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Tensorflow で Mnist

Tensorflow で Mnist をやってみます。

ドキュメント

MNIST For ML Beginners  |  TensorFlow

サンプルコード

tensorflow/mnist_softmax.py at r1.1 · tensorflow/tensorflow · GitHub

これを使えということなので、使ってみます。

mnist 用のデータを自動でダウンロードしてくれます。
Chainer 用に既にダウンロードしてありますが、まぁ、気にしません!

$ python mnist_softmax.py 
Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.
Extracting /tmp/tensorflow/mnist/input_data/train-images-idx3-ubyte.gz
Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.
Extracting /tmp/tensorflow/mnist/input_data/train-labels-idx1-ubyte.gz
Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.
Extracting /tmp/tensorflow/mnist/input_data/t10k-images-idx3-ubyte.gz
Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.
Extracting /tmp/tensorflow/mnist/input_data/t10k-labels-idx1-ubyte.gz
2017-05-09 15:08:44.979276: 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.
2017-05-09 15:08:44.979344: 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.
2017-05-09 15:08:45.215246: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2017-05-09 15:08:45.215956: I tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 with properties: 
name: GeForce GTX 1060 6GB
major: 6 minor: 1 memoryClockRate (GHz) 1.7845
pciBusID 0000:06:00.0
Total memory: 5.93GiB
Free memory: 5.84GiB
2017-05-09 15:08:45.215999: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0 
2017-05-09 15:08:45.216016: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0:   Y 
2017-05-09 15:08:45.216045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1060 6GB, pci bus id: 0000:06:00.0)
0.9186