我有一个用 Keras 编写的具有 (8,5,5,5,32) 个神经元的神经网络模型，如下所示：
# Sequential
model = Sequential()
# Neural network
model.add(Dense(5, input_dim=len(X[0]), activation='sigmoid' ))
model.add(Dense(5, activation='sigmoid' ))
model.add(Dense(5, activation='sigmoid' ))
model.add(Dense(len(y[0]), activation='sigmoid' ))
# Compile model
# sgd = optimizers.SGD(lr=0.01, decay=0.0, momentum=0.0, nesterov=False)
model.compile(loss='mean_squared_error', optimizer='adam', metrics=['acc'])
# Fit model
history = model.fit(X, y, nb_epoch=200, validation_split=0.2, batch_size=30)
当我在训练后访问权重时，我得到：
model.get_weights()
它返回一个长数组，对应于每层神经元之间的权重。我不明白的是较小的数组表示（与每层的神经元数量相同的权重数量）在较大的数组（与每层的神经元数量相同的子阵列数量）之间。
这是神经元所经历的偏差吗？
以下是“model.get_weights()”的结果：
[array([[ 0.31680015, 0.22357693, -0.63079047, -0.04600599, -0.26949674],
[ 0.0525099 , -0.41120723, 0.28259486, -0.37071031, 0.42028651],
[ 0.35435981, -0.35501873, -0.05099263, 0.3633016 , -0.64845532],
[ 0.60027206, 0.40594664, 0.29894602, -0.13255124, 0.52797431],
[-0.32299024, 0.54219592, 0.34114835, -0.59672344, -0.47126439],
[-0.51338726, 0.64451784, -0.35283062, 0.47248691, -0.31077194],
[-0.59289241, -0.207461 , 0.00371859, -0.52090681, 0.10946763],
[-0.37216368, -0.23905358, -0.38580573, 0.0401655 , -0.34231418]], dtype=float32),
array([-0.03448975, 0.04991768, 0.11635038, -0.04274927, 0.0325128 ], dtype=float32), # WHAT IS THIS ARRAY REPRESENTING?
array([[ 0.10943446, -0.24749899, 0.58269709, 0.54208171, -0.05888808],
[ 0.02320727, 0.08465887, -0.79114383, -0.19608408, 0.55898732],
[-0.81141329, 0.19124934, -0.69268334, -0.44021448, 0.72605485],
[ 0.32895803, 0.08196118, 0.53820646, 0.6348688 , -0.06715827],
[-0.0850288 , 0.5077976 , 0.36972848, 0.44874495, 0.36402631]], dtype=float32),
array([-0.30626452, 0.15301916, -0.17855364, 0.12410269, 0.2502442 ], dtype=float32),
array([[-0.31872895, -0.46534333, -0.4664084 , -0.23720025, 0.30465502],
[-0.37690881, -0.00396255, 0.38115206, 1.20845091, 0.69348788],
[ 0.15064301, -0.29923961, 0.13108611, -0.29579154, -0.34181508],
[ 0.62893951, 0.49498206, 0.02549251, 0.6561147 , -0.52280194],
[ 1.07029617, 0.66126752, 0.50944209, 0.58811921, -0.04030331]], dtype=float32),
array([ 0.57747394, 0.59574115, 0.68391681, 0.78335029, 0.26046163], dtype=float32),
array([[ -1.09961331e+00, -7.06328213e-01, -7.93772519e-01,
-5.50112486e-01, -5.05448937e-01, -4.78618711e-01,
-3.32313687e-01, -5.46549559e-01, 3.88661295e-01,
3.64094585e-01, -1.93489313e-01, -7.61669278e-02,
1.23761639e-01, 4.93125141e-01, 4.78168607e-01,
-7.07402304e-02, -2.54306406e-01, -2.37895012e-01,
-1.36467636e-01, -7.16407061e-01, 1.32701367e-01,
-4.23079096e-02, -4.71717492e-03, 2.56372184e-01,
