how to print all parameters of a keras model

I am trying to print all the 1290 parameters in dense_1 layer, but model.get_weights()[7] only show 10 parameters. How could I print all the 1290 parameters of dense_1 layer? What is the difference between model.get_weights() and model.layer.get_weights()

>model.get_weights()[7]
array([-2.8552295e-04, -4.3254648e-03, -1.8752701e-04,  2.3482188e-03,
       -3.4848123e-04,  7.6121779e-04, -2.7494309e-06, -1.9068648e-03,
        6.0777756e-04,  1.9550985e-03], dtype=float32)

>model.summary()
Model: "sequential"
_________________________________________________________________
Layer (type)                Output Shape              Param #   
=================================================================
 conv2d (Conv2D)             (None, 26, 26, 32)        320       
                                                                 
 conv2d_1 (Conv2D)           (None, 24, 24, 64)        18496     
                                                                 
 max_pooling2d (MaxPooling2D  (None, 12, 12, 64)       0         
 )                                                               
                                                                 
 dropout (Dropout)           (None, 12, 12, 64)        0         
                                                                 
 flatten (Flatten)           (None, 9216)              0         
                                                                 
 dense (Dense)               (None, 128)               1179776   
                                                                 
 dropout_1 (Dropout)         (None, 128)               0         
                                                                 
 dense_1 (Dense)             (None, 10)                1290      
_________________________________________________________________
                                                                 
=================================================================
Total params: 1,199,882
Trainable params: 1,199,882
Non-trainable params: 0
_________________________________________________________________
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