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View Code? Open in Web Editor NEWA resizable numpy array on disk (mmap based)
License: MIT License
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venkat214 shivam05011996 chatrapathik conanmatsui 20cmdingding r-ceph codegram sakurablossom idavalapatiramanjaneyulu mgtttdiskarray's Issues
Support close method to close the file
def close(self):
del self.data
self.data = NoneValues in the diskarray are changing.
I am using version 0.1.4.
The value of the appended numbers change -
>>> float_d = DiskArray('/tmp/float.diskarray', shape=(0,), dtype=[('floats', np.float32, 1)])
>>> float_d.append((0.1,))
>>> float_d.append((0.2,))
>>> float_d.append((0.3,))
>>> float_d.append((0.4,))
>>> float_d.append((0.5,))
>>> float_d['floats']
memmap([ 0.1 , 0.2 , 0.30000001, ..., 0. ,
0. , 0. ], dtype=float32)
>>> float_d['floats'][0]
0.1
>>> float_d['floats'][2]
0.30000001
>>> float_d['floats'][3]
0.40000001
>>> float_d['floats'][4]
0.5>>> z = D('/tmp/float.diskarray', shape=(0,), dtype=[('floats', np.float32, 1)])
>>> z.append((0.87686,))
>>> z[:][0]
( 0.87686002,)
>>>
>>>
>>> z.append((0.87684556,))
>>> z[:][1]
( 0.87684554,)>>> list_d = D('/tmp/float_list.diskarray', shape=(0,), dtype=[('floats', np.float32, 5)])
>>> list_d.append(([0.234324, -0.898767, 0.12213, 0.465477, 0.1]))
>>> list_d[:][0]
([ 0.23432399, -0.89876699, 0.12213 , 0.46547699, 0.1 ],)While dealing with wvspace file vectors this happens
>>> vec_d = D('/tmp/vec.diskarray', shape=(0,), dtype=[('vec', np.float32, 300)])
>>> vec_d.append((wv.get_word_vector('the')))
>>> vec_d['vec']
memmap([[-0.0708, -0.1261, -0.0024, ..., 0.3283, -0.1717, -0.0638],
[ 0. , 0. , 0. , ..., 0. , 0. , 0. ],
[ 0. , 0. , 0. , ..., 0. , 0. , 0. ],
...,
[ 0. , 0. , 0. , ..., 0. , 0. , 0. ],
[ 0. , 0. , 0. , ..., 0. , 0. , 0. ],
[ 0. , 0. , 0. , ..., 0. , 0. , 0. ]], dtype=float32)
>>> vec_d['vec'][0]
memmap([-0.0708, -0.1261, -0.0024, 0.071 , -0.244 , 0.4421, 0.0462,
0.3307, -0.2153, -0.3359, 0.33 , 0.1035, 0.173 , -0.026 ,
0.2973, -0.1994, 0.0365, -0.0269, -0.1076, -0.269 , 0.0057,
0.0448, -0.0338, -0.1212, 0.2337, 0.0181, 0.178 , -0.0441,
-0.1288, -0.5501, -0.0296, -0.4436, 0.3562, -0.085 , 0.0061,
-0.4216, -0.167 , -0.2316, 0.2465, -0.576 , -0.2651, 0.1639,
0.1773, -0.1638, -0.0192, 0.2562, 0.1118, 0.2438, -0.3158,
-0.1226, -0.0164, 0.1403, 0.2215, -0.079 , -0.5859, -0.133 ,
0.0374, -0.0172, 0.2372, -0.0897, -0.3149, -0.2292, 0.0373,
0.1108, -0.0798, 0.2603, -0.2713, -0.287 , 0.0302, -0.1888,
0.6536, -0.4905, 0.2123, -0.3576, -0.0011, -0.2266, 0.1184,
0.3063, -0.2623, -0.0794, 0.2039, 0.2903, -0.292 , -0.1514,
-0.0664, -0.0811, -0.2342, -0.0881, 0.153 , 0.0052, 0.0293,
0.3174, 0.0053, -0.3784, 0.1975, -0.2095, -0.1435, 0.1823,
-0.151 , 0.1768, -0.0346, -0.0776, 0.1035, -0.083 , 0.1746,
