diff --git a/eval/main.ipynb b/eval/main.ipynb
index 7e0081309431e91f8c63744c04494f889fcd5c54..0d4bbb2a5c0e0845bbc9a23f9a3daffca43dabbb 100644
--- a/eval/main.ipynb
+++ b/eval/main.ipynb
@@ -552,606 +552,600 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "m1_state_dict: OrderedDict([('conv1.weight', tensor([[[[-0.0229, -0.1412, -0.1879, -0.1106, 0.1383],\n",
- " [-0.0951, -0.0891, -0.0665, 0.0580, 0.1503],\n",
- " [ 0.0548, -0.1465, -0.1330, 0.0034, 0.0442],\n",
- " [ 0.0647, 0.1041, -0.0606, 0.0304, 0.1865],\n",
- " [ 0.1933, -0.1473, -0.0146, 0.1158, -0.1871]]],\n",
+ "m1_parameters: {'conv1.weight': tensor([[[[-0.0294, -0.0659, -0.1267, -0.1610, -0.1462],\n",
+ " [-0.1133, 0.1424, 0.1439, -0.0677, 0.1200],\n",
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"\n",
"\n",
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- " [ 0.1835, 0.0560, -0.1895, -0.1500, 0.0887]]],\n",
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"\n",
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"\n",
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- " [ 0.0788, -0.1481, 0.0193, -0.1642, 0.0172]]],\n",
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"\n",
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- " [-0.0082, -0.1101, 0.1115, -0.1290, -0.0865]]],\n",
+ " [[[ 0.1145, 0.1584, 0.0135, -0.0490, 0.1506],\n",
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"\n",
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"\n",
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- " [ 0.1101, -0.1810, 0.1917, -0.1686, 0.0950]]],\n",
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"\n",
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"\n",
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"\n",
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"\n",
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+ " [[[ 0.0671, 0.1113, 0.0242, -0.0552, -0.1848],\n",
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+ " [-0.0655, 0.1431, -0.1373, 0.0311, -0.1628]]],\n",
"\n",
"\n",
- " [[[ 0.0605, -0.0014, 0.1496, -0.0587, 0.0858],\n",
- " [-0.1680, -0.0135, 0.0629, 0.1832, 0.1535],\n",
- " [-0.0072, -0.0376, -0.0897, 0.1623, -0.0962],\n",
- " [-0.0958, -0.1683, 0.0390, -0.0637, 0.0455],\n",
- " [ 0.1662, 0.1725, 0.1976, -0.0250, -0.0974]]]])), ('conv1.bias', tensor([ 0.1412, -0.1699, -0.0253, -0.1142, 0.0345, -0.1778, 0.0337, -0.1811,\n",
- " 0.0301, -0.0841, -0.1326, -0.0041, 0.1206, -0.1253, -0.0549, 0.1375,\n",
- " 0.1011, -0.0645, -0.1874, 0.0055, -0.0208, 0.0685, 0.0626, -0.0987,\n",
- " -0.0448, -0.0284, 0.1807, 0.0769, 0.0155, 0.0411, -0.1243, -0.0014])), ('conv2.weight', tensor([[[[ 3.2746e-02, 7.6064e-03, 3.3012e-02, -2.6875e-02, -1.6692e-02],\n",
- " [-1.9286e-02, -6.8511e-03, -1.4456e-02, -8.0592e-03, -3.1047e-02],\n",
- " [-2.7445e-02, 3.1905e-02, -1.9314e-02, -2.7730e-02, 2.0723e-02],\n",
- " [ 3.1894e-02, 2.0955e-02, -2.2974e-02, 1.7649e-02, 1.6758e-02],\n",
- " [ 1.2061e-02, 3.0052e-02, 3.3479e-02, -5.7044e-03, 2.5757e-02]],\n",
+ " [[[ 0.0414, -0.0397, -0.0018, 0.1074, 0.1924],\n",
+ " [ 0.0205, 0.1236, -0.1880, 0.0947, -0.0946],\n",
+ " [-0.0543, -0.0087, 0.0633, -0.1134, 0.0912],\n",
+ " [ 0.0875, 0.0397, -0.1993, 0.1947, -0.1831],\n",
+ " [ 0.1359, 0.1628, -0.0632, -0.1867, -0.0839]]]]), 'conv1.bias': tensor([ 0.0303, 0.1421, 0.0549, -0.0636, 0.0261, -0.0631, 0.0215, 0.1342,\n",
+ " -0.0792, -0.1747, 0.0829, 0.1978, -0.1716, -0.1050, -0.0049, 0.1790,\n",
+ " 0.1964, 0.0633, 0.0980, -0.0159, 0.0837, -0.1232, -0.0526, -0.1208,\n",
+ " -0.1421, -0.0880, 0.1810, -0.0636, 0.1665, 0.1121, -0.1900, 0.0091]), 'conv2.weight': tensor([[[[-1.0712e-02, -2.8543e-02, 2.5060e-03, 9.5242e-03, 3.1358e-02],\n",
+ " [-1.4135e-02, 1.3580e-02, 2.1455e-02, 1.2194e-02, 1.4131e-02],\n",
+ " [ 3.0316e-02, -1.1152e-02, -3.2848e-02, -2.2067e-02, -2.6107e-02],\n",
+ " [ 8.4410e-03, 3.9427e-03, 1.2867e-02, -1.2513e-03, -2.1535e-02],\n",
+ " [-3.9282e-03, 8.2564e-03, 1.4120e-02, 2.8508e-02, 3.9923e-03]],\n",
"\n",
- " [[ 1.4391e-02, -1.5190e-02, -1.0179e-03, 2.7308e-02, 2.1345e-02],\n",
- " [-2.1532e-02, 1.9428e-03, -1.1062e-03, 2.1827e-02, 2.8505e-02],\n",
- " [ 3.4529e-02, 3.2408e-02, 9.7295e-03, 9.3658e-03, 6.2646e-03],\n",
- " [ 1.5906e-02, 1.4007e-02, -3.4417e-02, 2.2925e-02, -3.3685e-03],\n",
- " [-8.7568e-03, 1.2605e-02, -2.5771e-02, -2.2213e-02, -2.3717e-02]],\n",
+ " [[-1.4297e-03, 4.7124e-03, -3.4464e-02, 1.4309e-02, -3.4432e-02],\n",
+ " [ 2.6338e-02, -4.2020e-03, 5.5271e-03, 3.1447e-02, 3.5195e-02],\n",
+ " [-9.7311e-03, 3.0671e-02, 3.3432e-02, -1.6397e-02, 9.7262e-03],\n",
+ " [-3.1700e-02, -2.4078e-02, -5.8298e-03, -7.3698e-03, -3.1840e-02],\n",
+ " [ 1.7487e-02, -2.2445e-02, -4.2725e-03, 1.6929e-02, -1.6501e-02]],\n",
"\n",
- " [[-2.9527e-02, 2.2819e-02, -7.3266e-04, -5.2441e-03, -1.8673e-02],\n",
- " [-2.0790e-02, 2.8179e-02, 1.4795e-02, 2.2660e-02, 1.6540e-02],\n",
- " [ 2.0379e-02, -2.2184e-02, -2.1391e-02, -2.8546e-02, 1.2025e-02],\n",
- " [-1.6028e-02, -2.5776e-02, 2.8277e-03, 1.8941e-02, -1.7032e-02],\n",
- " [-2.0459e-02, 3.2729e-02, -3.4816e-02, 2.6955e-02, 1.1083e-02]],\n",
+ " [[ 2.6720e-02, 1.5540e-02, 2.3545e-02, -3.1226e-03, 4.3139e-03],\n",
+ " [ 2.4492e-02, -1.6616e-02, -2.1790e-02, 3.0564e-02, -1.6427e-02],\n",
+ " [-1.7733e-02, -2.4438e-02, -1.9700e-02, 2.1084e-02, 2.9459e-02],\n",
+ " [-3.0856e-02, -3.5242e-02, 2.0413e-02, 4.1613e-03, 8.3422e-03],\n",
+ " [-1.5534e-02, -1.4875e-02, 1.6494e-02, -3.2325e-02, -1.1099e-04]],\n",
"\n",
" ...,\n",
"\n",
- " [[ 2.0854e-03, 8.9433e-03, -3.4360e-02, 2.9036e-02, -1.2978e-02],\n",
- " [ 2.2407e-02, 8.8171e-03, 1.4031e-02, 3.2900e-02, 3.5173e-02],\n",
- " [-2.0740e-03, 1.1162e-02, 3.1859e-02, -1.1679e-02, -3.2770e-03],\n",
