Manipulating pretrained layers of convnet in Tensorflow
<p>I am learning convolutional networks in Tensorflow. I wonder if there is any tutorials of using TF to investigate a pre-trained convnet model, like these excellent tutorials for Caffe: <a href="http://nbviewer.jupyter.org/github/BVLC/caffe/blob/master/examples/00-classification.ipynb" rel="nofollow">this</a> and <a href="http://nbviewer.jupyter.org/github/BVLC/caffe/blob/master/examples/net_surgery.ipynb" rel="nofollow">this</a>. I mean, how to access middle layers, get its learned parameters and blobs, to customize input shape to accept arbitrary image size or batch size, etc.</p>