Part of the gradient is 0 during training of heterogeneous graphs

hi,Thanks for your work about DGL ! but i ran into some problems.

According to the api documentation, i implemented HGT. the detail of model is that.

  1. heterograph graph info:
    G = dgl.heterograph({ ('u', 'ur', 'r'): sp_u_r.nonzero(), ('r', 'ru', 'u'): sp_u_r.transpose().nonzero(), ('u', 'um', 'm'): sp_u_m.nonzero(), ('m', 'm', 'u'): sp_u_m.transpose().nonzero(), ('m', 'mr', 'r'): sp_m_r.nonzero(), ('r', 'rm', 'm'): sp_m_r.transpose().nonzero() })
  2. dataset. only ‘u’ has label in dataset.

train result:
relation_msg grad size [6, 4, 24, 24]
6 - edge type num
4 - head num
24 - feature dim
edge type num: [mr, mu, rm, ru, um, ur]

relation_msg grad in train process, just 2th dimension and 4th dimension grad is not zero. for instance:
name: gcs.0.relation_msg -->grad_requirs: True -->grad_value: tensor(
[
[[[ 0.0000e+00, 0.0000e+00, 0.0000e+00, …, 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 0.0000e+00, 0.0000e+00, 0.0000e+00, …, 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 0.0000e+00, 0.0000e+00, 0.0000e+00, …, 0.0000e+00,
0.0000e+00, 0.0000e+00],
…,
[ 0.0000e+00, 0.0000e+00, 0.0000e+00, …, 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 0.0000e+00, 0.0000e+00, 0.0000e+00, …, 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 0.0000e+00, 0.0000e+00, 0.0000e+00, …, 0.0000e+00,
0.0000e+00, 0.0000e+00]],

     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]],

     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]],

     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]]],


    [[[ 2.9386e-04,  2.2033e-04, -2.4458e-04,  ...,  9.8247e-05,
       -1.4378e-04,  1.2705e-04],
      [ 1.3501e-03,  1.0100e-03, -1.1088e-03,  ...,  4.5461e-04,
       -6.5970e-04,  5.8132e-04],
      [ 2.0886e-03,  1.5605e-03, -1.7097e-03,  ...,  7.0432e-04,
       -1.0205e-03,  9.0017e-04],
      ...,
      [ 1.4620e-03,  1.0940e-03, -1.2027e-03,  ...,  4.9121e-04,
       -7.1416e-04,  6.2982e-04],
      [ 1.2358e-03,  9.2436e-04, -1.0109e-03,  ...,  4.1608e-04,
       -6.0343e-04,  5.3248e-04],
      [ 1.9848e-03,  1.4838e-03, -1.6264e-03,  ...,  6.6959e-04,
       -9.7017e-04,  8.5566e-04]],

     [[-8.2373e-05,  6.9665e-04, -7.8943e-04,  ..., -9.9184e-04,
       -8.5768e-04, -5.0241e-04],
      [ 6.2685e-05, -5.3908e-04,  6.1362e-04,  ...,  7.6563e-04,
        6.6452e-04,  3.8612e-04],
      [ 1.6938e-04, -1.4696e-03,  1.6682e-03,  ...,  2.0844e-03,
        1.8082e-03,  1.0503e-03],
      ...,
      [-4.2399e-05,  3.7403e-04, -4.2247e-04,  ..., -5.2755e-04,
       -4.5806e-04, -2.6692e-04],
      [-3.1590e-04,  2.7127e-03, -3.0784e-03,  ..., -3.8534e-03,
       -3.3401e-03, -1.9421e-03],
      [ 8.6191e-05, -7.4456e-04,  8.4367e-04,  ...,  1.0549e-03,
        9.1552e-04,  5.3260e-04]],

     [[-3.3853e-03, -7.7910e-04, -9.9116e-04,  ...,  2.0605e-03,
        1.2581e-04,  2.1216e-03],
      [ 5.0360e-03,  1.1598e-03,  1.4740e-03,  ..., -3.0640e-03,
       -1.8554e-04, -3.1553e-03],
      [-3.7575e-03, -8.6500e-04, -1.1004e-03,  ...,  2.2853e-03,
        1.3779e-04,  2.3543e-03],
      ...,
      [-3.0968e-03, -7.1249e-04, -9.0761e-04,  ...,  1.8843e-03,
        1.1496e-04,  1.9399e-03],
      [ 6.7404e-03,  1.5522e-03,  1.9718e-03,  ..., -4.1012e-03,
       -2.4825e-04, -4.2243e-03],
      [ 4.4206e-03,  1.0173e-03,  1.2946e-03,  ..., -2.6898e-03,
       -1.6376e-04, -2.7701e-03]],