- " [-1.5003e-02, 8.3509e-03, -2.1289e-02, -1.8160e-02, -1.7401e-02],\n",
- " [ 2.8564e-03, 2.9883e-02, -1.2668e-02, 8.0667e-04, 3.4512e-02]],\n",
- "\n",
- " [[ 2.4441e-02, -3.2026e-02, 3.4663e-02, 1.3297e-02, -1.9757e-02],\n",
- " [-1.9587e-02, 9.0344e-03, -2.2241e-02, -1.1374e-02, -3.2283e-02],\n",
- " [ 5.7302e-03, 2.9798e-02, 1.0315e-02, -2.8048e-02, 1.4863e-03],\n",
- " [-2.0083e-02, -3.0710e-03, -3.4549e-02, 2.3184e-02, -9.9700e-03],\n",
- " [-1.0007e-02, 2.3101e-02, 1.5020e-02, -1.0336e-02, -1.8888e-03]],\n",
- "\n",
- " [[ 1.8208e-02, -1.9901e-02, 3.0093e-02, 1.9968e-02, 7.0317e-03],\n",
- " [-3.3956e-02, -1.7922e-03, -1.4408e-02, 2.8461e-02, 7.6843e-03],\n",
- " [-1.1414e-02, 2.6077e-02, -2.3152e-02, 8.8792e-03, -2.0675e-02],\n",
- " [ 1.4362e-02, 5.4677e-03, -2.9708e-02, 3.0239e-02, -3.1256e-02],\n",
- " [-8.4240e-03, -2.9612e-02, 6.7951e-03, 7.8364e-03, 3.2977e-02]]],\n",
- "\n",
- "\n",
- " [[[ 9.4418e-03, 3.2786e-03, -1.2435e-02, 1.5070e-02, -1.8267e-03],\n",
- " [ 1.6058e-03, -9.9090e-03, -1.7479e-02, 1.5799e-02, -1.9801e-03],\n",
- " [ 1.5065e-02, -2.1835e-02, 2.9958e-03, -2.2055e-02, 1.7255e-02],\n",
- " [-2.4921e-02, -2.3748e-02, 7.5943e-03, -2.8805e-02, 2.4922e-03],\n",
- " [-3.1805e-02, -2.5896e-02, -1.7868e-02, 2.7961e-02, -1.2373e-02]],\n",
- "\n",
- " [[-2.6565e-02, 3.5746e-03, -2.2760e-02, -6.0303e-03, -3.2547e-02],\n",
- " [-2.1761e-02, 1.7825e-02, 3.4372e-03, 2.1411e-02, 1.0314e-02],\n",
- " [ 1.2855e-02, -1.7095e-02, -3.3342e-02, -2.0678e-02, -1.1955e-02],\n",
- " [-6.1599e-03, -1.7464e-02, 4.1114e-03, 1.0711e-02, 3.1798e-02],\n",
- " [-1.3857e-02, 9.0615e-03, -6.9174e-03, -3.3586e-02, 1.9395e-02]],\n",
- "\n",
- " [[-3.0132e-02, -2.2624e-03, -5.9316e-03, -1.7227e-02, -2.4533e-02],\n",
- " [-6.2100e-03, -2.3675e-02, 3.0786e-02, 7.8731e-03, 2.2696e-03],\n",
- " [-3.3538e-02, 2.7875e-02, -1.9615e-02, 1.6261e-02, 1.3296e-04],\n",
- " [-3.4132e-02, -2.4884e-02, 2.0227e-02, 1.8549e-02, -8.0078e-03],\n",
- " [-1.4182e-03, 2.7721e-02, -1.1709e-02, -1.0164e-02, 1.3831e-02]],\n",
+ " [[ 1.2833e-02, -2.0625e-02, -2.0700e-02, -1.3513e-02, 1.5524e-02],\n",
+ " [ 7.5736e-03, 3.2956e-02, 2.6385e-02, -2.1103e-02, -2.3895e-02],\n",
+ " [-1.9102e-02, 1.1805e-02, 1.1777e-02, -3.0465e-02, 2.6048e-03],\n",
+ " [ 6.3230e-04, 1.0886e-02, -1.5035e-02, -1.5262e-02, -2.5167e-02],\n",
+ " [-2.1168e-03, 2.6181e-02, 1.4023e-02, 2.2960e-02, 3.0476e-02]],\n",
+ "\n",
+ " [[-2.1003e-02, -2.1934e-02, 1.6896e-02, -7.1724e-03, -2.8637e-02],\n",
+ " [ 2.8492e-03, 2.2367e-02, -3.2999e-02, -2.8547e-02, 2.5825e-02],\n",
+ " [-2.4395e-02, -1.2782e-02, 1.6746e-02, -1.8496e-02, -2.7374e-02],\n",
+ " [-2.0825e-03, 1.3699e-02, 2.0900e-02, -1.0655e-02, -2.0718e-02],\n",
+ " [ 2.3637e-03, -1.2933e-02, 1.3596e-03, -1.4176e-02, -2.7697e-02]],\n",
+ "\n",
+ " [[ 1.6140e-02, -9.6101e-03, 1.6965e-02, -2.4911e-02, 1.7669e-02],\n",
+ " [ 6.7341e-03, 1.9680e-02, -2.4388e-02, 2.5657e-02, -3.5043e-02],\n",
+ " [-1.7948e-02, -1.9798e-02, 3.2972e-02, -1.0105e-02, 3.2288e-02],\n",
+ " [ 6.9848e-03, -2.0427e-02, 3.0102e-02, 2.0419e-02, 1.1636e-02],\n",
+ " [ 1.4831e-02, 2.5886e-02, 8.4296e-03, 3.6944e-03, 1.2589e-02]]],\n",
+ "\n",
+ "\n",
+ " [[[-1.5369e-03, 6.7277e-03, -2.8153e-03, -5.2977e-03, 7.7895e-04],\n",
+ " [ 2.6822e-02, -2.7268e-03, 8.9981e-03, -1.0177e-02, 3.8218e-03],\n",
+ " [-1.2254e-02, 7.7431e-03, -3.3513e-02, -3.2448e-02, -8.5315e-03],\n",
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+ " [ 5.6234e-03, -2.1741e-03, -1.8802e-02, -1.0976e-02, 2.7378e-02]],\n",
+ "\n",
+ " [[ 7.5464e-03, -2.4656e-02, -3.2512e-02, -3.2849e-02, -1.5935e-02],\n",
+ " [-1.8062e-02, -8.6980e-03, -1.6742e-02, -2.0394e-03, -7.8879e-03],\n",
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+ " [-1.8519e-02, 7.6015e-03, 2.9804e-02, 3.7601e-03, -3.3281e-02],\n",
+ " [ 7.4764e-03, 3.5919e-03, 1.6526e-02, -8.7982e-03, -9.3495e-03]],\n",
+ "\n",
+ " [[-8.7813e-03, 2.0255e-02, 1.6511e-02, 9.1172e-04, -3.7212e-03],\n",
+ " [ 3.2860e-02, -1.9111e-02, 1.5490e-03, -5.6712e-03, -1.6889e-02],\n",
+ " [ 7.5624e-03, -6.9371e-03, 3.1618e-02, -6.7844e-03, -3.1054e-02],\n",
+ " [ 7.0345e-03, -7.7054e-03, 3.5078e-02, 6.3236e-03, 2.3317e-02],\n",
+ " [-2.2862e-02, -9.7549e-03, 2.7260e-02, -3.3476e-02, 1.8389e-02]],\n",
"\n",
" ...,\n",
"\n",
- " [[ 1.5085e-02, 2.1404e-02, 1.1670e-02, 7.9414e-03, -2.3269e-02],\n",
- " [ 3.1390e-03, -1.9571e-02, 1.7058e-02, -2.1079e-02, 1.1395e-02],\n",
- " [-1.1528e-02, 2.1676e-02, 3.0260e-02, -8.6194e-03, -3.5215e-02],\n",
- " [ 1.2097e-02, 1.3447e-02, -3.0891e-02, -3.1753e-02, 2.9082e-03],\n",
- " [ 2.6964e-02, -1.8573e-02, -1.7564e-02, -3.2200e-02, 1.8055e-02]],\n",
- "\n",
- " [[ 1.4695e-02, -2.5493e-02, 1.1962e-02, -3.4501e-02, -2.8435e-02],\n",
- " [-2.0480e-02, 1.4531e-03, 2.4348e-02, 2.9468e-02, -2.0317e-02],\n",
- " [-1.7271e-02, 3.5342e-03, -1.6577e-03, 3.0479e-02, 7.5468e-03],\n",
- " [-4.8140e-03, 1.0219e-02, 3.2605e-02, 9.3662e-03, 1.7923e-02],\n",
- " [ 6.7177e-03, -2.4020e-02, -9.6501e-03, -6.1049e-03, -1.5764e-02]],\n",
- "\n",
- " [[-1.1772e-02, 2.4333e-03, 3.3412e-03, -2.2287e-02, 3.3003e-02],\n",
- " [ 7.7133e-03, -2.8402e-02, 3.0503e-02, 2.0268e-02, -2.8774e-02],\n",
- " [ 3.2205e-02, 4.7889e-03, 1.4656e-02, 9.9381e-03, 5.1627e-03],\n",
- " [ 7.8195e-03, 2.9291e-02, -1.8244e-02, -2.9129e-03, 3.4969e-02],\n",
- " [ 1.3522e-02, 1.6393e-02, 3.0487e-02, -1.7014e-02, -1.7204e-02]]],\n",
- "\n",
- "\n",
- " [[[-2.2435e-02, 3.2695e-02, 1.8033e-03, -1.2957e-02, -1.8227e-02],\n",
- " [-2.0660e-02, 1.8752e-02, 1.9233e-02, -1.0020e-02, -2.7806e-03],\n",
- " [ 1.5691e-03, -1.5605e-02, 2.6992e-02, -3.3455e-02, 1.6912e-02],\n",
- " [ 7.3307e-03, -2.2232e-02, -2.6121e-02, -2.3932e-03, 2.7684e-02],\n",
