hello_world.txt

$ python mnist_mlp.py
60000 train samples
10000 test samples
2019-10-30 15:59:27.542886: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-10-30 15:59:27.870733: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:06:00.0
2019-10-30 15:59:27.873027: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 1 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:07:00.0
2019-10-30 15:59:27.875312: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 2 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:0d:00.0
2019-10-30 15:59:27.877608: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 3 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:0e:00.0
2019-10-30 15:59:27.879883: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 4 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:86:00.0
2019-10-30 15:59:27.882293: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 5 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:87:00.0
2019-10-30 15:59:27.884583: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 6 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:8d:00.0
2019-10-30 15:59:27.886826: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 7 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:8e:00.0
2019-10-30 15:59:27.888706: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 8 with properties:
name: GeForce GT 710 major: 3 minor: 5 memoryClockRate(GHz): 0.954
pciBusID: 0000:88:00.0
2019-10-30 15:59:27.889998: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2019-10-30 15:59:27.891970: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2019-10-30 15:59:27.893952: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2019-10-30 15:59:27.894994: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2019-10-30 15:59:27.897129: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2019-10-30 15:59:27.899073: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2019-10-30 15:59:27.903647: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-10-30 15:59:27.943770: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1731] Ignoring visible gpu device (device: 8, name: GeForce GT 710, pci bus id: 0000:88:00.0, compute capability: 3.5) with core count: 1. The minimum required count is 8. You can adjust this requirement with the env var TF_MIN_GPU_MULTIPROCESSOR_COUNT.
2019-10-30 15:59:27.943789: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0, 1, 2, 3, 4, 5, 6, 7
2019-10-30 15:59:27.944165: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2019-10-30 15:59:27.983894: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2294745000 Hz
2019-10-30 15:59:27.990760: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55c0390b9f00 executing computations on platform Host. Devices:
2019-10-30 15:59:27.990813: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): Host, Default Version
2019-10-30 15:59:30.040987: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:06:00.0
2019-10-30 15:59:30.043022: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 1 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:07:00.0
2019-10-30 15:59:30.045075: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 2 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:0d:00.0
2019-10-30 15:59:30.047315: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 3 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:0e:00.0
2019-10-30 15:59:30.049376: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 4 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:86:00.0
2019-10-30 15:59:30.051382: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 5 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:87:00.0
2019-10-30 15:59:30.053440: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 6 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:8d:00.0
2019-10-30 15:59:30.055447: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 7 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:8e:00.0
2019-10-30 15:59:30.055509: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2019-10-30 15:59:30.055558: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2019-10-30 15:59:30.055576: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2019-10-30 15:59:30.055592: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2019-10-30 15:59:30.055607: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2019-10-30 15:59:30.055622: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2019-10-30 15:59:30.055638: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-10-30 15:59:30.087632: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0, 1, 2, 3, 4, 5, 6, 7
2019-10-30 15:59:30.087688: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2019-10-30 15:59:30.108538: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-10-30 15:59:30.108559: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0 1 2 3 4 5 6 7
2019-10-30 15:59:30.108571: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N Y Y Y N N N N
2019-10-30 15:59:30.108578: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 1:   Y N Y Y N N N N
2019-10-30 15:59:30.108586: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 2:   Y Y N Y N N N N
2019-10-30 15:59:30.108593: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 3:   Y Y Y N N N N N
2019-10-30 15:59:30.108600: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 4:   N N N N N Y Y Y
2019-10-30 15:59:30.108607: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 5:   N N N N Y N Y Y
2019-10-30 15:59:30.108614: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 6:   N N N N Y Y N Y
2019-10-30 15:59:30.108622: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 7:   N N N N Y Y Y N
2019-10-30 15:59:30.133271: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10799 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:06:00.0, compute capability: 3.7)
2019-10-30 15:59:30.138268: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 10799 MB memory) -> physical GPU (device: 1, name: Tesla K80, pci bus id: 0000:07:00.0, compute capability: 3.7)
