(?, 128, 128, 24)
(?, 64, 64, 24)
(?, 64, 64, 96)
(?, 32, 32, 96)
2017-07-29 18:31:20.497520: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-07-29 18:31:20.497532: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-07-29 18:31:20.497536: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-07-29 18:31:20.497540: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
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Iter 30, Minibatch Loss= 48161656.000000, Training Accuracy= 0.80000
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Iter 60, Minibatch Loss= 321867840.000000, Training Accuracy= 0.00000
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Iter 90, Minibatch Loss= 423731744.000000, Training Accuracy= 0.00000
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Iter 120, Minibatch Loss= 427380992.000000, Training Accuracy= 0.00000
count: 2
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Iter 150, Minibatch Loss= 212897232.000000, Training Accuracy= 0.00000
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Iter 180, Minibatch Loss= 46964744.000000, Training Accuracy= 0.10000
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Iter 210, Minibatch Loss= 14519466.000000, Training Accuracy= 0.40000
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Iter 240, Minibatch Loss= 9990268.000000, Training Accuracy= 0.60000
count: 3
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Iter 270, Minibatch Loss= 80894400.000000, Training Accuracy= 0.00000
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Iter 300, Minibatch Loss= 55994028.000000, Training Accuracy= 0.00000
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Iter 330, Minibatch Loss= 71483504.000000, Training Accuracy= 0.00000
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Iter 360, Minibatch Loss= 36483064.000000, Training Accuracy= 0.00000
count: 4
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Iter 390, Minibatch Loss= 58645964.000000, Training Accuracy= 0.00000
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Iter 420, Minibatch Loss= 48663864.000000, Training Accuracy= 0.00000
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Iter 450, Minibatch Loss= 17381402.000000, Training Accuracy= 0.10000
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Iter 480, Minibatch Loss= 2577538.500000, Training Accuracy= 0.70000
count: 5
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Iter 510, Minibatch Loss= 15052680.000000, Training Accuracy= 0.40000
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Iter 540, Minibatch Loss= 18420312.000000, Training Accuracy= 0.20000
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Iter 570, Minibatch Loss= 23141172.000000, Training Accuracy= 0.10000
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Iter 600, Minibatch Loss= 10837658.000000, Training Accuracy= 0.40000
count: 6
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Iter 630, Minibatch Loss= 21745000.000000, Training Accuracy= 0.30000
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Iter 660, Minibatch Loss= 17480332.000000, Training Accuracy= 0.40000
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Iter 690, Minibatch Loss= 17633370.000000, Training Accuracy= 0.10000
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Iter 720, Minibatch Loss= 10235282.000000, Training Accuracy= 0.30000
count: 7
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Iter 750, Minibatch Loss= 6799557.000000, Training Accuracy= 0.80000
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Iter 780, Minibatch Loss= 4268240.000000, Training Accuracy= 0.70000
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Iter 810, Minibatch Loss= 575766.312500, Training Accuracy= 0.90000
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Iter 840, Minibatch Loss= 6839501.000000, Training Accuracy= 0.50000
count: 8
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Iter 870, Minibatch Loss= 19500750.000000, Training Accuracy= 0.30000
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Iter 900, Minibatch Loss= 11227581.000000, Training Accuracy= 0.60000
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Iter 930, Minibatch Loss= 14566576.000000, Training Accuracy= 0.20000
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Iter 960, Minibatch Loss= 5684557.500000, Training Accuracy= 0.40000
count: 9
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Iter 990, Minibatch Loss= 7205131.000000, Training Accuracy= 0.80000
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Iter 1020, Minibatch Loss= 5167798.000000, Training Accuracy= 0.70000
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Iter 1050, Minibatch Loss= 0.000000, Training Accuracy= 1.00000
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Iter 1080, Minibatch Loss= 394604.187500, Training Accuracy= 0.90000
count: 10
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Iter 1110, Minibatch Loss= 3477911.250000, Training Accuracy= 0.70000
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Iter 1140, Minibatch Loss= 293735.093750, Training Accuracy= 0.90000
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Iter 1170, Minibatch Loss= 3111549.500000, Training Accuracy= 0.80000
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Iter 1200, Minibatch Loss= 0.000000, Training Accuracy= 1.00000
Optimization Finished!

Process finished with exit code 0