- First, we start by loading the necessary libraries and declaring the TensorFlow application flags as follows:
import os import re import numpy as np import tensorflow as tf from tensorflow.python.framework import ops ops.reset_default_graph() # Define App Flagstf.flags.DEFINE_string("storage_folder", "temp", "Where to store model and data.")tf.flags.DEFINE_float('learning_rate', 0.0005, 'Initial learning rate.')tf.flags.DEFINE_float('dropout_prob', 0.5, 'Per to keep probability for dropout.')tf.flags.DEFINE_integer('epochs', 20, 'Number of epochs for training.')tf.flags.DEFINE_integer('batch_size', 250, 'Batch Size for training.')tf.flags.DEFINE_integer('rnn_size', 15, 'RNN feature size.')tf.flags.DEFINE_integer('embedding_size', ...