     [[-2.7084e-04, -5.7016e-04,  7.9181e-04,  ...,  2.3430e-04,
       -9.7345e-04,  4.0422e-04],
      [ 1.2916e-04,  2.7936e-04, -3.8169e-04,  ..., -1.1295e-04,
        4.7032e-04, -1.9840e-04],
      [-2.1777e-04, -4.6421e-04,  6.4020e-04,  ...,  1.9069e-04,
       -7.9167e-04,  3.2959e-04],
      ...,
      [ 8.7625e-04,  1.8674e-03, -2.5768e-03,  ..., -7.6828e-04,
        3.1903e-03, -1.3288e-03],
      [-4.3550e-04, -9.2699e-04,  1.2819e-03,  ...,  3.8199e-04,
       -1.5857e-03,  6.5898e-04],
      [ 9.7769e-04,  2.0894e-03, -2.8764e-03,  ..., -8.5817e-04,
        3.5619e-03, -1.4868e-03]]],


    [[[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]],

     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]],

     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]],

     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]]],


    [[[-1.3555e-03, -9.4653e-04,  1.0894e-03,  ..., -4.1232e-04,
        7.5999e-04, -5.9938e-04],
      [ 1.3334e-04,  9.3594e-05, -1.0762e-04,  ...,  4.0632e-05,
       -7.4725e-05,  5.8490e-05],
      [ 2.5522e-03,  1.7783e-03, -2.0459e-03,  ...,  7.7695e-04,
       -1.4309e-03,  1.1305e-03],
      ...,
      [-1.1826e-04, -8.2046e-05,  9.4439e-05,  ..., -3.6246e-05,
        6.6307e-05, -5.2510e-05],
      [-4.0508e-03, -2.8245e-03,  3.2491e-03,  ..., -1.2340e-03,
        2.2703e-03, -1.7932e-03],
      [-2.6699e-03, -1.8621e-03,  2.1419e-03,  ..., -8.1490e-04,
        1.4942e-03, -1.1824e-03]],

     [[ 5.3411e-05, -4.6874e-04,  5.7286e-04,  ...,  6.4302e-04,
        5.8587e-04,  3.2686e-04],
      [-2.2701e-04,  2.0446e-03, -2.4975e-03,  ..., -2.7915e-03,
       -2.5481e-03, -1.4298e-03],
      [ 4.0636e-05, -3.6105e-04,  4.4095e-04,  ...,  4.9512e-04,
        4.5085e-04,  2.5157e-04],
      ...,
      [ 2.5961e-04, -2.3619e-03,  2.8803e-03,  ...,  3.2232e-03,
        2.9418e-03,  1.6484e-03],
      [-1.9141e-04,  1.7239e-03, -2.1041e-03,  ..., -2.3553e-03,
       -2.1486e-03, -1.2037e-03],
      [ 8.6319e-05, -7.6695e-04,  9.3778e-04,  ...,  1.0491e-03,
        9.5696e-04,  5.3636e-04]],

     [[ 2.3358e-04,  5.7907e-05,  6.2813e-05,  ..., -1.6143e-04,
       -1.6490e-05, -1.4886e-04],
      [ 3.6006e-03,  8.8118e-04,  9.7041e-04,  ..., -2.4452e-03,
       -2.3957e-04, -2.2937e-03],
      [ 3.0193e-03,  7.3924e-04,  8.1340e-04,  ..., -2.0492e-03,
       -2.0058e-04, -1.9236e-03],
      ...,
      [-1.3734e-03, -3.3709e-04, -3.6930e-04,  ...,  9.3263e-04,
        9.1438e-05,  8.7545e-04],
      [ 1.0176e-03,  2.5012e-04,  2.7371e-04,  ..., -6.9090e-04,
       -6.7416e-05, -6.4885e-04],
      [-6.5541e-03, -1.6063e-03, -1.7650e-03,  ...,  4.4553e-03,
        4.3775e-04,  4.1754e-03]],

