  21. dataset_5/train_3173_a_2.npy +3 -0
  22. dataset_5/train_3204_a_2.npy +3 -0
  23. dataset_5/train_3221_a_2.npy +3 -0
  24. dataset_5/train_3247_a_2.npy +3 -0
  25. dataset_5/train_3260_b_2.npy +3 -0
  26. dataset_5/train_3295_a_2.npy +3 -0
  27. dataset_5/train_3305_a_2.npy +3 -0
  28. dataset_5/train_3319_a_2.npy +3 -0
  29. dataset_5/train_3327_a_2.npy +3 -0
  30. dataset_5/train_3361_a_2.npy +3 -0
  31. dataset_5/train_3405_a_2.npy +3 -0
  32. dataset_5/train_3440_a_2.npy +3 -0
  33. dataset_5/train_3441_a_2.npy +3 -0
  34. dataset_5/train_347_a_2.npy +3 -0
  35. dataset_5/train_3493_a_2.npy +3 -0
  36. dataset_5/train_3603_a_2.npy +3 -0
  37. dataset_5/train_3615_a_2.npy +3 -0
  38. dataset_5/train_3636_a_2.npy +3 -0
  39. dataset_5/train_3702_a_2.npy +3 -0
  40. dataset_5/train_3712_a_2.npy +3 -0
  41. dataset_5/train_3746_a_2.npy +3 -0
  42. dataset_5/train_3751_b_2.npy +3 -0
  43. dataset_5/train_3773_a_2.npy +3 -0
  44. dataset_5/train_3773_b_2.npy +3 -0
  45. dataset_5/train_3780_a_2.npy +3 -0
  46. dataset_5/train_3841_a_2.npy +3 -0
  47. dataset_5/train_3850_a_2.npy +3 -0
  48. dataset_5/train_3957_a_2.npy +3 -0
  49. dataset_5/train_3962_a_2.npy +3 -0
  50. dataset_5/train_4009_a_2.npy +3 -0
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