- " [ 3.3649e-02, -5.1965e-03, -1.5039e-02, 3.5366e-03, 3.0508e-02]],\n",
- "\n",
- " [[ 2.0061e-02, 1.9717e-02, 1.0357e-02, -3.3255e-02, 9.8102e-03],\n",
- " [ 1.7618e-02, 2.4140e-02, 7.0476e-03, -3.2115e-02, -7.6617e-03],\n",
- " [-8.2441e-03, -1.5926e-02, -2.5963e-02, -2.6432e-02, 2.3809e-02],\n",
- " [ 2.5385e-03, -9.1865e-04, -1.2525e-02, 2.9783e-02, 3.4802e-02],\n",
- " [ 3.4328e-02, 2.5756e-02, -2.1410e-02, -2.0238e-02, -2.1875e-02]],\n",
- "\n",
- " [[-9.3015e-03, 1.4058e-02, -1.1882e-02, 3.3075e-02, 3.4996e-02],\n",
- " [-7.9394e-03, 3.2237e-02, -2.6205e-02, -3.0383e-02, -7.0993e-03],\n",
- " [ 2.0615e-02, -1.4620e-02, -3.2926e-02, -3.1128e-02, -2.8229e-02],\n",
- " [ 2.4899e-03, 8.9844e-03, -3.4723e-02, 8.2829e-03, 8.7329e-03],\n",
- " [ 2.8381e-02, 3.2110e-02, -2.0183e-03, -1.4615e-02, -9.5140e-03]],\n",
+ " [[ 1.3349e-02, 1.8076e-02, -2.1153e-03, 6.5682e-04, 2.4534e-02],\n",
+ " [ 5.3663e-03, 2.8427e-02, 7.8194e-03, -1.4124e-02, 3.0364e-02],\n",
+ " [ 3.1933e-02, -2.4390e-02, -3.3345e-02, 1.1310e-02, -2.0207e-02],\n",
+ " [-2.5572e-02, 2.6358e-02, 1.7217e-02, -2.9017e-03, 7.4605e-03],\n",
+ " [-3.0439e-02, 1.5487e-02, -5.8104e-03, -3.2419e-02, 6.8073e-03]],\n",
+ "\n",
+ " [[ 1.1699e-02, 2.2438e-02, -1.2508e-02, -1.1145e-02, 1.1388e-02],\n",
+ " [-1.5566e-02, 1.7208e-02, -1.0435e-02, 9.3911e-03, 2.2554e-03],\n",
+ " [-7.6326e-03, -1.4475e-02, -7.9627e-04, 3.4089e-02, -2.1129e-02],\n",
+ " [ 8.4534e-05, -1.6221e-02, -4.5830e-03, -2.2959e-02, -2.0502e-02],\n",
+ " [-2.4321e-02, 1.4042e-02, 3.4342e-03, 2.5126e-02, 3.1417e-02]],\n",
+ "\n",
+ " [[-7.1903e-03, -1.5285e-02, 3.4991e-02, -1.1870e-02, 3.3646e-02],\n",
+ " [ 2.5525e-02, 2.7944e-02, 3.1858e-02, 2.1613e-02, 2.5457e-02],\n",
+ " [-1.5631e-02, -1.9511e-02, 1.4821e-02, 6.1392e-03, -2.2879e-02],\n",
+ " [-2.0709e-03, 2.4683e-02, 1.5450e-02, 1.7543e-02, 3.0431e-02],\n",
+ " [ 1.2472e-02, 3.3912e-02, -3.3891e-02, -2.9483e-02, 2.1657e-02]]],\n",
+ "\n",
+ "\n",
+ " [[[ 1.2854e-03, 1.4983e-02, 2.6787e-03, -3.7954e-03, -3.8526e-04],\n",
+ " [-9.0427e-03, -2.3686e-02, -2.5989e-02, 2.9986e-02, -3.4829e-02],\n",
+ " [ 1.4774e-02, -2.5571e-03, 1.0485e-02, 5.6443e-03, -4.8553e-03],\n",
+ " [ 3.6432e-03, 1.7875e-02, 1.5348e-03, 1.8016e-02, 8.2804e-03],\n",
+ " [ 1.9742e-02, -1.5757e-02, -2.3739e-02, 1.6706e-02, -5.5210e-03]],\n",
+ "\n",
+ " [[-1.4544e-02, 2.8706e-02, 3.0579e-02, -3.2698e-02, 9.7423e-03],\n",
+ " [-2.7827e-02, -3.6608e-03, 6.3911e-03, 1.1768e-03, -2.5861e-02],\n",
+ " [-3.3910e-02, 3.2610e-02, -1.0725e-02, -2.5239e-02, 1.3869e-02],\n",
+ " [-2.4907e-02, 2.2308e-02, 3.4435e-02, -1.1574e-02, -1.5687e-02],\n",
+ " [-3.3932e-02, -1.4322e-02, -9.2028e-03, 1.6489e-02, 2.7247e-02]],\n",
+ "\n",
+ " [[ 1.9997e-02, 2.0339e-02, -2.4083e-02, 2.1822e-02, 3.5218e-02],\n",
+ " [ 4.6625e-03, -4.3648e-03, 1.3782e-02, -9.2227e-03, -1.9670e-02],\n",
+ " [-2.3750e-02, -1.6718e-02, -8.2103e-03, -3.0051e-02, 2.0756e-02],\n",
+ " [ 9.1907e-03, -2.6468e-02, 2.6651e-02, 2.2466e-02, 2.2550e-02],\n",
+ " [-2.5045e-02, -3.3377e-02, 2.4491e-02, -2.2864e-02, -6.7297e-03]],\n",
"\n",
" ...,\n",
"\n",
- " [[ 2.5843e-02, -2.7146e-02, 3.1365e-02, -1.7570e-02, -1.1656e-02],\n",
- " [ 2.4452e-02, -2.9268e-02, 2.2156e-02, -2.0007e-02, 1.2864e-02],\n",
- " [ 2.2081e-02, 4.4346e-03, -3.3851e-02, -2.2446e-02, -2.9914e-02],\n",
- " [-1.3931e-02, -1.0571e-02, -1.9827e-02, -8.4832e-03, -4.6840e-04],\n",
- " [ 3.3050e-03, 2.9839e-02, 2.3548e-02, 1.8797e-02, 2.3927e-02]],\n",
+ " [[ 2.5862e-02, -1.0371e-03, -1.9383e-02, 1.7942e-03, 1.9761e-02],\n",
+ " [-2.8891e-02, 6.3965e-03, -2.6830e-02, 1.3699e-02, 1.0821e-02],\n",
+ " [ 1.1547e-02, -1.9258e-02, 1.4291e-02, -7.1339e-03, -2.1092e-02],\n",
+ " [ 1.1358e-02, 5.8365e-03, -2.8330e-02, -1.6591e-02, 1.4738e-02],\n",
+ " [-3.0109e-03, -3.1205e-02, 1.0713e-02, -2.7946e-02, 5.6631e-03]],\n",
"\n",
- " [[ 6.0766e-03, -2.1119e-02, -7.4612e-03, -2.8573e-02, -1.1375e-02],\n",
- " [-2.1335e-02, 6.7210e-03, -1.2251e-02, -1.0163e-03, -6.8753e-03],\n",
- " [-1.0076e-02, -2.1910e-03, 5.1250e-04, -5.3031e-03, -7.5937e-03],\n",
- " [-2.6741e-03, -3.4738e-02, 3.1672e-02, -2.4893e-02, -3.3263e-02],\n",
- " [-1.1028e-02, 1.9241e-02, 1.6009e-02, 2.4161e-02, 3.3235e-02]],\n",
+ " [[-3.4269e-03, 5.9247e-03, -2.2628e-02, 1.5790e-02, 1.6851e-02],\n",
+ " [-1.3199e-02, 1.1820e-02, -2.9882e-02, 1.5963e-02, 1.4160e-02],\n",
+ " [-1.8430e-02, 1.7088e-02, 1.0258e-02, -3.1797e-02, -1.5712e-02],\n",
+ " [ 5.8283e-03, -3.2654e-02, -1.2848e-02, 2.9440e-02, 1.5735e-02],\n",
+ " [ 1.5160e-02, -1.1311e-03, 1.5635e-02, -3.1450e-03, -2.3950e-02]],\n",
"\n",
- " [[ 7.0783e-03, -1.9811e-02, -8.6785e-03, -3.4500e-02, 1.2150e-02],\n",
- " [-7.2774e-03, 2.2635e-03, 3.5135e-02, -3.3153e-03, -1.7127e-02],\n",
- " [ 1.1098e-02, 1.1369e-02, -3.5151e-03, -1.8415e-02, 7.1177e-03],\n",
- " [ 7.1935e-03, -2.6246e-02, -1.0526e-02, -2.6759e-02, -4.7185e-03],\n",
- " [-2.3434e-02, -4.3492e-03, -4.9457e-03, -2.1908e-02, 7.1825e-03]]],\n",
+ " [[ 1.1689e-02, -5.3986e-03, -1.7156e-02, 1.5808e-02, 1.1226e-02],\n",
+ " [ 6.9512e-03, 1.9596e-02, -9.9320e-03, -2.5242e-02, 2.5922e-02],\n",
+ " [-1.1149e-03, -1.8153e-02, -6.7535e-03, -4.0143e-03, 1.5343e-02],\n",
+ " [ 2.1245e-02, 2.0272e-02, -1.5746e-02, 4.4477e-03, 1.3009e-02],\n",
+ " [-2.7403e-02, -1.7578e-03, -5.7534e-03, -4.3350e-03, 3.2173e-03]]],\n",
"\n",
"\n",
" ...,\n",
"\n",
"\n",
- " [[[ 2.1287e-02, -1.8313e-02, -3.6076e-03, -6.2449e-03, -2.4652e-02],\n",
- " [ 8.9968e-03, -1.1765e-02, -2.1595e-02, -2.4103e-02, 6.7955e-03],\n",
- " [ 3.9301e-03, -3.0373e-02, 3.2183e-02, 3.5264e-02, -2.2304e-03],\n",
- " [-3.9002e-03, -4.5479e-04, -1.1849e-02, 7.2274e-03, 4.6744e-03],\n",
- " [ 2.6520e-02, -1.4180e-02, -3.4668e-02, 1.5128e-02, -3.3632e-02]],\n",