     [[-3.9267e-04, -1.1961e-03,  1.5886e-03,  ...,  4.6229e-04,
       -1.8212e-03,  8.4340e-04],
      [-4.2820e-04, -1.2977e-03,  1.7215e-03,  ...,  5.0082e-04,
       -1.9752e-03,  9.1483e-04],
      [-5.2357e-04, -1.5939e-03,  2.1166e-03,  ...,  6.1677e-04,
       -2.4293e-03,  1.1246e-03],
      ...,
      [-6.3563e-05, -1.9443e-04,  2.5871e-04,  ...,  7.5632e-05,
       -2.9765e-04,  1.3712e-04],
      [ 4.8618e-04,  1.4838e-03, -1.9717e-03,  ..., -5.7422e-04,
        2.2609e-03, -1.0462e-03],
      [-1.2303e-03, -3.7457e-03,  4.9748e-03,  ...,  1.4480e-03,
       -5.7033e-03,  2.6409e-03]]],


    [[[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
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      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
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      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]],

     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
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      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
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      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
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     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
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      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
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        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]],

     [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
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      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      ...,
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00],
      [ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,
        0.0000e+00,  0.0000e+00]]],


    [[[-3.1220e-05, -4.6404e-05,  3.1248e-05,  ...,  5.0066e-05,
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        1.9659e-04, -3.4810e-05],
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        8.2193e-05, -1.4315e-05],
      ...,
      [-1.9348e-05, -2.8707e-05,  1.9180e-05,  ...,  3.3241e-05,
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      [ 5.6733e-05,  8.3884e-05, -5.6161e-05,  ..., -9.2009e-05,
       -1.4601e-04,  2.5594e-05]],

     [[-4.4039e-05,  1.0926e-05,  3.6490e-05,  ..., -1.6846e-04,
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      ...,
      [-2.5238e-05,  6.2442e-06,  2.1621e-05,  ..., -9.6925e-05,
       -1.5454e-05,  1.5560e-04],
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      [-1.8811e-05,  5.0174e-06,  1.6632e-05,  ..., -7.2993e-05,
       -1.1565e-05,  1.1569e-04]],

     [[ 8.4149e-05, -1.6170e-04, -7.5072e-05,  ...,  3.2733e-05,
       -2.2902e-05, -9.0484e-05],
      [ 1.0774e-05, -2.1308e-05, -1.0011e-05,  ...,  4.1846e-06,
       -2.9602e-06, -1.2003e-05],
      [ 1.7841e-05, -3.4936e-05, -1.6484e-05,  ...,  6.9733e-06,
       -5.2608e-06, -1.9681e-05],
      ...,
      [-7.9003e-05,  1.5205e-04,  7.0718e-05,  ..., -3.0997e-05,
        2.1533e-05,  8.5325e-05],
      [ 4.5710e-05, -8.8112e-05, -4.1279e-05,  ...,  1.7230e-05,
       -1.2703e-05, -4.9148e-05],
      [ 1.7663e-05, -3.3840e-05, -1.5419e-05,  ...,  7.3235e-06,
       -4.6384e-06, -1.9049e-05]],

     [[ 4.2401e-05,  6.3181e-05,  3.6498e-05,  ...,  3.5402e-05,
        1.4445e-06, -3.8307e-05],
      [ 1.0218e-04,  1.5459e-04,  8.8335e-05,  ...,  8.5611e-05,
        3.2342e-06, -9.4105e-05],
      [ 1.1736e-04,  1.7372e-04,  1.0084e-04,  ...,  9.7288e-05,
        4.3842e-06, -1.0596e-04],
      ...,
      [ 2.0705e-04,  2.9787e-04,  1.7667e-04,  ...,  1.6887e-04,
        9.1329e-06, -1.8247e-04],
      [-5.9878e-05, -8.9926e-05, -5.1550e-05,  ..., -4.9913e-05,
       -2.1076e-06,  5.4881e-05],
      [ 4.3078e-05,  6.3224e-05,  3.6931e-05,  ...,  3.5404e-05,
        1.8143e-06, -3.8773e-05]]]])

Would love for your help :pray:

Did you try the HGT example in dgl/examples/pytorch/hgt at master · dmlc/dgl · GitHub?

yes, but on my own data set.

and when I print out the weights, I find that many weights are 1. I guess my model is not sufficiently trained and falls to the local best. but I don’t know how to optimize further, can you give me some suggestions?

