Now, we arrive at the fun part—the neural network. The complete code to train this model is available at the following link: https://github.com/mlwithtf/mlwithtf/blob/master/chapter_02/training.py
To train the model, we'll import several more modules:
import sys, os
import tensorflow as tf
import numpy as np
sys.path.append(os.path.realpath('..'))
import data_utils
import logmanager
Then, we will define a few parameters for the training process:
batch_size = 128
num_steps = 10000
learning_rate = 0.3
data_showing_step = 500
After that, we will use the data_utils package to load the dataset that was downloaded in the previous section:
dataset, image_size, num_of_classes, num_of_channels =
data_utils.prepare_not_mnist_dataset(root_dir="..")
dataset = data_utils.reformat(dataset, image_size, num_of_channels,
num_of_classes)
print...