rnn_minist_01_input.py

from __future__ import print_function
import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)

element_size = 28
time_steps = 28
num_classes = 10
batch_size = 128
hidden_layer_size = 128

LOG_DIR = "logs/RNN_with_summaries"

_inputs = tf.placeholder(tf.float32,
                         shape=[None, time_steps, element_size],
                         name='inputs')
y = tf.placeholder(tf.float32, shape=[None, num_classes], name='labels')


# Processing inputs to work with scan function
# Current input shape: (batch_size, time_steps, element_size)
processed_input = tf.transpose(_inputs, perm=[1, 0, 2])
# Current input shape now: (time_steps,batch_size, element_size)