[4.65156772e-04 4.64034732e-04 1.46237365e-03 4.60746582e-04
4.12484584e-03 4.60838579e-04 4.57462389e-04 1.03430049e-02
5.27146412e-03 9.47223138e-03 5.30892611e-03 3.32993150e-01
2.06966273e-04 2.01429182e-04 2.94686370e-02 1.12884282e-03
1.33624463e-03 1.12520938e-03 9.65247164e-04 1.13830366e-03
1.00000000e+00 2.64379615e-03 3.32806796e-01 3.53627751e-04
4.86739445e-04 3.49415961e-04 4.84161836e-04 3.08122998e-03
1.97333563e-03 2.98258592e-03 2.43484299e-03 1.70504535e-03
4.38184710e-04 2.16871747e-04 2.26265445e-04 4.33415000e-04
1.36481167e-03 2.86930241e-02 6.17271464e-04 7.53842236e-04
3.12367309e-04 7.68535479e-04 4.56012727e-04 4.55585861e-04
1.45709515e-02 3.44933663e-03 4.44918434e-04 1.11108966e-01
4.88135556e-04 4.53478628e-04 4.55803471e-04 4.49333194e-04
1.67170109e-03 4.46874416e-03 2.01044633e-04 4.49484301e-04
4.55481815e-04 4.50760417e-04 3.49380018e-04 3.09582305e-04
2.49735243e-03 4.06562001e-04 2.77982443e-04 4.40607721e-04
3.26534675e-04 3.74804856e-03 4.44497797e-04 5.02581894e-02
3.60151753e-03 2.26241145e-02 3.76093271e-03 6.54198229e-03
4.01242374e-04 1.73890265e-03 1.23695820e-03 3.33557400e-04
1.49013475e-03 4.23031044e-04 2.09189835e-03 4.24366677e-04
1.81115267e-03 1.37315341e-03 1.78235874e-03 5.73679456e-04
3.62072745e-03 6.21174171e-04 5.07831238e-02 2.97325524e-03
1.24194007e-03 4.26119601e-04 1.79127418e-03 3.58328514e-04
3.85696563e-04 1.00000000e+00 8.18547967e-04 8.16640561e-04
1.30323402e-03 8.13156599e-04 2.34490610e-03 2.35748186e-04
3.85857624e-04 3.86028696e-04 2.28824392e-02 6.53873989e-03
1.27128314e-03 9.89508932e-04 3.08714429e-04 2.00789720e-01
4.03527258e-04 1.24380216e-01 1.00000000e+00 4.08504973e-04
4.04079154e-04 1.11156618e-02 4.06106206e-04 5.72388759e-04
4.06156149e-04 6.49502850e-04 4.07697400e-04 2.15696928e-04
7.61017343e-03 1.15339588e-02 4.01706202e-04 4.00600926e-04
4.05014929e-04 4.08705266e-04 1.08623097e-03 7.43891636e-04
4.02249367e-04 1.09908348e-02 4.06284438e-04 4.23095794e-03
4.06077219e-04 4.08639491e-04 9.16808203e-04 3.08619550e-04
8.85129382e-04 4.09749511e-04 4.06116160e-04 4.05518629e-04
8.17495631e-04 1.75593363e-03 4.04206221e-04 4.04239894e-04
3.09104403e-03 1.76539645e-03 5.11364080e-03 3.97153315e-04
4.00220219e-04 1.04493620e-02 7.54686212e-03 2.51456410e-01
2.46890374e-02 2.00578451e-01 4.97874826e-01 4.06239007e-04
4.07681073e-04 4.05291532e-04 4.05915518e-04 3.94738279e-03
4.04042221e-04 2.65208510e-04 4.05623752e-04 4.02836391e-04
7.31333392e-04 4.03101614e-04 2.36444612e-04 2.66577728e-04
4.03135316e-04 4.07716318e-04 4.02146718e-04 1.67784423e-01
4.08608001e-04 4.60008346e-03 3.58069758e-03 9.44305386e-04
2.82911933e-04 1.05627917e-03 8.69047176e-03 3.29175917e-03
