[[0 1 0] [1 0 0] [0 1 0] [0 1 0] [0 1 0] [0 1 0] [0 1 0] [1 0 0] [0 1 0] [0 1 0] [0 1 0] [0 0 1] [0 1 0] [0 0 1] [0 1 0] [0 1 0] [0 1 0] [0 0 1] [0 1 0] [0 1 0]] 2017-08-17 10:46:06.443575: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 2017-08-17 10:46:06.443591: 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. 2017-08-17 10:46:06.443593: 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. 2017-08-17 10:46:06.443595: 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. 2017-08-17 10:46:06.443597: 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. 2017-08-17 10:46:06.573456: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:893] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2017-08-17 10:46:06.573784: I tensorflow/core/common_runtime/gpu/gpu_device.cc:940] Found device 0 with properties: name: GeForce GTX 980 Ti major: 5 minor: 2 memoryClockRate (GHz) 1.3545 pciBusID 0000:01:00.0 Total memory: 5.93GiB Free memory: 5.25GiB 2017-08-17 10:46:06.668582: W tensorflow/stream_executor/cuda/cuda_driver.cc:523] A non-primary context 0x58af0b0 exists before initializing the StreamExecutor. We haven't verified StreamExecutor works with that. 2017-08-17 10:46:06.668806: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:893] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2017-08-17 10:46:06.669083: I tensorflow/core/common_runtime/gpu/gpu_device.cc:940] Found device 1 with properties: name: GeForce GTX 980 Ti major: 5 minor: 2 memoryClockRate (GHz) 1.228 pciBusID 0000:02:00.0 Total memory: 5.94GiB Free memory: 5.83GiB 2017-08-17 10:46:06.669361: I tensorflow/core/common_runtime/gpu/gpu_device.cc:961] DMA: 0 1 2017-08-17 10:46:06.669367: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: Y Y 2017-08-17 10:46:06.669370: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 1: Y Y 2017-08-17 10:46:06.669376: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 980 Ti, pci bus id: 0000:01:00.0) 2017-08-17 10:46:06.669379: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Creating TensorFlow device (/gpu:1) -> (device: 1, name: GeForce GTX 980 Ti, pci bus id: 0000:02:00.0) 2017-08-17 10:46:07.059295: I tensorflow/core/common_runtime/gpu/pool_allocator.cc:247] PoolAllocator: After 1734 get requests, put_count=1637 evicted_count=1000 eviction_rate=0.610874 and unsatisfied allocation rate=0.690311 2017-08-17 10:46:07.059314: I tensorflow/core/common_runtime/gpu/pool_allocator.cc:259] Raising pool_size_limit_ from 100 to 110 Iter 2000, Minibatch Loss= 1.166351, Training Accuracy= 0.75000 2017-08-17 10:46:07.738897: I tensorflow/core/common_runtime/gpu/pool_allocator.cc:247] PoolAllocator: After 10710 get requests, put_count=10729 evicted_count=1000 eviction_rate=0.0932053 and unsatisfied allocation rate=0.0937442 2017-08-17 10:46:07.738917: I tensorflow/core/common_runtime/gpu/pool_allocator.cc:259] Raising pool_size_limit_ from 256 to 281 Iter 4000, Minibatch Loss= 0.740859, Training Accuracy= 0.75000 Iter 6000, Minibatch Loss= 0.730592, Training Accuracy= 0.75000 Iter 8000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 10000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 12000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 14000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 16000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 18000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 20000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 22000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 24000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 26000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 28000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 30000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 32000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 34000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 36000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 38000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 40000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 42000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 44000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 46000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 48000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 50000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 52000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 54000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 56000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 58000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 60000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 62000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 64000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 66000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 68000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 70000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 72000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 74000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 76000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 78000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 80000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 82000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 84000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 86000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 88000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 90000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 92000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 94000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 96000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 98000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 100000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 102000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 104000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 106000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 108000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 110000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 112000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 114000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 116000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 118000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 120000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 122000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 124000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 126000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 128000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 130000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 132000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 134000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 136000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 138000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 140000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 142000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 144000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 146000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 148000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 150000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 152000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 154000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 156000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 158000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 160000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 162000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 164000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 166000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 168000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 170000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 172000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 174000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 176000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 178000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 180000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 182000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 184000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 186000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 188000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 190000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 192000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 194000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 196000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 198000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 200000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 202000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 204000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 206000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 208000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 210000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 212000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 214000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 216000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 218000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 220000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 222000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 224000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 226000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 228000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 230000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 232000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 234000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 236000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 238000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 240000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 242000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 244000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 246000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 248000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 250000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 252000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 254000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 256000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 258000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 260000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 262000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 264000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 266000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 268000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 270000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 272000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 274000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 276000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 278000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 280000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 282000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 284000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 286000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 288000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 290000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 292000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 294000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 296000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 298000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 300000, Minibatch Loss= 0.730593, Training Accuracy= 0.75000 Iter 302000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 304000, Minibatch Loss= 0.730596, Training Accuracy= 0.75000 Iter 306000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 308000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 310000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 312000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 314000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 316000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 318000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 320000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 322000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 324000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 326000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 328000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 330000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 332000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 334000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 336000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 338000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 340000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 342000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 344000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 346000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 348000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 350000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 352000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 354000, Minibatch Loss= 0.730592, Training Accuracy= 0.75000 Iter 356000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 358000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 360000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 362000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 364000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 366000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 368000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 370000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 372000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 374000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 376000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 378000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 380000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 382000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 384000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 386000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 388000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 390000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 392000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 394000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 396000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 398000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 400000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 402000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 404000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 406000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 408000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 410000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 412000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 414000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 416000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 418000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 420000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 422000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 424000, Minibatch Loss= 0.730592, Training Accuracy= 0.75000 Iter 426000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 428000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 430000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 432000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 434000, Minibatch Loss= 0.730604, Training Accuracy= 0.75000 Iter 436000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 438000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 440000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 442000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 444000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 446000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 448000, Minibatch Loss= 0.730607, Training Accuracy= 0.75000 Iter 450000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 452000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 454000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 