IF YOU WOULD LIKE TO GET AN ACCOUNT, please write an email to s dot adaszewski at gmail dot com. User accounts are meant only to report issues and/or generate pull requests. This is a purpose-specific Git hosting for ADARED projects. Thank you for your understanding!
Nevar pievienot vairāk kā 25 tēmas Tēmai ir jāsākas ar burtu vai ciparu, tā var saturēt domu zīmes ('-') un var būt līdz 35 simboliem gara.

87 rindas
2.4KB

  1. from icosagon.decode import DEDICOMDecoder, \
  2. DistMultDecoder, \
  3. BilinearDecoder, \
  4. InnerProductDecoder
  5. import decagon_pytorch.decode.pairwise
  6. import torch
  7. def test_dedicom_decoder_01():
  8. repr_ = torch.rand(20, 32)
  9. dec_1 = DEDICOMDecoder(32, 7, keep_prob=1.,
  10. activation=torch.sigmoid)
  11. dec_2 = decagon_pytorch.decode.pairwise.DEDICOMDecoder(32, 7, drop_prob=0.,
  12. activation=torch.sigmoid)
  13. dec_2.global_interaction = dec_1.global_interaction
  14. dec_2.local_variation = dec_1.local_variation
  15. res_1 = dec_1(repr_, repr_)
  16. res_2 = dec_2(repr_, repr_)
  17. assert isinstance(res_1, list)
  18. assert isinstance(res_2, list)
  19. assert len(res_1) == len(res_2)
  20. for i in range(len(res_1)):
  21. assert torch.all(res_1[i] == res_2[i])
  22. def test_dist_mult_decoder_01():
  23. repr_ = torch.rand(20, 32)
  24. dec_1 = DistMultDecoder(32, 7, keep_prob=1.,
  25. activation=torch.sigmoid)
  26. dec_2 = decagon_pytorch.decode.pairwise.DistMultDecoder(32, 7, drop_prob=0.,
  27. activation=torch.sigmoid)
  28. dec_2.relation = dec_1.relation
  29. res_1 = dec_1(repr_, repr_)
  30. res_2 = dec_2(repr_, repr_)
  31. assert isinstance(res_1, list)
  32. assert isinstance(res_2, list)
  33. assert len(res_1) == len(res_2)
  34. for i in range(len(res_1)):
  35. assert torch.all(res_1[i] == res_2[i])
  36. def test_bilinear_decoder_01():
  37. repr_ = torch.rand(20, 32)
  38. dec_1 = BilinearDecoder(32, 7, keep_prob=1.,
  39. activation=torch.sigmoid)
  40. dec_2 = decagon_pytorch.decode.pairwise.BilinearDecoder(32, 7, drop_prob=0.,
  41. activation=torch.sigmoid)
  42. dec_2.relation = dec_1.relation
  43. res_1 = dec_1(repr_, repr_)
  44. res_2 = dec_2(repr_, repr_)
  45. assert isinstance(res_1, list)
  46. assert isinstance(res_2, list)
  47. assert len(res_1) == len(res_2)
  48. for i in range(len(res_1)):
  49. assert torch.all(res_1[i] == res_2[i])
  50. def test_inner_product_decoder_01():
  51. repr_ = torch.rand(20, 32)
  52. dec_1 = InnerProductDecoder(32, 7, keep_prob=1.,
  53. activation=torch.sigmoid)
  54. dec_2 = decagon_pytorch.decode.pairwise.InnerProductDecoder(32, 7, drop_prob=0.,
  55. activation=torch.sigmoid)
  56. res_1 = dec_1(repr_, repr_)
  57. res_2 = dec_2(repr_, repr_)
  58. assert isinstance(res_1, list)
  59. assert isinstance(res_2, list)
  60. assert len(res_1) == len(res_2)
  61. for i in range(len(res_1)):
  62. assert torch.all(res_1[i] == res_2[i])