python - How to get around this memoryview error in numpy? -

in code snippet train_dataset, test_dataset , valid_dataset of type numpy.ndarray.

def check_overlaps(images1, images2):     images1.flags.writeable=false     images2.flags.writeable=false     print(type(images1))     print(type(images2))     start = time.clock()     hash1 = set([hash(image1.data) image1 in images1])     hash2 = set([hash(image2.data) image2 in images2])     all_overlaps = set.intersection(hash1, hash2)     return all_overlaps, time.clock()-start  r, exectime = check_overlaps(train_dataset, test_dataset)     print("# overlaps between training , test sets:", len(r), "execution time:", exectime) r, exectime = check_overlaps(train_dataset, valid_dataset)    print("# overlaps between training , validation sets:", len(r), "execution time:", exectime)  r, exectime = check_overlaps(valid_dataset, test_dataset)  print("# overlaps between validation , test sets:", len(r), "execution time:", exectime) 

but gives following error: (formatting code make readable!)

valueerror                                traceback (most recent call last) <ipython-input-14-337e73a1cb14> in <module>()      12     return all_overlaps, time.clock()-start      13  ---> 14 r, exectime = check_overlaps(train_dataset, test_dataset)      15 print("# overlaps between training , test sets:", len(r), "execution time:", exectime)      16 r, exectime = check_overlaps(train_dataset, valid_dataset)  <ipython-input-14-337e73a1cb14> in check_overlaps(images1, images2)       7     print(type(images2))       8     start = time.clock() ----> 9     hash1 = set([hash(image1.data) image1 in images1])      10     hash2 = set([hash(image2.data) image2 in images2])      11     all_overlaps = set.intersection(hash1, hash2)  <ipython-input-14-337e73a1cb14> in <listcomp>(.0)       7     print(type(images2))       8     start = time.clock() ----> 9     hash1 = set([hash(image1.data) image1 in images1])      10     hash2 = set([hash(image2.data) image2 in images2])      11     all_overlaps = set.intersection(hash1, hash2)  valueerror: memoryview: hashing restricted formats 'b', 'b' or 'c' 

now problem don't know error means let alone think correcting it. please?

the problem method hash arrays works python2. therefore, code fails try compute hash(image1.data). error message tells memoryviews of formats unsigned bytes ('b'), bytes ('b') of single bytes ('c') supported , have not found way such view out of np.ndarray without copying. way came includes copying array, might not feasible in application depending on amount of data. being said, can try change function to:

def check_overlaps(images1, images2):     start = time.clock()     hash1 = set([hash(image1.tobytes()) image1 in images1])     hash2 = set([hash(image2.tobytes()) image2 in images2])     all_overlaps = set.intersection(hash1, hash2)     return all_overlaps, time.clock()-start