{"action":"opened","number":4,"pull_request":{"url":"https://api.github.com/repos/farzaa/SimpleMultilayerPerceptron/pulls/4","id":201222454,"node_id":"MDExOlB1bGxSZXF1ZXN0MjAxMjIyNDU0","html_url":"https://github.com/farzaa/SimpleMultilayerPerceptron/pull/4","diff_url":"https://github.com/farzaa/SimpleMultilayerPerceptron/pull/4.diff","patch_url":"https://github.com/farzaa/SimpleMultilayerPerceptron/pull/4.patch","issue_url":"https://api.github.com/repos/farzaa/SimpleMultilayerPerceptron/issues/4","number":4,"state":"open","locked":false,"title":"Python3 compatibility","user":{"login":"inzouzouwetrust","id":17804379,"node_id":"MDQ6VXNlcjE3ODA0Mzc5","avatar_url":"https://avatars2.githubusercontent.com/u/17804379?v=4","gravatar_id":"","url":"https://api.github.com/users/inzouzouwetrust","html_url":"https://github.com/inzouzouwetrust","followers_url":"https://api.github.com/users/inzouzouwetrust/followers","following_url":"https://api.github.com/users/inzouzouwetrust/following{/other_user}","gists_url":"https://api.github.com/users/inzouzouwetrust/gists{/gist_id}","starred_url":"https://api.github.com/users/inzouzouwetrust/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/inzouzouwetrust/subscriptions","organizations_url":"https://api.github.com/users/inzouzouwetrust/orgs","repos_url":"https://api.github.com/users/inzouzouwetrust/repos","events_url":"https://api.github.com/users/inzouzouwetrust/events{/privacy}","received_events_url":"https://api.github.com/users/inzouzouwetrust/received_events","type":"User","site_admin":false},"body":"I refactored the current code base so that it works with Python 3 as well as Python 2 (mostly adding parenthesis to print statements and ditching ``xrange`` for built-in ``range``). I updated the ``README.md`` section accordingly.\r\n\r\nI tested both using ``conda`` virtual environments (plain Python 2.7/3.6 with ``numpy``).\r\n\r\nI fixed the broken ``fancy_mlp.py`` implementation as it was throwing a ``ValueError``.\r\nI also increased the number of training steps in ``fancy_mlp.py`` from ``20000`` to ``40000`` as convergence has proven to be slow.\r\n\r\n```Traceback (most recent call last):\r\n  File \"fancy_mlp.py\", line 74, in <module>\r\n    main()\r\n  File \"fancy_mlp.py\", line 71, in main\r\n    train(inputs, keys, layer_one_weights, layer_two_weights)\r\n  File \"fancy_mlp.py\", line 53, in train\r\n    layer_one_weights +=  np.dot(layer_one_prediction.T, layer_one_change_in_error)\r\nValueError: operands could not be broadcast together with shapes (3,4) (4,4) 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