+ " [[[ 2.4695e-02, 2.4198e-02, 5.4242e-03, 1.7946e-03, 1.5525e-03],\n",
+ " [-6.9484e-03, -2.8010e-02, 6.0022e-03, -3.4202e-02, -9.2220e-03],\n",
+ " [-1.8714e-02, -3.3158e-02, 1.2717e-02, 2.1173e-02, 2.3357e-02],\n",
+ " [ 2.1218e-02, 1.3226e-02, 1.5477e-02, 1.4576e-02, -1.6706e-02],\n",
+ " [ 5.8316e-03, 1.7646e-02, 2.6505e-02, 1.6435e-02, -9.7523e-03]],\n",
"\n",
- " [[ 1.8598e-02, 1.4959e-02, -2.9480e-02, 1.9813e-02, -1.5348e-02],\n",
- " [ 6.2970e-03, -3.1894e-02, -1.5896e-03, -2.4380e-02, 9.9467e-03],\n",
- " [-3.0277e-02, -2.7341e-02, 3.4734e-02, 6.8040e-03, 3.2219e-02],\n",
- " [-2.4927e-03, -2.5790e-03, -5.7664e-03, -3.2622e-02, -3.3634e-02],\n",
- " [ 2.0730e-02, -2.5132e-02, -2.6545e-02, -1.1005e-02, 2.8195e-02]],\n",
+ " [[-7.5557e-03, 3.0235e-02, 4.0494e-03, -6.5395e-03, -2.7983e-02],\n",
+ " [-1.6704e-02, -1.4708e-02, -1.2753e-02, 2.0003e-02, 2.0317e-02],\n",
+ " [-1.4792e-02, -2.5440e-03, 8.3960e-03, 3.1746e-02, -4.2791e-03],\n",
+ " [-2.6947e-02, 2.8178e-02, -8.7998e-03, -1.1918e-03, 1.9409e-02],\n",
+ " [ 2.7548e-02, 2.9289e-02, -1.4868e-02, -2.4845e-02, 2.1959e-02]],\n",
"\n",
- " [[ 2.6250e-02, 7.9877e-03, -1.8213e-02, 1.4875e-02, -1.2586e-02],\n",
- " [ 3.4744e-03, -8.0666e-04, 2.5727e-02, 2.8350e-02, -9.4837e-03],\n",
- " [ 1.4090e-02, -1.2686e-02, -1.7193e-02, 3.3702e-02, -1.3203e-02],\n",
- " [-1.9251e-02, -2.0643e-02, -3.4949e-02, -6.2629e-03, -1.9547e-02],\n",
- " [-1.9111e-02, 4.1030e-03, -2.7258e-02, -1.1742e-02, 1.5548e-02]],\n",
+ " [[ 2.7115e-03, 2.1398e-02, -2.7235e-02, 2.4657e-02, 3.2983e-02],\n",
+ " [-2.9811e-02, 2.8511e-02, 2.6691e-02, 3.0088e-02, 5.6536e-03],\n",
+ " [ 1.2006e-02, 9.3720e-03, -8.6544e-04, -1.8001e-02, -4.6723e-04],\n",
+ " [ 1.5956e-02, 1.0558e-02, -2.6408e-03, -1.8055e-02, -1.8820e-02],\n",
+ " [ 2.0884e-02, -6.9533e-03, -2.7761e-02, -2.1180e-02, -1.0313e-02]],\n",
"\n",
" ...,\n",
"\n",
- " [[-2.5090e-03, 4.7538e-03, 7.9407e-03, -2.2791e-02, 2.1788e-03],\n",
- " [-4.9433e-03, 3.1922e-02, -3.1142e-02, 1.4006e-02, -7.7551e-03],\n",
- " [ 2.1749e-02, 5.9137e-03, -1.1533e-02, -1.6676e-02, -3.5265e-03],\n",
- " [ 3.1718e-02, 1.0119e-02, 3.2395e-02, 3.3945e-02, 4.8077e-03],\n",
- " [-1.1578e-02, -2.0632e-02, 2.7696e-02, 3.2618e-02, 9.7284e-03]],\n",
- "\n",
- " [[ 1.8375e-02, -9.7233e-05, 1.8388e-02, -2.9518e-02, 3.9843e-03],\n",
- " [-1.9700e-02, 3.2218e-03, 2.4047e-02, -3.0775e-02, 1.4493e-02],\n",
- " [-9.0917e-03, -7.6246e-03, -1.3552e-02, 2.6074e-03, 2.4428e-02],\n",
- " [ 2.7959e-02, 2.8538e-02, 1.4753e-02, -1.2307e-02, -2.6018e-02],\n",
- " [-3.3357e-02, 3.3910e-02, 1.0897e-02, 2.8469e-02, -2.6521e-02]],\n",
- "\n",
- " [[-3.1437e-02, -3.0936e-02, 2.0549e-02, 2.5189e-02, 5.8238e-03],\n",
- " [ 1.3889e-02, -2.7012e-02, 3.3450e-02, -1.3303e-02, -2.2165e-02],\n",
- " [ 2.1920e-02, -2.0136e-02, -7.9523e-03, -1.1588e-02, -2.8461e-02],\n",
- " [-5.5698e-03, -9.2438e-03, 4.1570e-04, -1.8359e-02, 1.9532e-02],\n",
- " [ 2.0134e-02, 8.2159e-03, -2.3395e-02, 7.6182e-03, 2.7166e-02]]],\n",
- "\n",
- "\n",
- " [[[-7.3934e-03, -1.0176e-02, -9.7839e-03, -4.7201e-03, 2.9347e-02],\n",
- " [ 2.2820e-02, -2.3556e-02, 3.1363e-02, 3.1633e-02, 1.2403e-02],\n",
- " [ 1.8365e-02, 1.9939e-02, -1.0798e-02, 1.4977e-02, -2.4530e-02],\n",
- " [-2.7912e-02, 1.9863e-02, 1.0049e-02, 1.4724e-02, 1.2780e-02],\n",
- " [ 4.0170e-03, -3.3140e-02, -2.9632e-02, 1.4946e-03, -1.6940e-02]],\n",
- "\n",
- " [[-3.4747e-02, -5.2359e-03, -1.5862e-02, 2.6807e-02, -5.9706e-03],\n",
- " [ 2.7407e-02, -1.0718e-02, -1.4837e-02, -3.1179e-02, -1.7709e-02],\n",
- " [-1.3655e-02, -2.1498e-02, 2.8826e-02, 2.5957e-02, -2.4366e-02],\n",
- " [ 1.4200e-02, -1.4852e-02, -4.7653e-03, 2.4253e-02, -1.6041e-02],\n",
- " [-4.7325e-03, 2.8462e-02, -5.8148e-03, -2.6908e-02, -2.0238e-02]],\n",
- "\n",
- " [[ 4.9883e-03, 8.7387e-03, 1.6713e-02, -1.0209e-02, -1.0910e-03],\n",
- " [ 2.6915e-02, -2.4194e-02, 2.7620e-02, 2.2118e-02, -2.5813e-02],\n",
- " [-8.1892e-03, -2.0470e-02, -1.1753e-02, -1.0251e-02, 2.4059e-02],\n",
- " [-3.1399e-03, 3.1092e-02, 1.7936e-02, -2.1981e-02, 2.5822e-02],\n",
- " [ 1.9193e-02, 9.7368e-03, 2.6554e-02, -2.7229e-02, 1.5611e-02]],\n",
+ " [[-2.5222e-02, -2.6723e-02, -2.5127e-02, -8.3920e-03, 1.2354e-02],\n",
+ " [ 2.4635e-02, -2.1187e-02, 3.2576e-02, 5.1753e-03, -1.5645e-02],\n",
+ " [-2.7097e-02, -1.3811e-02, -2.8127e-02, -7.5398e-03, -2.5397e-02],\n",
+ " [-3.2788e-02, 9.4662e-03, -2.5773e-02, -5.5557e-03, -2.1646e-02],\n",
+ " [-3.9811e-03, -2.9400e-02, -2.9801e-02, 3.4086e-03, -2.5995e-02]],\n",
+ "\n",
+ " [[-1.7667e-02, -2.9269e-02, 3.3983e-02, 1.7904e-03, -1.1844e-02],\n",
+ " [-3.1558e-03, 2.8698e-02, -2.4786e-02, 2.8517e-02, -2.1105e-02],\n",
+ " [-1.3482e-02, -2.3590e-02, 1.5106e-02, -2.6257e-02, -3.1513e-02],\n",
+ " [ 1.5126e-02, 9.0866e-03, -3.5108e-03, -3.1232e-02, 1.0039e-02],\n",
+ " [ 1.0646e-02, 2.0490e-02, -1.6026e-02, 9.4491e-03, 1.8696e-03]],\n",
+ "\n",
+ " [[ 9.5597e-03, -1.0937e-03, 3.1415e-03, -2.9728e-02, 2.4290e-02],\n",
+ " [ 2.1983e-02, -4.4185e-03, -4.3551e-03, -2.3103e-03, 2.8911e-02],\n",
+ " [-2.3258e-02, -2.7318e-02, 2.5071e-02, -2.8034e-02, -9.6178e-03],\n",
+ " [ 1.1631e-02, -6.4006e-03, 3.1090e-02, -2.6229e-02, -3.1959e-02],\n",
+ " [-1.8579e-03, 1.1335e-02, -1.9144e-02, 2.1692e-02, 7.2188e-03]]],\n",
+ "\n",
+ "\n",
+ " [[[-5.6811e-03, -1.0477e-02, 1.1886e-02, 7.3932e-03, 1.6800e-02],\n",
+ " [ 2.9957e-02, -4.6041e-03, 1.7368e-02, 2.9004e-02, -1.8263e-02],\n",
+ " [-2.6259e-02, 1.8272e-02, -8.9695e-03, 2.3765e-02, -3.3679e-02],\n",
+ " [-1.0965e-02, -7.6722e-03, 2.3450e-02, -1.0505e-02, 5.3181e-03],\n",
+ " [-5.6810e-03, -2.4764e-02, 3.1046e-02, -2.9747e-03, -2.8656e-02]],\n",
+ "\n",
+ " [[ 2.0621e-02, 3.0689e-02, 9.9618e-03, -1.2074e-02, -3.4941e-02],\n",