0.0941, -0.0066, 0.2882, 0.0505, 0.0989, -0.0578, 0.2479,
0.043 , 0.2448, 0.0516, 0.2548, 0.1639, 0.0132, 0.0273,
-0.3195, 0.1441, 0.0072, -0.2061, 0.0982, -0.0936, -0.2313,
0.2072, -0.0253, 0.0126, -0.0423, 0.2766, 0.0332, 0.0633,
-0.1975, -0.0643, 0.0887, -0.1165, 0.0899, -0.2726, -0.4402,
-0.1391, 0.1087, 0.0317, -0.0621, 0.2462, -0.1575, -0.3078,
-0.2344, -0.0769, -0.043 , -0.0089, 0.0353, 0.1602, -0.041 ,
-0.2797, 0.2453, 0.0144, -0.0767, -0.2859, -0.0195, -0.1154,
0.0503, 0.0656, -0.0075, -0.3465, -0.1241, -0.302 , 0.1875,
0.279 , 0.0758, -0.1974, 0.223 , -0.3469, 0.0192, 0.1762,
0.0787, 0.2191, -0.1073, 0.2317, 0.3902, -0.3307, -0.079 ,
0.1755, -0.1113, 0.1689, 0.166 , -0.1134, 0.0815, 0.1436,
-0.0286, -0.1198, -0.1074, -0.0272, 0.2614, -0.251 , 0.0039,
0.0329, 0.2288, 0.2932, 0.5009, -0.0998, 0.1664, 0.084 ,
0.1192, -0.432 , -0.3663, 0.2071, 0.795 , -0.1185, -0.2545,
-0.1827, -0.1033, -0.3473, -0.149 , -0.0287, -0.1032, -0.0202,
0.3946, 0.1252, 0.0658, -0.0617, -0.4052, 0.0417, 0.1702,
0.0718, 0.2493, -0.2788, 0.2397, 0.1541, -0.0553, 0.1348,
0.4107, -0.0179, 0.0422, -0.1157, 0.0066, 0.2859, 0.0109,
0.0334, -0.3072, -0.0232, -0.3964, -0.0321, -0.5027, -0.1077,
0.094 , -0.0616, 0.1182, 0.024 , 0.3452, 0.3762, -0.0421,
0.1445, 0.0904, -0.6647, 0.3608, -0.0042, -0.0711, 0.1041,
-0.445 , 0.1815, 0.3388, -0.135 , 0.1139, -0.0077, 0.2227,
-0.1813, -0.068 , -0.1217, -0.0918, -0.0526, 0.1311, -0.0199,
-0.1598, -0.1521, -0.0995, 0.0921, 0.1171, -0.1107, 0.3541,
-0.2168, 0.2845, -0.2572, 0.4754, -0.0839, 0.286 , 0.5393,
-0.1501, 0.2447, 0.3126, 0.345 , 0.2083, 0.0781, 0.2214,
0.0664, -0.0724, -0.0039, 0.3283, -0.1717, -0.0638], dtype=float32)
>>> wv.get_word_vector('the')
array([-0.0708, -0.1261, -0.0024, 0.071 , -0.244 , 0.4421, 0.0462,
0.3307, -0.2153, -0.3359, 0.33 , 0.1035, 0.173 , -0.026 ,
0.2973, -0.1994, 0.0365, -0.0269, -0.1076, -0.269 , 0.0057,
0.0448, -0.0338, -0.1212, 0.2337, 0.0181, 0.178 , -0.0441,
-0.1288, -0.5501, -0.0296, -0.4436, 0.3562, -0.085 , 0.0061,
-0.4216, -0.167 , -0.2316, 0.2465, -0.576 , -0.2651, 0.1639,
0.1773, -0.1638, -0.0192, 0.2562, 0.1118, 0.2438, -0.3158,
-0.1226, -0.0164, 0.1403, 0.2215, -0.079 , -0.5859, -0.133 ,
0.0374, -0.0172, 0.2372, -0.0897, -0.3149, -0.2292, 0.0373,
0.1108, -0.0798, 0.2603, -0.2713, -0.287 , 0.0302, -0.1888,
0.6536, -0.4905, 0.2123, -0.3576, -0.0011, -0.2266, 0.1184,
0.3063, -0.2623, -0.0794, 0.2039, 0.2903, -0.292 , -0.1514,
-0.0664, -0.0811, -0.2342, -0.0881, 0.153 , 0.0052, 0.0293,
0.3174, 0.0053, -0.3784, 0.1975, -0.2095, -0.1435, 0.1823,
-0.151 , 0.1768, -0.0346, -0.0776, 0.1035, -0.083 , 0.1746,
0.0941, -0.0066, 0.2882, 0.0505, 0.0989, -0.0578, 0.2479,
0.043 , 0.2448, 0.0516, 0.2548, 0.1639, 0.0132, 0.0273,
-0.3195, 0.1441, 0.0072, -0.2061, 0.0982, -0.0936, -0.2313,
0.2072, -0.0253, 0.0126, -0.0423, 0.2766, 0.0332, 0.0633,
-0.1975, -0.0643, 0.0887, -0.1165, 0.0899, -0.2726, -0.4402,
