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  1. $./main.py -c journal_models/RNN-FF/train/best-1529969240.38/
  2. Loading from checkpoint...
  3. wrangling tracks
  4. Reading raw data from csv's / checkpoint and splitting into data pool, this will take some time
  5. loading data from: intersections-dataset
  6. origin | destination
  7. north west SW NE SE east south NW total
  8. north 31.0 298.0 0.0 0.0 0.0 4340.0 6592.0 0.0 11261.0
  9. SE 0.0 0.0 43.0 41.0 5.0 0.0 0.0 1459.0 1548.0
  10. south 7046.0 793.0 0.0 0.0 0.0 1533.0 17.0 0.0 9389.0
  11. NW 0.0 0.0 28.0 140.0 1541.0 0.0 0.0 5.0 1714.0
  12. total 7077.0 1091.0 71.0 181.0 1546.0 5873.0 6609.0 1464.0 23912.0
  13. origin | destination
  14. left straight right u-turn total
  15. north 4340.0 6592.0 298.0 31.0 11261.0
  16. SE 43.0 1459.0 41.0 5.0 1548.0
  17. south 793.0 7046.0 1533.0 17.0 9389.0
  18. NW 140.0 1541.0 28.0 5.0 1714.0
  19. total 5316.0 16638.0 1900.0 58.0 23912.0
  20. /usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/_encoders.py:371: FutureWarning: The handling of integer data will change in version 0.22. Currently, the categories are determined based on the range [0, max(values)], while in the future they will be determined based on the unique values.
  21. If you want the future behaviour and silence this warning, you can specify "categories='auto'".
  22. In case you used a LabelEncoder before this OneHotEncoder to convert the categories to integers, then you can now use the OneHotEncoder directly.
  23. warnings.warn(msg, FutureWarning)
  24. Computing batch normalization parameters.
  25. Encoder means: [-3.98354701 2.26732147 0.03548995 6.63765986]
  26. Encoder vars: [ 7.41111757 108.25326478 0.28638244 5.60370354]
  27. Encoder standard deviations: [ 2.72233678 10.40448292 0.53514712 2.3672143 ]
  28. Wrangling track: 23911 [ OK ]
  29. Discarded 0 tracks
  30. Passed 23912 tracks
  31. Using seed: 42296 for test/train split
  32. Encoder means: [-3.9413989 0.78363454 0.04127831 6.5038037 ]
  33. Encoder vars: [ 5.1926866 92.58522 0.2548986 5.5409775]
  34. Encoder standard deviations: [2.2787466 9.622122 0.5048748 2.353928 ]
  35. Crossfold cache miss, calculating splits and making sub-pools
  36. concatenating pools
  37. Exception in thread Thread-1:
  38. Traceback (most recent call last):
  39. File "/usr/lib/python2.7/threading.py", line 801, in __bootstrap_inner
  40. self.run()
  41. File "/usr/lib/python2.7/threading.py", line 754, in run
  42. self.__target(*self.__args, **self.__kwargs)
  43. File "/usr/local/lib/python2.7/dist-packages/multiprocess/pool.py", line 328, in _handle_workers
  44. pool._maintain_pool()
  45. File "/usr/local/lib/python2.7/dist-packages/multiprocess/pool.py", line 232, in _maintain_pool
  46. self._repopulate_pool()
  47. File "/usr/local/lib/python2.7/dist-packages/multiprocess/pool.py", line 225, in _repopulate_pool
  48. w.start()
  49. File "/usr/local/lib/python2.7/dist-packages/multiprocess/process.py", line 130, in start
  50. self._popen = Popen(self)
  51. File "/usr/local/lib/python2.7/dist-packages/multiprocess/forking.py", line 124, in __init__
  52. self.pid = os.fork()
  53. OSError: [Errno 12] Cannot allocate memory
  54.  