456000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 458000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 460000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 462000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 464000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 466000, Minibatch Loss= 0.730601, Training Accuracy= 0.75000 Iter 468000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 470000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 472000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 474000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 476000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 478000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 480000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 482000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 484000, Minibatch Loss= 0.730592, Training Accuracy= 0.75000 Iter 486000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 488000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 490000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 492000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 494000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 496000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 498000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 500000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 502000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 504000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 506000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 508000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 510000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 512000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 514000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 516000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 518000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 520000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 522000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 524000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 526000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 528000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 530000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 532000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 534000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 536000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 538000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 540000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 542000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 544000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 546000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 548000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 550000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 552000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 554000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 556000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 558000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 560000, Minibatch Loss= 0.730595, Training Accuracy= 0.75000 Iter 562000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 564000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 566000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 568000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 570000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 572000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 574000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 576000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 578000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 580000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 582000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 584000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 586000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 588000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 590000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 592000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 594000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 596000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 598000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 600000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 602000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 604000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 606000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 608000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 610000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 612000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 614000, Minibatch Loss= 0.730598, Training Accuracy= 0.75000 Iter 616000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 618000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 620000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 622000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 624000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 626000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 628000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 630000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 632000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 634000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 636000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 638000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 640000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 642000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 644000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 646000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 648000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 650000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 652000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 654000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 656000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 658000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 660000, Minibatch Loss= 0.730593, Training Accuracy= 0.75000 Iter 662000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 664000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 666000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 668000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 670000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 672000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 674000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 676000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 678000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 680000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 682000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 684000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 686000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 688000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 690000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 692000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 694000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 696000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 698000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 700000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 702000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 704000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 706000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 708000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 710000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 712000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 714000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 716000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 718000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 720000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 722000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 724000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 726000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 728000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 730000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 732000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 734000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 736000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 738000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 740000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 742000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 744000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 746000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 748000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 750000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 752000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 754000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 756000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 758000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 760000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 762000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 764000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 766000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 768000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 770000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 772000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 774000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 776000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 778000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 780000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 782000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 784000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 786000, Minibatch Loss= 0.730591, Training Accuracy= 0.75000 Iter 788000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 790000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 792000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 794000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 796000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 798000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 800000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 802000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 804000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 806000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 808000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 810000, Minibatch Loss= 0.730599, Training Accuracy= 0.75000 Iter 812000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 814000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 816000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 818000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 820000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 822000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 824000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 826000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 828000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 830000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 832000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 834000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 836000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 838000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 840000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 842000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 844000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 846000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 848000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 850000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 852000, Minibatch Loss= 0.730594, Training Accuracy= 0.75000 Iter 854000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 856000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 858000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 860000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 862000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 864000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 866000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 868000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 870000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 872000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 874000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 876000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 878000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 880000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 882000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 884000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 886000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 888000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 890000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 892000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 894000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 896000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 898000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 900000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 902000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 904000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 906000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 908000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 910000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 912000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 914000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 916000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 918000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 920000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 922000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 924000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 926000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 928000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 930000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 932000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 934000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 936000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 938000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 940000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 942000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 944000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 946000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 948000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 950000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 952000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 954000, Minibatch Loss= 0.730594, Training Accuracy= 0.75000 Iter 956000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 958000, Minibatch Loss= 0.730590, Training Accuracy= 0.75000 Iter 960000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 962000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 964000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 966000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 968000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 970000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 972000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 974000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 976000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 978000, Minibatch Loss= 0.730592, Training Accuracy= 0.75000 Iter 980000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 982000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 984000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 986000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 988000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 990000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 992000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 994000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Iter 996000, Minibatch Loss= 0.730589, Training Accuracy= 0.75000 Iter 998000, Minibatch Loss= 0.730588, Training Accuracy= 0.75000 Optimization Finished!

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