+ " [ 2.5171e-02, 2.5641e-02, 2.3229e-02, -2.1664e-02, -1.0035e-02],\n",
+ " [-2.7126e-02, 1.5039e-03, -1.8666e-02, -1.3896e-03, -2.8527e-02],\n",
+ " [-3.8435e-03, 1.9811e-02, 2.6598e-02, 3.9880e-03, -1.2667e-02],\n",
+ " [-2.9899e-02, -1.0524e-04, -6.9346e-03, -9.0742e-03, -9.5847e-03]],\n",
+ "\n",
+ " [[ 3.4221e-02, 1.8155e-02, -2.0950e-02, -3.0531e-02, -1.6531e-02],\n",
+ " [-2.6935e-02, -2.9924e-02, -1.2559e-02, -1.1806e-02, -3.4378e-02],\n",
+ " [-3.1124e-03, 6.3495e-03, -2.1526e-02, -2.1942e-02, 4.1308e-03],\n",
+ " [-4.0192e-03, -7.1271e-03, 3.2742e-02, 9.6951e-03, -8.8074e-03],\n",
+ " [ 5.0674e-03, -3.0229e-02, 1.2071e-02, -1.5985e-02, -1.9603e-02]],\n",
"\n",
" ...,\n",
"\n",
- " [[ 2.5990e-02, 1.8204e-03, 6.3907e-04, 1.3599e-02, -2.4928e-02],\n",
- " [-4.0177e-03, -9.5758e-03, -3.1354e-02, 3.4710e-02, 1.5811e-02],\n",
- " [-1.3928e-02, -5.0035e-03, -8.0641e-03, 1.7689e-03, -3.0916e-02],\n",
- " [ 2.2672e-02, 2.5900e-02, -1.4861e-02, -1.9387e-02, 2.4626e-03],\n",
- " [ 5.2564e-03, -1.1521e-02, 1.1267e-02, 2.8809e-02, 8.4900e-03]],\n",
- "\n",
- " [[-2.4825e-02, 1.4945e-02, 2.0792e-02, -7.3404e-03, -3.1627e-02],\n",
- " [ 2.1001e-02, -1.1632e-02, 1.1063e-02, 5.0528e-03, 1.8288e-02],\n",
- " [ 1.8396e-02, 2.4709e-02, -1.8625e-02, 3.1313e-03, -1.7493e-02],\n",
- " [ 3.4257e-02, -3.2146e-03, 1.9457e-02, 2.9968e-02, 2.6933e-02],\n",
- " [ 2.8540e-02, -1.9069e-02, -8.6731e-03, 6.6561e-03, -7.9887e-03]],\n",
- "\n",
- " [[ 2.0432e-02, 4.1301e-03, 2.8091e-02, -1.5266e-02, 3.8479e-03],\n",
- " [-3.0857e-03, -1.9645e-02, 3.2926e-02, -1.6260e-02, -2.0212e-02],\n",
- " [ 3.3778e-03, -9.7388e-04, -7.2386e-03, -9.4193e-03, -1.5630e-02],\n",
- " [-1.4204e-03, -8.6640e-03, 2.0029e-02, -1.6952e-02, 2.7978e-02],\n",
- " [ 1.4138e-02, -1.3769e-02, -2.7078e-02, -5.8826e-03, 2.9882e-02]]],\n",
- "\n",
- "\n",
- " [[[ 1.2291e-02, -2.2902e-02, 1.1633e-02, 3.4403e-02, -1.1917e-02],\n",
- " [ 1.2536e-02, -1.1643e-02, -9.9262e-03, 1.7047e-02, -3.4983e-02],\n",
- " [ 8.9901e-03, -3.3618e-02, -8.4233e-03, -5.1072e-04, -8.9520e-04],\n",
- " [ 1.3063e-02, 1.5268e-02, 2.8177e-02, 1.2762e-02, 2.4342e-02],\n",
- " [-1.6559e-02, 3.3652e-02, -2.4771e-03, -7.7901e-03, 3.9261e-03]],\n",
- "\n",
- " [[-1.7359e-02, -3.0286e-02, -3.1738e-02, -2.5330e-02, 2.6791e-03],\n",
- " [-1.6079e-02, -4.5769e-03, -1.9375e-02, -1.4358e-02, -1.4470e-02],\n",
- " [-2.2557e-03, -2.9062e-02, 3.2361e-02, -2.0854e-02, 1.3980e-02],\n",
- " [ 4.6692e-03, -6.2594e-03, -2.1700e-02, 1.7638e-02, -1.6371e-02],\n",
- " [ 1.3422e-02, 2.3067e-03, 2.0222e-02, 8.4460e-03, 1.5446e-02]],\n",
- "\n",
- " [[ 2.7963e-02, -2.2203e-03, -2.0449e-02, -2.6557e-02, 3.4897e-02],\n",
- " [ 6.2281e-03, 1.4564e-03, -5.3195e-03, -1.0745e-02, -2.5309e-02],\n",
- " [-2.8325e-03, -3.1341e-02, 3.5223e-02, 1.4007e-02, 9.4664e-03],\n",
- " [-1.4459e-02, 2.3820e-02, 3.5399e-03, 1.9318e-02, -8.8443e-03],\n",
- " [-2.4607e-03, 1.4686e-03, -2.0640e-02, -3.1963e-02, 3.5608e-03]],\n",
+ " [[-2.6260e-02, -1.7585e-02, -2.1982e-02, -2.3320e-02, -4.1119e-03],\n",
+ " [ 1.3096e-02, -1.7109e-02, -1.3888e-02, -2.8812e-05, 2.6391e-02],\n",
+ " [-1.3052e-02, -1.1130e-02, -2.9985e-02, 1.2317e-02, -3.1856e-02],\n",
+ " [-8.2432e-03, 2.8641e-02, 2.4846e-02, 5.5159e-03, 1.9084e-02],\n",
+ " [-3.4092e-02, -2.1065e-02, 2.2432e-02, -1.6194e-02, 2.2492e-02]],\n",
+ "\n",
+ " [[ 3.3804e-02, 1.4972e-02, 2.2994e-03, 3.1839e-02, -1.3227e-02],\n",
+ " [-3.3975e-02, -3.4533e-02, -1.6026e-02, 2.2788e-03, -1.4643e-03],\n",
+ " [ 3.2438e-02, -2.8320e-02, -1.8481e-02, 5.8380e-03, -5.3999e-03],\n",
+ " [ 9.1915e-03, 3.6022e-03, 1.1685e-04, -2.4490e-02, 1.3981e-02],\n",
+ " [ 5.1616e-03, -6.7223e-03, 2.9258e-02, 3.0399e-02, -1.0489e-02]],\n",
+ "\n",
+ " [[-2.0869e-02, -2.7418e-02, 9.2013e-03, 1.0312e-03, -1.3312e-02],\n",
+ " [ 7.1380e-05, 1.8098e-02, 4.8561e-03, 2.6030e-02, 4.5902e-03],\n",
+ " [-3.8396e-06, -9.0726e-03, -3.4657e-02, -3.5020e-02, 1.7769e-02],\n",
+ " [ 4.7196e-03, -3.0351e-04, 6.6702e-03, -1.5387e-02, -1.5521e-02],\n",
+ " [ 2.0964e-03, 1.5412e-02, 2.2774e-02, -4.0799e-03, 2.0905e-02]]],\n",
+ "\n",
+ "\n",
+ " [[[ 1.6501e-02, -2.7081e-02, 9.0558e-03, 2.5332e-03, 1.2791e-02],\n",
+ " [-7.0474e-03, 1.6052e-02, 2.9610e-02, -4.8062e-03, 2.2890e-02],\n",
+ " [-2.1236e-02, -8.2819e-03, -3.3545e-02, 3.3778e-02, 2.5133e-02],\n",
+ " [ 3.3057e-02, -1.5296e-02, 1.7353e-02, -4.8650e-03, 3.4039e-02],\n",
+ " [ 2.9383e-02, 2.2072e-02, -1.3218e-02, 2.5207e-02, -3.1896e-02]],\n",
+ "\n",
+ " [[ 1.3995e-02, -2.0663e-02, -7.7605e-03, -2.9423e-02, 1.3063e-02],\n",
+ " [ 2.5140e-02, -9.7825e-03, -2.2534e-02, 1.2679e-02, -2.3407e-03],\n",
+ " [ 3.0757e-02, 1.2600e-02, -9.9360e-03, -2.9706e-02, 3.0537e-02],\n",
+ " [ 2.1376e-02, 2.1465e-02, 1.6579e-02, -2.8762e-02, -2.8087e-02],\n",
+ " [ 2.5223e-02, -1.7151e-02, 7.6622e-03, 3.3316e-02, 9.0349e-03]],\n",
+ "\n",
+ " [[-3.2144e-02, -3.4602e-02, -1.2078e-03, 2.5526e-02, -2.1524e-02],\n",
+ " [-3.4233e-02, 8.9771e-03, 3.4649e-02, -2.9127e-02, -2.1181e-02],\n",
+ " [-2.3100e-02, 3.9237e-03, -2.6253e-02, -3.1718e-02, 3.5719e-03],\n",
+ " [-1.8098e-02, 2.5035e-02, -1.7552e-02, 2.4375e-02, -2.1021e-02],\n",
+ " [-3.5218e-02, -2.3443e-02, 3.5088e-02, -1.7220e-03, 2.7329e-03]],\n",
"\n",
" ...,\n",
"\n",
- " [[ 3.3729e-02, 1.5060e-02, -1.0339e-02, -3.3869e-02, 9.5173e-03],\n",
- " [ 2.9181e-02, 2.6096e-02, 6.5876e-03, 1.4734e-02, -1.3666e-02],\n",
- " [ 3.8105e-03, 1.4149e-02, -1.5581e-02, -6.6103e-03, 2.5904e-02],\n",
- " [ 1.7985e-02, 3.0942e-02, 1.5265e-02, -1.5719e-02, -6.3216e-03],\n",
- " [ 4.6500e-03, 1.2790e-02, 2.9090e-03, 5.3699e-03, -1.4805e-02]],\n",
- "\n",
- " [[-1.0921e-02, -1.9939e-03, -2.8213e-02, -6.9159e-03, -1.5026e-03],\n",