  55. Traceback (most recent call last):
  56. File "./main.py", line 142, in <module>
  57. Wrangler.split_into_evaluation_pools(test_idxs=from_pickle['test_idxs'], trainval_idxs=from_pickle['trainval_idxs'])
  58. File "/media/bartosz/hdd1TB/workspace_hdd/radip/SequenceWrangler.py", line 210, in split_into_evaluation_pools
  59. pickle.dump(to_pickle, pkl_file)
  60. File "/usr/local/lib/python2.7/dist-packages/dill/_dill.py", line 287, in dump
  61. pik.dump(obj)
  62. File "/usr/lib/python2.7/pickle.py", line 224, in dump
  63. self.save(obj)
  64. File "/usr/lib/python2.7/pickle.py", line 286, in save
  65. f(self, obj) # Call unbound method with explicit self
  66. File "/usr/local/lib/python2.7/dist-packages/dill/_dill.py", line 902, in save_module_dict
  67. StockPickler.save_dict(pickler, obj)
  68. File "/usr/lib/python2.7/pickle.py", line 655, in save_dict
  69. self._batch_setitems(obj.iteritems())
  70. File "/usr/lib/python2.7/pickle.py", line 687, in _batch_setitems
  71. save(v)
  72. File "/usr/lib/python2.7/pickle.py", line 286, in save
  73. f(self, obj) # Call unbound method with explicit self
  74. File "/usr/lib/python2.7/pickle.py", line 606, in save_list
  75. self._batch_appends(iter(obj))
  76. File "/usr/lib/python2.7/pickle.py", line 639, in _batch_appends
  77. save(x)
  78. File "/usr/lib/python2.7/pickle.py", line 286, in save
  79. f(self, obj) # Call unbound method with explicit self
  80. File "/usr/lib/python2.7/pickle.py", line 606, in save_list
  81. self._batch_appends(iter(obj))
  82. File "/usr/lib/python2.7/pickle.py", line 639, in _batch_appends
  83. save(x)
  84. File "/usr/lib/python2.7/pickle.py", line 331, in save
  85. self.save_reduce(obj=obj, *rv)
  86. File "/usr/lib/python2.7/pickle.py", line 425, in save_reduce
  87. save(state)
  88. File "/usr/lib/python2.7/pickle.py", line 286, in save
  89. f(self, obj) # Call unbound method with explicit self
  90. File "/usr/local/lib/python2.7/dist-packages/dill/_dill.py", line 902, in save_module_dict
  91. StockPickler.save_dict(pickler, obj)
  92. File "/usr/lib/python2.7/pickle.py", line 655, in save_dict
  93. self._batch_setitems(obj.iteritems())
  94. File "/usr/lib/python2.7/pickle.py", line 687, in _batch_setitems
  95. save(v)
  96. File "/usr/lib/python2.7/pickle.py", line 331, in save
  97. self.save_reduce(obj=obj, *rv)
  98. File "/usr/lib/python2.7/pickle.py", line 425, in save_reduce
  99. save(state)
  100. File "/usr/lib/python2.7/pickle.py", line 286, in save
  101. f(self, obj) # Call unbound method with explicit self
  102. File "/usr/lib/python2.7/pickle.py", line 568, in save_tuple
  103. save(element)
  104. File "/usr/lib/python2.7/pickle.py", line 286, in save
  105. f(self, obj) # Call unbound method with explicit self
  106. File "/usr/lib/python2.7/pickle.py", line 606, in save_list
  107. self._batch_appends(iter(obj))
  108. File "/usr/lib/python2.7/pickle.py", line 639, in _batch_appends
  109. save(x)
  110. File "/usr/lib/python2.7/pickle.py", line 331, in save
  111. self.save_reduce(obj=obj, *rv)
  112. File "/usr/lib/python2.7/pickle.py", line 425, in save_reduce
  113. save(state)
  114. File "/usr/lib/python2.7/pickle.py", line 286, in save
  115. f(self, obj) # Call unbound method with explicit self
  116. File "/usr/lib/python2.7/pickle.py", line 568, in save_tuple
  117. save(element)
  118. File "/usr/lib/python2.7/pickle.py", line 286, in save
  119. f(self, obj) # Call unbound method with explicit self
  120. File "/usr/lib/python2.7/pickle.py", line 606, in save_list
  121. self._batch_appends(iter(obj))
  122. File "/usr/lib/python2.7/pickle.py", line 639, in _batch_appends
  123. save(x)
  124. File "/usr/lib/python2.7/pickle.py", line 331, in save
  125. self.save_reduce(obj=obj, *rv)
  126. File "/usr/lib/python2.7/pickle.py", line 401, in save_reduce
  127. save(args)
  128. File "/usr/lib/python2.7/pickle.py", line 286, in save
  129. f(self, obj) # Call unbound method with explicit self
  130. File "/usr/lib/python2.7/pickle.py", line 561, in save_tuple
  131. self.memoize(obj)
  132. File "/usr/lib/python2.7/pickle.py", line 247, in memoize
  133. self.memo[id(obj)] = memo_len, obj
  134. MemoryError
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