1.89603701e-01, 2.20276624e-01, -2.55215704e-01,
-1.04997739e-01, 2.81909049e-01, -7.00806752e-02,
2.99933195e-01, 3.84294897e-01],
[ -9.60830688e-01, -6.18087530e-01, -8.46309483e-01,
-6.05162561e-01, -2.39057451e-01, 3.03133931e-02,
-2.07459703e-01, -6.84834659e-01, 3.47823203e-01,
-6.44357502e-02, 2.55657077e-01, -2.37801671e-01,
2.57411227e-02, -1.01771923e-02, -6.76048512e-04,
3.06296106e-02, 2.05646217e-01, 8.02281871e-02,
-4.01538044e-01, -5.49115181e-01, 3.00252885e-01,
3.31445992e-01, -1.75046876e-01, -3.36513370e-01,
1.65666446e-01, 1.74015135e-01, -2.15066984e-01,
3.79294544e-01, 1.67991996e-01, 2.39770293e-01,
-5.49201332e-02, -1.67401493e-01],
[ -1.24525476e+00, -5.97414970e-01, -1.36500984e-01,
-5.60880482e-01, -4.26550537e-01, 1.46522000e-01,
-6.26730978e-01, -8.33723724e-01, -2.20034972e-01,
3.54697943e-01, 2.86612272e-01, 2.60758907e-01,
-5.10771237e-02, 1.91444799e-01, 3.32518548e-01,
1.51452944e-01, -2.18744278e-01, -2.07690187e-02,
9.60563496e-02, -2.26809219e-01, 8.80904198e-02,
2.33646557e-01, 2.45599806e-01, 2.53560930e-01,
1.55982673e-01, 6.49829209e-01, -1.26019821e-01,
5.47675073e-01, 3.28564644e-01, 8.67465809e-02,
-1.40921310e-01, -2.35581279e-01],
[ -1.51756608e+00, -1.11596704e+00, -4.97624874e-01,
-4.95555460e-01, -4.83801186e-01, -2.23367065e-01,
-1.08115244e+00, -9.68795598e-01, 4.32208836e-01,
1.16957083e-01, -1.02919623e-01, -8.19303747e-03,
4.21310306e-01, 1.09493546e-01, 1.54512182e-01,
-1.46762207e-01, 1.58293337e-01, -3.95552874e-01,
-2.07770184e-01, -1.90177709e-01, 2.07072627e-02,
6.61122620e-01, 5.44478893e-01, -1.46910429e-01,
4.22070086e-01, 2.49319345e-01, 6.19665794e-02,
9.74300727e-02, 3.37298632e-01, 2.90907085e-01,
8.78930092e-02, 1.25872776e-01],
[ -7.40014732e-01, -7.02967405e-01, -1.42469540e-01,
1.66655079e-01, -1.59682855e-01, -2.07361296e-01,
-9.04432237e-02, -1.22986667e-01, -3.28961462e-01,
9.21192244e-02, -2.13514805e-01, -1.59033865e-01,
-2.79709876e-01, -1.64602488e-01, 1.96248814e-01,
-1.98676869e-01, 2.80951142e-01, -4.50290412e-01,
2.34707281e-01, -3.13370705e-01, -2.24865358e-02,
2.63352484e-01, 4.90205318e-01, 1.96813330e-01,
4.13736820e-01, 7.11815134e-02, -1.92510381e-01,
5.77223562e-02, -4.25750390e-02, -3.79479416e-02,
6.17611647e-01, 3.11740283e-02]], dtype=float32),
array([-1.66324592, -1.4556272 , -1.10267663, -0.52273899, -0.59953606,
-0.52498704, -1.15079761, -1.19500864, 0.13858946, -0.01602219,
0.02289196, 0.2923668 , 0.14240141, 0.19787838, 0.15867165,
0.24876554, 0.21616565, -0.35774839, -0.40798596, -0.71499836,
0.36547631, 0.48771939, 0.40948448, 0.01851768, 0.56893039,
0.93250728, -0.32663229, 0.34419572, 0.15536141, 0.21145843,
0.53275597, 0.0364211 ], dtype=float32)]