Implemention LSTM example for MNIST data with tflearn

1. Tflearn is higher-level API for TensorFlow.

2. Dependencies: tensorflow 1.0, tflearn (sudo pip install tensorflow, tensorflow-gpu(GPU only), tflearn)

- Input: 28 rows of 28x1 fixel vector

- Output: 10 classes

3. Usage

- Training: python mnist_lstm.py

- Tensorboard: tensorboard --logdir=/tmp/tflearn_logs/

4. Result

$ python mnist_lstm.py

...
Training Step: 8600  | total loss: 0.03430 | time: 23.780s
| Adam | epoch: 010 | loss: 0.03430 - R2: 0.9763 -- iter: 55000/55000
training time: 131.180480003
predict time: 2.66158895493
accuracy:  97.53

5. Tensorboard