jatinshah / ufldl_tutorial Goto Github PK

File "........\load_MNIST.py", line 18, in load_MNIST_images
images = images.reshape((num_images, num_rows * num_cols)).transpose()
ValueError: total size of new array must be unchanged

I modified train.py like this to do sample image exercise:
"
visible_size = 8 * 8
hidden_size = 25
......

patches = sample_images.sample_images()
"
but I got wrong output, any suggestion? Thank you!
I also tried
"
sparsity_param = 0.01
lambda_ = 1e-3
beta = 3
"
like what ufldl tutorial suggested, but the output is still wrong!

In calculating the gradient, you only consider take derivatives to the z2, but not taking the sparsity loss into consideration.

Hi guys,,

have you the problem of terrified slow computation when run the line

num_grad = gradient.compute_gradient(J, theta) % line 101 in train.py

It has already taken more than 12 hours and only finished 34700 inputs.
Do I run the code not in a right way? Thanks

Matlab mnist images are stored column major order, whereas this version stores them in row major. This means that when transferring weights between Python and Matlab implementations, you need to reshape/transpose/flatten each row of the first layer weights matrix

dad's kiiiii

In section Recovering an Approximation of the Data, isn't a vector?

If so, why do we get:

You should add a np.sqrt above s+epsilon like below.

(u, s, vt) = np.linalg.svd(sigma)
zca_white = u.dot(np.diag(1 / np.sqrt(s + epsilon))).dot(u.transpose())

when I run the train.py,I get the following error
images = images.reshape((num_images[0], num_rows[0] * num_cols[0])).transpose()
Traceback (most recent call last):
File "/home/snow/Documents/study/ufldl_tutorial/train.py", line 42, in
images = load_MNIST.load_MNIST_images('data/mnist/train-images-idx3-ubyte')
File "/home/snow/Documents/study/ufldl_tutorial/load_MNIST.py", line 20, in load_MNIST_images
images = images.reshape((num_images[0], num_rows[0] * num_cols[0])).transpose()
ValueError: cannot reshape array of size 9912406 into shape (2055376946,1902539786)

#####code begin
with open(filename, "rb") as f:
magic = np.fromfile(f, dtype=np.dtype('>i4'), count=1)

    num_images = np.fromfile(f, dtype=np.dtype('>i4'), count=1)
    num_rows = np.fromfile(f, dtype=np.dtype('>i4'), count=1)
    num_cols = np.fromfile(f, dtype=np.dtype('>i4'), count=1)
    #num_images = 60000
    #num_rows = 28
    #num_cols = 28
    images = np.fromfile(f, dtype=np.ubyte)
    images = images.reshape((num_images[0], num_rows[0] * num_cols[0])).transpose()
    images = images.astype(np.float64) / 255

    f.close()

#####code end

I google the http://yann.lecun.com/exdb/mnist/
find the value:
0004 32 bit integer 60000 number of images
0008 32 bit integer 28 number of rows
0012 32 bit integer 28 number of columns

by calculating the value, I find 282860000 larger than the 9912422,that makes me so confused,
How can I correct the code?