4.52680979e-03 3.02652275e-04 3.47061170e-04 4.53886390e-03
4.54709632e-03 3.45017412e-03 4.55365703e-03 1.00000000e+00
4.49496601e-03 4.50710813e-03 4.53993306e-03 1.00000000e+00
4.57232166e-03 3.39155551e-04 2.51097441e-01 3.35781485e-01
4.61157830e-03 3.36290389e-01 4.53042286e-03 3.48288752e-03
4.52198973e-03 3.43619031e-03 4.58869711e-03 1.03305280e-02
4.57915757e-03 4.62227874e-03 3.49445525e-03 3.42691340e-03
4.54203133e-03 3.46159167e-03 2.62360624e-03 1.00000000e+00
4.51527536e-03 4.55594901e-03 4.49875416e-03 3.42884590e-03
4.56106709e-03 4.51638224e-03 4.54253796e-03 4.58674273e-03
4.45018848e-03 1.00000000e+00 4.51232865e-03 3.43141635e-03
4.52562841e-03 4.50947462e-03 2.40374982e-01 4.59522475e-03
3.49305966e-03 2.66375300e-03 4.98611450e-01 4.50468063e-03
4.59588831e-03 2.65495409e-03 1.00000000e+00 1.00000000e+00
4.57543787e-03 3.16228048e-04 4.52610990e-03 3.43744061e-03
2.62235617e-03 1.00000000e+00 1.00000000e+00 4.58535040e-03
4.53579379e-03 1.00000000e+00 4.53343103e-03 9.49638337e-03
4.19079093e-04 2.64425552e-03 1.00000000e+00 1.00000000e+00
4.56531299e-03 9.57482774e-03 4.46369639e-03 4.51760041e-03
1.99231833e-01 4.57918691e-03 1.00000000e+00 4.57617873e-03
3.48000065e-03 4.55305167e-03 3.46752419e-03 3.58054810e-03
1.43999100e-01 4.57417453e-03 3.47425416e-03 2.65287748e-03
1.00000000e+00 1.00000000e+00 4.55483561e-03 4.52759257e-03
1.00000000e+00 2.37452652e-04 4.55568265e-03 4.54371935e-03
4.55464469e-03 3.45969037e-03 4.57635149e-03 2.75917671e-04
2.91147997e-04 2.98032840e-03 4.50488413e-03 4.56833746e-03
1.00000000e+00 1.00000000e+00 4.50267410e-03 1.00000000e+00
4.55712061e-03 1.00000000e+00 4.47550556e-03 5.33018378e-04
1.00000000e+00 4.55557322e-03 4.58135922e-03 4.57763067e-03
4.46079735e-04 4.71971650e-03 4.48405277e-03 4.60713496e-03
1.36956514e-03 9.15171229e-04 1.26404509e-01 4.56279959e-04
4.57440456e-03 4.52960609e-03 2.49310508e-01 4.49127099e-03
4.54785256e-03 1.68976421e-03 4.50768927e-03 3.43055674e-03
4.56687342e-03 3.47631401e-03 4.54899482e-03 4.49431129e-03
4.51655267e-03 3.43932095e-03 1.98676363e-01 4.57048090e-03
4.48297476e-03 3.42010451e-03 4.55816835e-03 3.46713723e-03
2.64454633e-03 1.00000000e+00 4.58350033e-03 3.41619947e-03
4.53664409e-03 1.00000000e+00 4.51681949e-03 4.52239206e-03
4.52366751e-03 3.44344904e-03 4.53906646e-03 3.45062139e-03
2.63520959e-03 1.00000000e+00 4.56789136e-03 4.57824115e-03
4.52470453e-03 3.44030326e-03 1.00000000e+00 4.57244786e-03
4.58176946e-03 6.06345362e-04 1.00000000e+00 2.08224636e-03
1.25174345e-02 2.33358727e-03 5.23461669e-04 9.47866309e-03
5.32071164e-04 5.24887699e-04 4.39477852e-04]

weight distribution:
image