- " [ 3.1958e-02, 7.6529e-03, -1.5578e-02, -2.3311e-02, -7.5325e-03],\n",
- " [ 9.9005e-03, -1.2741e-02, 2.4803e-02, -1.7379e-04, 2.8831e-02],\n",
- " [-2.3304e-02, -1.4651e-02, 2.0540e-03, 6.7600e-03, -2.2979e-02],\n",
- " [-2.8824e-02, 2.5435e-02, 2.3059e-02, 2.0000e-03, -2.6226e-02]],\n",
- "\n",
- " [[-3.8041e-03, 1.3903e-02, -2.4387e-02, -6.0695e-03, -1.2511e-02],\n",
- " [-2.3270e-02, 1.7635e-02, 9.2290e-03, 3.1794e-02, -1.5929e-03],\n",
- " [-3.1804e-02, -1.5838e-02, -7.3459e-03, 1.6185e-02, 2.6591e-02],\n",
- " [-7.9933e-03, -2.6467e-03, -1.7165e-02, 1.1167e-02, 1.2200e-02],\n",
- " [-2.1517e-02, -1.5859e-02, -2.5180e-02, -1.4661e-02, -2.9686e-02]]]])), ('conv2.bias', tensor([-0.0089, -0.0188, -0.0332, 0.0145, 0.0114, 0.0143, -0.0350, 0.0262,\n",
- " -0.0120, -0.0293, -0.0241, 0.0296, 0.0040, 0.0037, -0.0102, -0.0286,\n",
- " 0.0114, 0.0021, 0.0105, 0.0194, 0.0032, -0.0117, 0.0232, 0.0098,\n",
- " 0.0349, 0.0020, -0.0103, -0.0307, 0.0153, 0.0227, 0.0066, 0.0023,\n",
- " -0.0033, 0.0143, -0.0275, 0.0305, 0.0050, -0.0263, -0.0068, 0.0017,\n",
- " 0.0258, 0.0263, -0.0047, 0.0063, 0.0233, -0.0141, -0.0251, 0.0072,\n",
- " 0.0058, -0.0183, -0.0226, -0.0204, 0.0080, -0.0164, 0.0317, -0.0037,\n",
- " -0.0171, -0.0219, 0.0041, 0.0267, -0.0242, -0.0056, 0.0006, 0.0317])), ('fc1.weight', tensor([[-0.0071, 0.0033, -0.0022, ..., -0.0169, -0.0172, 0.0034],\n",
- " [ 0.0109, -0.0090, 0.0169, ..., 0.0074, -0.0104, 0.0056],\n",
- " [ 0.0113, -0.0158, -0.0173, ..., -0.0151, -0.0095, 0.0036],\n",
+ " [[ 2.0920e-02, -2.8072e-02, 2.0046e-02, 2.1542e-02, 2.8214e-02],\n",
+ " [-1.4556e-02, -2.8212e-02, -8.9851e-03, -3.3224e-02, 2.4021e-02],\n",
+ " [-2.6013e-02, -3.1922e-02, -1.5481e-04, -1.2796e-02, 5.5097e-03],\n",
+ " [ 3.1735e-02, 2.0218e-02, 2.9766e-02, 2.7779e-02, 3.0098e-02],\n",
+ " [ 1.8398e-03, -2.1543e-02, -2.9273e-02, -5.8921e-03, 1.6662e-02]],\n",
+ "\n",
+ " [[ 2.8385e-02, -1.8564e-02, -6.6080e-03, 2.5015e-02, -3.3667e-03],\n",
+ " [-1.9641e-02, -3.4182e-02, 2.0578e-02, -2.0450e-02, 3.3780e-03],\n",
+ " [ 6.3422e-04, 2.6127e-02, 1.1615e-02, 2.5706e-02, -2.4499e-02],\n",
+ " [ 1.9641e-02, 3.2078e-02, -2.9023e-02, -3.4537e-02, 1.1839e-02],\n",
+ " [-1.1807e-03, 3.3522e-02, -2.9450e-02, -3.3327e-02, -3.3981e-02]],\n",
+ "\n",
+ " [[-2.3388e-03, -8.2398e-03, -1.6055e-02, -1.2572e-03, -1.9137e-02],\n",
+ " [-2.5775e-02, 1.8130e-03, -4.7393e-04, 1.8243e-02, -1.0023e-02],\n",
+ " [ 8.7671e-03, -2.4885e-02, -2.3222e-02, 3.0048e-02, -2.0407e-02],\n",
+ " [-2.8137e-02, 3.1120e-02, -7.6599e-03, -1.9271e-02, 2.2285e-02],\n",
+ " [-2.9455e-02, 1.2270e-02, -2.2933e-02, 6.5161e-03, 2.0707e-02]]]]), 'conv2.bias': tensor([-0.0294, 0.0329, 0.0288, 0.0177, -0.0267, 0.0292, -0.0254, 0.0350,\n",
+ " 0.0102, 0.0154, 0.0301, 0.0296, 0.0310, -0.0298, 0.0040, 0.0274,\n",
+ " 0.0159, 0.0237, -0.0041, 0.0274, 0.0122, -0.0251, 0.0142, 0.0245,\n",
+ " 0.0126, 0.0059, 0.0148, 0.0251, 0.0234, 0.0009, -0.0098, -0.0203,\n",
+ " 0.0108, -0.0250, 0.0113, 0.0071, 0.0188, 0.0034, 0.0039, -0.0132,\n",
+ " 0.0325, 0.0291, -0.0115, 0.0208, 0.0073, -0.0019, 0.0264, -0.0297,\n",
+ " -0.0012, -0.0327, -0.0204, -0.0143, -0.0182, 0.0242, 0.0229, -0.0135,\n",
+ " -0.0017, 0.0063, 0.0077, -0.0157, -0.0293, 0.0144, 0.0262, 0.0104]), 'fc1.weight': tensor([[-0.0081, 0.0138, -0.0154, ..., 0.0130, 0.0123, 0.0151],\n",
+ " [-0.0053, 0.0166, -0.0099, ..., -0.0101, -0.0069, -0.0051],\n",
+ " [-0.0101, 0.0112, -0.0009, ..., 0.0026, -0.0106, 0.0138],\n",
" ...,\n",
- " [-0.0174, -0.0122, 0.0140, ..., -0.0145, -0.0094, 0.0060],\n",
- " [-0.0027, 0.0069, -0.0158, ..., -0.0118, 0.0147, -0.0022],\n",
- " [-0.0161, -0.0009, -0.0035, ..., -0.0114, -0.0134, 0.0092]])), ('fc1.bias', tensor([ 1.0599e-02, -8.6450e-03, -6.3942e-03, -1.6975e-02, 9.9938e-03,\n",
- " 1.9097e-03, -1.0315e-02, -1.3646e-02, -8.1271e-03, 9.0041e-03,\n",
- " -1.5887e-02, -8.1938e-03, 2.3270e-03, 6.1815e-03, 1.3092e-02,\n",
- " -1.6892e-02, 7.6708e-03, 5.4282e-03, -1.5561e-02, -3.7766e-03,\n",
- " -1.5642e-02, -8.5728e-03, -8.8577e-03, -3.0399e-03, -8.2830e-04,\n",
- " 1.0327e-02, 1.3440e-02, -6.5937e-03, -1.1239e-02, -1.4882e-05,\n",
- " 3.3315e-03, 1.4572e-02, 1.0429e-02, 3.8221e-03, 1.5226e-02,\n",
- " -7.9018e-03, -6.1310e-03, 7.9535e-03, -1.7202e-04, 1.1906e-02,\n",
- " -1.4496e-03, -5.4891e-03, -1.7822e-02, 4.6960e-03, 2.4820e-03,\n",
- " 9.9257e-03, 2.6597e-03, -1.6335e-02, -8.0572e-03, -1.6191e-02,\n",
- " 2.6107e-03, -8.7351e-03, 1.2610e-02, -2.6491e-03, 3.7665e-03,\n",
- " 1.7175e-02, -6.5901e-03, -9.9649e-03, 2.9988e-03, -1.7338e-02,\n",
- " 1.6825e-02, -1.1604e-02, -4.9108e-03, -2.1019e-03, 1.2322e-02,\n",
- " -8.7332e-03, 1.6764e-02, -1.3749e-02, -2.0282e-03, -1.3290e-03,\n",
- " 1.3664e-02, 5.7036e-03, 1.5984e-03, -1.0168e-02, -4.8652e-03,\n",
- " 8.3150e-03, 6.2086e-03, 4.7627e-03, 1.3689e-02, 1.4757e-02,\n",
- " -9.3733e-03, -1.5374e-02, 1.5027e-02, 4.3609e-03, -1.0545e-02,\n",
- " -5.0889e-03, -1.7105e-02, -1.7145e-02, -1.1442e-02, -6.1340e-03,\n",
- " 8.5078e-04, -9.6481e-03, -1.3213e-02, 5.9745e-03, -1.1376e-02,\n",
- " 3.3183e-03, 1.6145e-02, 2.4235e-03, 1.6919e-02, 1.5337e-02,\n",
- " -1.1545e-02, -1.0109e-02, 2.0069e-03, -1.6511e-02, 1.3294e-02,\n",
- " -1.5669e-02, -3.9068e-03, 1.8742e-03, -9.1673e-03, 1.1506e-03,\n",
- " -1.4879e-02, 1.0596e-02, -9.0080e-03, 1.0127e-02, -1.4706e-02,\n",
- " 1.5415e-02, -1.7710e-02, 1.1429e-02, -1.5419e-02, 6.1092e-03,\n",
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+ " -1.6927e-02, -1.1344e-02, -1.1302e-02, -1.5232e-02, 1.3569e-02,\n",
+ " -3.4408e-03, -1.4370e-02, 1.5899e-02, 5.6999e-03, 2.5900e-03,\n",
+ " -9.2822e-03, -4.7884e-03, 1.2711e-02, 1.4953e-02, -9.6008e-03,\n",
+ " -7.8154e-03, 2.3049e-03, -7.2286e-03, 3.4406e-03, -1.4979e-02,\n",
