{"action":"opened","number":4,"pull_request":{"url":"https://api.github.com/repos/arun-gupta/k8s-machine-learning/pulls/4","id":216551836,"node_id":"MDExOlB1bGxSZXF1ZXN0MjE2NTUxODM2","html_url":"https://github.com/arun-gupta/k8s-machine-learning/pull/4","diff_url":"https://github.com/arun-gupta/k8s-machine-learning/pull/4.diff","patch_url":"https://github.com/arun-gupta/k8s-machine-learning/pull/4.patch","issue_url":"https://api.github.com/repos/arun-gupta/k8s-machine-learning/issues/4","number":4,"state":"open","locked":false,"title":"Add mnist training using Tensorflow on 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tensorflow\r\nNAME         READY     STATUS    RESTARTS   AGE\r\ntensorflow   1/1       Running   0          5m\r\n88e9fe562973:k8s-machine-learning gauta$ \r\n\r\nTraining has started \r\n\r\n88e9fe562973:k8s-machine-learning gauta$ kubectl logs tensorflow\r\nUsing TensorFlow backend.\r\nDownloading data from https://s3.amazonaws.com/img-datasets/mnist.npz\r\n\r\n   16384/11490434 [..............................] - ETA: 0s\r\n   24576/11490434 [..............................] - ETA: 36s\r\n   57344/11490434 [..............................] - ETA: 31s\r\n  122880/11490434 [..............................] - ETA: 21s\r\n  303104/11490434 [..............................] - ETA: 11s\r\n  557056/11490434 [>.............................] - ETA: 7s \r\n 1155072/11490434 [==>...........................] - ETA: 4s\r\n 2334720/11490434 [=====>........................] - ETA: 2s\r\n 3907584/11490434 [=========>....................] - ETA: 1s\r\n 5480448/11490434 [=============>................] - ETA: 0s\r\n 7053312/11490434 [=================>............] - ETA: 0s\r\n 8626176/11490434 [=====================>........] - ETA: 0s\r\n10199040/11490434 [=========================>....] - ETA: 0s\r\n11493376/11490434 [==============================] - 1s 0us/step\r\n\r\n11501568/11490434 [==============================] - 1s 0us/step\r\n2018-09-19 08:12:43.142740: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA\r\nx_train shape: (60000, 28, 28, 1)\r\n60000 train samples\r\n10000 test samples\r\nTrain on 60000 samples, validate on 10000 samples\r\nEpoch 1/12\r\n\r\n  128/60000 [..............................] - ETA: 4:56 - loss: 2.3072 - acc: 0.1094\r\n  256/60000 [..............................] - ETA: 3:30 - loss: 2.2785 - acc: 0.1367\r\n  384/60000 [..............................] - ETA: 3:00 - loss: 2.2411 - acc: 0.1901\r\n  512/60000 [..............................] - ETA: 2:45 - loss: 2.2161 - acc: 0.2070\r\n  640/60000 [..............................] - ETA: 2:37 - loss: 2.1876 - acc: 0.2422\r\n  768/60000 [..............................] - ETA: 2:30 - loss: 2.1491 - acc: 0.2617\r\n  896/60000 [..............................] - ETA: 2:25 - loss: 2.1092 - acc: 0.2846\r\n 1024/60000 [..............................] - ETA: 2:22 - loss: 2.0544 - acc: 0.3096\r\n 1152/60000 [..............................] - ETA: 2:20 - loss: 1.9965 - acc: 0.3316\r\n 1280/60000 [..............................] - ETA: 2:17 - loss: 1.9899 - 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