This is a question not an issue.
I don't know if I can write my question here or not.
I am very new to all deep learning as well as using python.
I apologize if my question is very simple or not smart.

So I run the dA.py code and it works fine.
I am trying to run the dA on just a single image (my image is not a binary image and its size is 28*28) and visualize my hidden layer (weights) and see the reconstructed image as well.
first I'd like to run it of dA and then on sda (stacked ae) and visualize all the layers.
I really appreciate it someone can help me. please let me know if I need to ask my question somewhere else.

Here is the code that I write so far:

import PIL.Image as Image
import dA
rng = dA.numpy.random.RandomState(123)
theano_rng = dA.RandomStreams(rng.randint(2 ** 30))
Img2 = dA.Image.open("fruits.jpg").convert('LA')
index = dA.T.lscalar()  # index to a [mini]batch
x = dA.T.matrix('x')

da = dA.dA(
    numpy_rng=rng,
    theano_rng=theano_rng,
    input=Img2,
    n_visible=28 * 28,
    n_hidden=500
)

so it works fine without any error, but I dont know what to do next.