+ " 1.3255e-02, -1.5416e-02, 4.7037e-03, -6.2464e-05, 6.1763e-03,\n",
+ " -1.7083e-02, -4.1979e-03, 4.8330e-03, 1.6848e-02, -5.8141e-03,\n",
+ " 1.0530e-02, 1.2660e-02, 7.7921e-03, 1.2516e-02, -8.2558e-03,\n",
+ " 9.6033e-03, 7.4281e-04, 1.6809e-02, -1.2299e-02, 1.1192e-02,\n",
+ " -1.2419e-02, 1.7704e-02, -2.2003e-03, -5.5301e-03, -1.1976e-02,\n",
+ " -7.5681e-03, 1.7068e-02, 1.3416e-02, 1.0705e-02, -1.8727e-03,\n",
+ " 1.1100e-02, 1.7324e-02, 4.0332e-03, 5.9611e-04, 1.3360e-02,\n",
+ " 1.2185e-02, 7.5230e-03, 1.5142e-02, 1.4654e-02, 1.2797e-02,\n",
+ " 1.6562e-02, 5.9504e-03, 6.2322e-03, 1.6638e-02, 3.0088e-04,\n",
+ " -1.5574e-02, 1.0657e-02, -5.7672e-03, 1.6510e-02, -1.1042e-02,\n",
+ " -1.4875e-02, 1.5410e-02, -1.6385e-02, -1.1161e-03, 7.7549e-03,\n",
+ " 1.1378e-02, 1.0371e-02, -2.7560e-03, 1.3848e-02, -1.2284e-02,\n",
+ " -2.9374e-03, 1.0240e-02, -1.2988e-02, -8.2888e-03, -1.4185e-02,\n",
+ " -1.2491e-02, -7.7231e-03, 1.1543e-02, 1.4141e-02, 6.7815e-03,\n",
+ " 1.4062e-02, 5.3020e-04, 5.9166e-03, 7.7286e-03, 8.2705e-03,\n",
+ " 1.2781e-03, -1.4400e-02]), 'fc2.weight': tensor([[ 0.0173, -0.0204, -0.0246, ..., -0.0214, 0.0191, 0.0375],\n",
+ " [ 0.0109, -0.0418, -0.0442, ..., -0.0027, 0.0389, 0.0407],\n",
+ " [ 0.0440, 0.0031, -0.0332, ..., 0.0294, -0.0359, -0.0237],\n",
" ...,\n",
- " [ 0.0134, -0.0336, -0.0370, ..., -0.0342, 0.0213, 0.0314],\n",
- " [ 0.0109, 0.0286, -0.0269, ..., -0.0081, 0.0009, -0.0038],\n",
- " [-0.0080, 0.0278, 0.0083, ..., 0.0007, 0.0084, -0.0251]])), ('fc2.bias', tensor([ 2.2357e-02, 1.9226e-02, 1.1123e-02, -2.4498e-03, -1.6226e-02,\n",
- " 3.9878e-02, -3.7970e-02, 2.9134e-02, 1.5137e-02, 3.2274e-02,\n",
- " -3.5957e-02, -2.9998e-02, 7.1591e-03, -2.9987e-02, -2.4313e-02,\n",
- " 4.2241e-02, 9.3610e-03, 1.5294e-02, -1.6146e-02, 3.7757e-02,\n",
- " 2.1120e-02, -3.7359e-03, -2.3047e-02, 6.2452e-04, -2.0957e-02,\n",
- " 3.2647e-02, 3.9253e-02, 2.0014e-02, -3.0535e-02, -1.6816e-02,\n",
- " -3.9067e-02, -1.2906e-02, -2.3393e-02, 4.3545e-02, -3.0294e-02,\n",
- " -1.3963e-02, 4.1285e-02, 3.9417e-02, 3.4044e-02, 2.5627e-02,\n",
- " -3.4948e-04, -1.9061e-05, 3.3105e-02, -3.3628e-02, 2.1815e-02,\n",
- " 2.9446e-02, 2.1422e-02, -1.4810e-03, 2.7396e-02, -1.2598e-02,\n",
- " 2.5633e-03, -3.4380e-02, -2.7923e-02, -2.9328e-03, 5.5454e-03,\n",
- " 1.7421e-02, -2.5213e-02, 6.5188e-03, 1.3223e-02, -2.5570e-02,\n",
- " -2.6113e-02, -8.3992e-03]))])\n",
- "o1_state_dict: {'state': {}, 'param_groups': [{'lr': 0.6, 'momentum': 0, 'dampening': 0, 'weight_decay': 0, 'nesterov': False, 'params': [0, 1, 2, 3, 4, 5, 6, 7]}]}\n"
+ " [-0.0346, -0.0161, 0.0228, ..., -0.0070, -0.0313, -0.0109],\n",
+ " [ 0.0340, -0.0133, -0.0414, ..., 0.0021, -0.0173, 0.0435],\n",
+ " [ 0.0281, -0.0380, 0.0440, ..., -0.0395, -0.0356, -0.0384]]), 'fc2.bias': tensor([ 0.0387, -0.0387, 0.0442, 0.0035, -0.0139, 0.0319, 0.0112, -0.0021,\n",
+ " 0.0198, -0.0422, -0.0340, -0.0312, -0.0236, 0.0207, -0.0330, -0.0092,\n",
+ " 0.0038, 0.0132, 0.0357, 0.0131, -0.0439, 0.0403, 0.0326, -0.0034,\n",
+ " 0.0372, -0.0296, -0.0147, -0.0009, 0.0266, -0.0027, -0.0150, 0.0015,\n",
+ " 0.0336, -0.0176, -0.0119, 0.0077, -0.0043, 0.0044, 0.0299, 0.0308,\n",
+ " -0.0223, -0.0223, 0.0140, 0.0130, -0.0155, 0.0175, -0.0068, 0.0380,\n",
+ " 0.0010, -0.0395, 0.0146, -0.0289, 0.0194, -0.0129, 0.0116, 0.0291,\n",
+ " -0.0225, -0.0211, 0.0376, 0.0088, -0.0227, -0.0254])}\n"
]
}
],
@@ -1160,8 +1154,19 @@
"from decentralizepy.datasets.Femnist import CNN\n",
"m1 = CNN()\n",
"o1 = torch.optim.SGD(m1.parameters(), 0.6)\n",
- "print(\"m1_state_dict: \", m1.state_dict())\n",
- "print(\"o1_state_dict: \", o1.state_dict())"
+ "print(\"m1_parameters: \", {k:v.data for k, v in zip(m1.state_dict(), m1.parameters())})\n",
+ "#print(\"m1_state_dict: \", m1.state_dict())\n",
+ "#print(\"o1_state_dict: \", o1.state_dict())\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "a = [(3, 2), (2, 5), (2, 6)]\n",
+ "a.sort(reverse = True)\n"
]
},
{
diff --git a/eval/testing.py b/eval/testing.py
index dd52c2bcac1864ce1df9a6354b36153a5ed70fde..459c1de1ce2a78be8a74459a02e34f98954de9ae 100644
--- a/eval/testing.py
+++ b/eval/testing.py
@@ -39,7 +39,13 @@ if __name__ == "__main__":
args = parser.parse_args()
Path(args.log_dir).mkdir(parents=True, exist_ok=True)
- log_level = {"INFO": logging.INFO, "DEBUG": logging.DEBUG, "WARNING": logging.WARNING, "ERROR": logging.ERROR, "CRITICAL": logging.CRITICAL}
+ log_level = {
+ "INFO": logging.INFO,
+ "DEBUG": logging.DEBUG,
+ "WARNING": logging.WARNING,
+ "ERROR": logging.ERROR,
+ "CRITICAL": logging.CRITICAL,
+ }
config = read_ini(args.config_file)
my_config = dict()
@@ -56,5 +62,13 @@ if __name__ == "__main__":
mp.spawn(
fn=Node,
nprocs=procs_per_machine,
- args=[m_id, l, g, my_config, args.iterations, args.log_dir, log_level[args.log_level]],
+ args=[
+ m_id,
+ l,
+ g,
+ my_config,
+ args.iterations,
+ args.log_dir,
+ log_level[args.log_level],
+ ],
)
diff --git a/src/decentralizepy/datasets/Femnist.py b/src/decentralizepy/datasets/Femnist.py
index 13cbff27c335ee060233007f93c0de4981ebf673..ec53d32de579426dd6b9cd4f2c9f6cb4ec469150 100644
--- a/src/decentralizepy/datasets/Femnist.py
+++ b/src/decentralizepy/datasets/Femnist.py
@@ -7,14 +7,13 @@ import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn.functional as F
-import torchvision
from torch import nn
-from torch._C import ParameterDict
from torch.utils.data import DataLoader
from decentralizepy.datasets.Data import Data
from decentralizepy.datasets.Dataset import Dataset
from decentralizepy.datasets.Partitioner import DataPartitioner
+from decentralizepy.models.Model import Model
NUM_CLASSES = 62
IMAGE_SIZE = (28, 28)
@@ -290,7 +289,7 @@ class Femnist(Dataset):
logging.info("Evaluating complete.")
