Sanity Check for MNIST HDF5

We want to make sure that neon can correctly load the data from the HDF5 file.



In [32]:

    
from neon.data import HDF5Iterator  # Neon's HDF5 data loader
from neon.backends import gen_backend
import numpy as np



In [5]:

    
be = gen_backend(backend='cpu', batch_size=1)



In [6]:

    
outFilename = 'mnist_test.h5'  # The name of our HDF5 data file



In [7]:

    
train_set = HDF5Iterator(outFilename)



In [8]:

    
train_set.get_description()









    Out[8]:





{'config': {'hdf_filename': 'mnist_test.h5', 'name': 'HDF5Iterator_1'},
 'type': 'neon.data.hdf5iterator.HDF5Iterator'}



In [10]:

    
train_set.ndata   # Number of patients in our dataset









    Out[10]:





10000



In [11]:

    
train_set.lshape   # DICOM image tensor (C x H x W x D)









    Out[11]:





(1, 28, 28)



In [17]:

    
from matplotlib import pyplot as plt
%matplotlib inline



In [37]:

    
plt.imshow(train_set.inp[0,:].reshape(28,28), cmap=cm.gray);



In [29]:

    
i = 0
for x, t in train_set:
    
    print(i)
    print(x)
    plt.imshow(x.get().reshape(28,28), cmap=cm.gray); 
    
    i += 1
    break









    



0
CPUTensor(base 0x104421990) name:None shape:(784, 1) dtype:float32 strides:(4, 4) is_c_contiguous:True



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