-0.1391, 0.1087, 0.0317, -0.0621, 0.2462, -0.1575, -0.3078,
-0.2344, -0.0769, -0.043 , -0.0089, 0.0353, 0.1602, -0.041 ,
-0.2797, 0.2453, 0.0144, -0.0767, -0.2859, -0.0195, -0.1154,
0.0503, 0.0656, -0.0075, -0.3465, -0.1241, -0.302 , 0.1875,
0.279 , 0.0758, -0.1974, 0.223 , -0.3469, 0.0192, 0.1762,
0.0787, 0.2191, -0.1073, 0.2317, 0.3902, -0.3307, -0.079 ,
0.1755, -0.1113, 0.1689, 0.166 , -0.1134, 0.0815, 0.1436,
-0.0286, -0.1198, -0.1074, -0.0272, 0.2614, -0.251 , 0.0039,
0.0329, 0.2288, 0.2932, 0.5009, -0.0998, 0.1664, 0.084 ,
0.1192, -0.432 , -0.3663, 0.2071, 0.795 , -0.1185, -0.2545,
-0.1827, -0.1033, -0.3473, -0.149 , -0.0287, -0.1032, -0.0202,
0.3946, 0.1252, 0.0658, -0.0617, -0.4052, 0.0417, 0.1702,
0.0718, 0.2493, -0.2788, 0.2397, 0.1541, -0.0553, 0.1348,
0.4107, -0.0179, 0.0422, -0.1157, 0.0066, 0.2859, 0.0109,
0.0334, -0.3072, -0.0232, -0.3964, -0.0321, -0.5027, -0.1077,
0.094 , -0.0616, 0.1182, 0.024 , 0.3452, 0.3762, -0.0421,
0.1445, 0.0904, -0.6647, 0.3608, -0.0042, -0.0711, 0.1041,
-0.445 , 0.1815, 0.3388, -0.135 , 0.1139, -0.0077, 0.2227,
-0.1813, -0.068 , -0.1217, -0.0918, -0.0526, 0.1311, -0.0199,
-0.1598, -0.1521, -0.0995, 0.0921, 0.1171, -0.1107, 0.3541,
-0.2168, 0.2845, -0.2572, 0.4754, -0.0839, 0.286 , 0.5393,
-0.1501, 0.2447, 0.3126, 0.345 , 0.2083, 0.0781, 0.2214,
0.0664, -0.0724, -0.0039, 0.3283, -0.1717, -0.0638], dtype=float32)
>>> vec_d['vec'][0][0]
>>> vec_d['vec'][0][0]
-0.070754707
>>> wv.get_word_vector('the')[0]
-0.070754707The values in the memmap and array remain the same, but on accessing the individual values see how it varies, what is the reason for this.
This been tested on dev0.servers.deepcompute.com and [email protected]
@prashanthellina Is this actually as change in information. Also, I believe this is harmful for NN training.
could we add an "allow_pickle"=true/false option?
If shape is not given then it would be better to assume the previous shape.
- Let us assume we gave shape as (4, 3) and append some arrays to diskarray and close it.
- When I open the diskarray second time and if I don't give the shape then it is giving 1D array.
- It would be better if I don't give the shape then assume the shape is (4, 3) and give the actual array.
Support diskarray.take and diskarray.data
-
diskarray.take:
If we want to take the data from diskarray then we need to specify diskarray[:].take. Instead of this it would be better to support take. -
The same with diskarray.data like if I want the data instead of specifying diskarray[:] support diskarray.data.
Problem in README
-
In 89 line of README
>>> da = DiskArray('/tmp/disk.array', shape=(0, 3), capacity=(10, 3), dtype=np.float32)
it should be dtype=dtype. It is wrongly mentioned as np.float32. -
If anyone gives commit please fix this.
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