-class LogisticRegression(nn.Module):
+class LogisticRegression(Model):
"""
Class for a Logistic Regression Neural Network for FEMNIST
"""
@@ -320,7 +319,7 @@ class LogisticRegression(nn.Module):
return x
-class CNN(nn.Module):
+class CNN(Model):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(1, 32, 5, padding=2)
diff --git a/src/decentralizepy/graphs/FullyConnected.py b/src/decentralizepy/graphs/FullyConnected.py
new file mode 100644
index 0000000000000000000000000000000000000000..d235f7e5917e60b1a4290736af771793c27e070a
--- /dev/null
+++ b/src/decentralizepy/graphs/FullyConnected.py
@@ -0,0 +1,20 @@
+from decentralizepy.graphs.Graph import Graph
+
+
+class FullyConnected(Graph):
+ """
+ The class for generating a Fully Connected Graph Topology
+ """
+
+ def __init__(self, n_procs):
+ """
+ Constructor. Generates a Fully Connected graph
+ Parameters
+ ----------
+ n_procs : int
+ total number of nodes in the graph
+ """
+ super().__init__(n_procs)
+ for node in range(n_procs):
+ neighbors = set([x for x in range(n_procs) if x != node])
+ self.adj_list[node] = neighbors
diff --git a/src/decentralizepy/graphs/Ring.py b/src/decentralizepy/graphs/Ring.py
new file mode 100644
index 0000000000000000000000000000000000000000..c502cf330a4df4dea84715763d32647b5fe51d2b
--- /dev/null
+++ b/src/decentralizepy/graphs/Ring.py
@@ -0,0 +1,18 @@
+from decentralizepy.graphs.Graph import Graph
+
+
+class Ring(Graph):
+ """
+ The class for generating a Ring topology
+ """
+
+ def __init__(self, n_procs):
+ """
+ Constructor. Generates a Ring graph
+ Parameters
+ ----------
+ n_procs : int
+ total number of nodes in the graph
+ """
+ super().__init__(n_procs)
+ self.connect_graph()
diff --git a/src/decentralizepy/models/Model.py b/src/decentralizepy/models/Model.py
new file mode 100644
index 0000000000000000000000000000000000000000..befc93289d8a4ac105e878ff5a567d90aaba03f7
--- /dev/null
+++ b/src/decentralizepy/models/Model.py
@@ -0,0 +1,7 @@
+from torch import nn
+
+
+class Model(nn.Module):
+ def __init__(self):
+ super().__init__()
+ self.accumulated_gradients = []
diff --git a/src/decentralizepy/models/__init__.py b/src/decentralizepy/models/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/src/decentralizepy/sharing/PartialModel.py b/src/decentralizepy/sharing/PartialModel.py
index 7702d2ebad2a8e6cd7565c43e284c1fa043492b9..46ba8cf721eb7b45b40b93a9744641c444e00f24 100644
--- a/src/decentralizepy/sharing/PartialModel.py
+++ b/src/decentralizepy/sharing/PartialModel.py
@@ -1,6 +1,58 @@
+import json
+import math
+
+import numpy
+import torch
+
from decentralizepy.sharing.Sharing import Sharing
+
class PartialModel(Sharing):
- def __init__(self, rank, machine_id, communication, mapping, graph, model, dataset):
- super().__init__(rank, machine_id, communication, mapping, graph, model, dataset)
-
+ def __init__(
+ self, rank, machine_id, communication, mapping, graph, model, dataset, alpha=1.0
+ ):
+ super().__init__(
+ rank, machine_id, communication, mapping, graph, model, dataset
+ )
+ self.alpha = alpha
+
+ def extract_sorted_gradients(self):
+ assert len(self.model.accumulated_gradients) > 0
+ gradient_sum = self.model.accumulated_gradients[0]
+ for i in range(1, len(self.model.accumulated_gradients)):
+ for key in self.model.accumulated_gradients[i]:
+ gradient_sum[key] += self.model.accumulated_gradients[i][key]
+ gradient_sequence = []
+
+ for key, gradient in gradient_sum.items():
+ for index, val in enumerate(torch.flatten(gradient)):
+ gradient_sequence.append((val, key, index))
+
+ gradient_sequence.sort()
+ return gradient_sequence
+
+ def serialized_model(self):
+ gradient_sequence = self.extract_sorted_gradients()
+ gradient_sequence = gradient_sequence[
+ : math.round(len(gradient_sequence) * self.alpha)
+ ]
+
+ m = dict()
+ for _, key, index in gradient_sequence:
+ if key not in m:
+ m[key] = []
+ m[key].append(index, torch.flatten(self.model.state_dict()[key])[index])
+
+ for key in m:
+ m[key] = json.dumps(m[key])
+
+ return m
+
+ def deserialized_model(self, m):
+ state_dict = self.model.state_dict()
+
+ for key, value in m.items():
+ for index, param_val in json.loads(value):
+ torch.flatten(state_dict[key])[index] = param_val
+ state_dict[key] = torch.from_numpy(numpy.array(json.loads(value)))
+ return state_dict
diff --git a/src/decentralizepy/training/GradientAccumulator.py b/src/decentralizepy/training/GradientAccumulator.py
new file mode 100644
index 0000000000000000000000000000000000000000..727f6519092da3c46f2d0a9445618c6b3b35e703
--- /dev/null
+++ b/src/decentralizepy/training/GradientAccumulator.py
@@ -0,0 +1,40 @@
+import logging
+
+from decentralizepy.training.Training import Training
+
+
+class GradientAccumulator(Training):
+ def __init__(
+ self, model, optimizer, loss, epochs_per_round="", batch_size="", shuffle=""
+ ):
+ super().__init__()
+
+ def train(self, dataset):
+ """
+ One training iteration with accumulation of gradients in model.accumulated_gradients
+ Parameters
+ ----------
+ dataset : decentralizepy.datasets.Dataset
+ The training dataset. Should implement get_trainset(batch_size, shuffle)
+ """
+ trainset = dataset.get_trainset(self.batch_size, self.shuffle)
+ self.model.accumulated_gradients = []
+
+ for epoch in range(self.epochs_per_round):
+ epoch_loss = 0.0
+ count = 0
+ for data, target in trainset:
+ self.model.zero_grad()
+ output = self.model(data)
+ loss_val = self.loss(output, target)
+ epoch_loss += loss_val.item()
+ loss_val.backward()
+ self.model.accumulated_gradients.append(
+ grad_dict={
+ k: v.grad.clone().detach()
+ for k, v in zip(self.model.state_dict(), self.parameters())
+ }
+ )
+ self.optimizer.step()
+ count += 1
+ logging.info("Epoch: {} loss: {}".format(epoch, epoch_loss / count))
diff --git a/src/decentralizepy/training/Training.py b/src/decentralizepy/training/Training.py
index 4f4095cc08712a0d0f968ff893bc83a4ed6553be..82f1151c462e6aa1eb0f587095f8410475824ca8 100644
--- a/src/decentralizepy/training/Training.py
+++ b/src/decentralizepy/training/Training.py
@@ -2,8 +2,6 @@ import logging
import matplotlib.pyplot as plt
import numpy as np
-import torch
-import torchvision
from decentralizepy import utils
@@ -38,11 +36,6 @@ class Training:
self.batch_size = utils.conditional_value(batch_size, "", int(1))
self.shuffle = utils.conditional_value(shuffle, "", False)
- def imshow(self, img):
- npimg = img.numpy()
- plt.imshow(np.transpose(npimg, (1, 2, 0)))
- plt.show()
-
def reset_optimizer(self, optimizer):
self.optimizer = optimizer
@@ -56,12 +49,6 @@ class Training:
"""
trainset = dataset.get_trainset(self.batch_size, self.shuffle)
- # dataiter = iter(trainset)
- # images, labels = dataiter.next()
- # self.imshow(torchvision.utils.make_grid(images[:16]))
- # plt.savefig(' '.join('%5s' % j for j in labels) + ".png")
- # print(' '.join('%5s' % j for j in labels[:16]))
-
for epoch in range(self.epochs_per_round):
epoch_loss = 0.0
count = 0