Hello,
l tried the following and l get stuck at visualizing the features of my model.
 my_model=torch.load(my_pre_trained_mode)
    my_model.keys()
    ['cnn.conv0.weight',
     'cnn.conv0.bias',
     'cnn.conv1.weight',
     'cnn.conv1.bias',
     'cnn.conv2.weight',
     'cnn.conv2.bias',
     'cnn.batchnorm2.weight',
     'cnn.batchnorm2.bias',
     'cnn.batchnorm2.running_mean',
     'cnn.batchnorm2.running_var',
     'cnn.conv3.weight',
     'cnn.conv3.bias',
     'cnn.conv4.weight',
     'cnn.conv4.bias',
     'cnn.batchnorm4.weight',
     'cnn.batchnorm4.bias',
     'cnn.batchnorm4.running_mean',
     'cnn.batchnorm4.running_var',
     'cnn.conv5.weight',
     'cnn.conv5.bias',
     'cnn.conv6.weight',
     'cnn.conv6.bias',
     'cnn.batchnorm6.weight',
     'cnn.batchnorm6.bias',
     'cnn.batchnorm6.running_mean',
     'cnn.batchnorm6.running_var',
     'rnn.0.rnn.weight_ih_l0',
     'rnn.0.rnn.weight_hh_l0',
     'rnn.0.rnn.bias_ih_l0',
     'rnn.0.rnn.bias_hh_l0',
     'rnn.0.rnn.weight_ih_l0_reverse',
     'rnn.0.rnn.weight_hh_l0_reverse',
     'rnn.0.rnn.bias_ih_l0_reverse',
     'rnn.0.rnn.bias_hh_l0_reverse',
     'rnn.0.embedding.weight',
     'rnn.0.embedding.bias',
     'rnn.1.rnn.weight_ih_l0',
     'rnn.1.rnn.weight_hh_l0',
     'rnn.1.rnn.bias_ih_l0',
     'rnn.1.rnn.bias_hh_l0',
     'rnn.1.rnn.weight_ih_l0_reverse',
     'rnn.1.rnn.weight_hh_l0_reverse',
     'rnn.1.rnn.bias_ih_l0_reverse',
     'rnn.1.rnn.bias_hh_l0_reverse',
     'rnn.1.embedding.weight',
     'rnn.1.embedding.bias']

    conv0=my_moel.get('cnn.conv0.weight')
    ...
    (63,0 ,.,.) = 
      0.5229 -1.4523  1.0662
      0.1048 -1.8494  1.5810
     -0.4727 -1.4437  1.9553
    [torch.FloatTensor of size 64x1x3x3]


    rnn=my_mode.get('rnn.1.embedding.weight')
    [torch.FloatTensor of size 37x512]

How can l visualize the weights of each layer for instance cnn.conv0 and rnn.1 ?
Thank you