2019-10-30 15:59:30.142531: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:2 with 10799 MB memory) -> physical GPU (device: 2, name: Tesla K80, pci bus id: 0000:0d:00.0, compute capability: 3.7)
2019-10-30 15:59:30.147251: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:3 with 10799 MB memory) -> physical GPU (device: 3, name: Tesla K80, pci bus id: 0000:0e:00.0, compute capability: 3.7)
2019-10-30 15:59:30.152052: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:4 with 10799 MB memory) -> physical GPU (device: 4, name: Tesla K80, pci bus id: 0000:86:00.0, compute capability: 3.7)
2019-10-30 15:59:30.156770: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:5 with 10799 MB memory) -> physical GPU (device: 5, name: Tesla K80, pci bus id: 0000:87:00.0, compute capability: 3.7)
2019-10-30 15:59:30.161112: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:6 with 10799 MB memory) -> physical GPU (device: 6, name: Tesla K80, pci bus id: 0000:8d:00.0, compute capability: 3.7)
2019-10-30 15:59:30.165508: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:7 with 10799 MB memory) -> physical GPU (device: 7, name: Tesla K80, pci bus id: 0000:8e:00.0, compute capability: 3.7)
2019-10-30 15:59:30.169185: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55c03b8e3590 executing computations on platform CUDA. Devices:
2019-10-30 15:59:30.169206: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): Tesla K80, Compute Capability 3.7
2019-10-30 15:59:30.169229: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (1): Tesla K80, Compute Capability 3.7
2019-10-30 15:59:30.169237: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (2): Tesla K80, Compute Capability 3.7
2019-10-30 15:59:30.169246: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (3): Tesla K80, Compute Capability 3.7
2019-10-30 15:59:30.169254: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (4): Tesla K80, Compute Capability 3.7
2019-10-30 15:59:30.169262: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (5): Tesla K80, Compute Capability 3.7
2019-10-30 15:59:30.169271: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (6): Tesla K80, Compute Capability 3.7
2019-10-30 15:59:30.169279: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (7): Tesla K80, Compute Capability 3.7
Model: "sequential"
_________________________________________________________________
Layer (type)                 Output Shape              Param #
=================================================================
dense (Dense)                (None, 512)               401920
_________________________________________________________________
dropout (Dropout)            (None, 512)               0
_________________________________________________________________
dense_1 (Dense)              (None, 512)               262656
_________________________________________________________________
dropout_1 (Dropout)          (None, 512)               0
_________________________________________________________________
dense_2 (Dense)              (None, 10)                5130
=================================================================
Total params: 669,706
Trainable params: 669,706
Non-trainable params: 0
_________________________________________________________________
Train on 60000 samples, validate on 10000 samples
Epoch 1/20
2019-10-30 15:59:31.607390: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
60000/60000 [==============================] - 4s 65us/sample - loss: 0.2451 - accuracy: 0.9249 - val_loss: 0.1270 - val_accuracy: 0.9601
Epoch 2/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.1011 - accuracy: 0.9695 - val_loss: 0.0840 - val_accuracy: 0.9746
Epoch 3/20
60000/60000 [==============================] - 3s 53us/sample - loss: 0.0753 - accuracy: 0.9781 - val_loss: 0.0790 - val_accuracy: 0.9767
Epoch 4/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0615 - accuracy: 0.9814 - val_loss: 0.0725 - val_accuracy: 0.9810
Epoch 5/20
60000/60000 [==============================] - 3s 53us/sample - loss: 0.0502 - accuracy: 0.9846 - val_loss: 0.0717 - val_accuracy: 0.9798
Epoch 6/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0444 - accuracy: 0.9867 - val_loss: 0.0750 - val_accuracy: 0.9819
Epoch 7/20
60000/60000 [==============================] - 3s 53us/sample - loss: 0.0384 - accuracy: 0.9887 - val_loss: 0.0814 - val_accuracy: 0.9809
Epoch 8/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0348 - accuracy: 0.9902 - val_loss: 0.0767 - val_accuracy: 0.9829
Epoch 9/20
60000/60000 [==============================] - 3s 52us/sample - loss: 0.0311 - accuracy: 0.9906 - val_loss: 0.0822 - val_accuracy: 0.9838
Epoch 10/20
60000/60000 [==============================] - 3s 49us/sample - loss: 0.0293 - accuracy: 0.9916 - val_loss: 0.0829 - val_accuracy: 0.9836
Epoch 11/20
60000/60000 [==============================] - 3s 51us/sample - loss: 0.0266 - accuracy: 0.9927 - val_loss: 0.0811 - val_accuracy: 0.9847
Epoch 12/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0241 - accuracy: 0.9929 - val_loss: 0.0985 - val_accuracy: 0.9830
Epoch 13/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0238 - accuracy: 0.9933 - val_loss: 0.0987 - val_accuracy: 0.9825
Epoch 14/20
60000/60000 [==============================] - 3s 49us/sample - loss: 0.0211 - accuracy: 0.9941 - val_loss: 0.1025 - val_accuracy: 0.9816
Epoch 15/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0222 - accuracy: 0.9939 - val_loss: 0.1171 - val_accuracy: 0.9819
Epoch 16/20
60000/60000 [==============================] - 3s 49us/sample - loss: 0.0205 - accuracy: 0.9945 - val_loss: 0.0975 - val_accuracy: 0.9833
Epoch 17/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0181 - accuracy: 0.9952 - val_loss: 0.1019 - val_accuracy: 0.9840
Epoch 18/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0175 - accuracy: 0.9951 - val_loss: 0.1147 - val_accuracy: 0.9839
Epoch 19/20
60000/60000 [==============================] - 3s 50us/sample - loss: 0.0181 - accuracy: 0.9951 - val_loss: 0.1196 - val_accuracy: 0.9834
Epoch 20/20
60000/60000 [==============================] - 3s 49us/sample - loss: 0.0178 - accuracy: 0.9956 - val_loss: 0.1321 - val_accuracy: 0.9829
Test loss: 0.13206868417525783
Test accuracy: 0.9829