So far, we haven't started to build our computational graph for this classifier. Let's start off by creating the session variable that will be responsible for executing the computational graph we are going to build:
sess = tf.Session()
Next up, we are going to define our model's placeholders, which will be used to feed data into the computational graph:
input_values = tf.placeholder(tf.float32, shape=[None, 784]
When we specify None in our placeholder's first dimension, it means the placeholder can be fed as many examples as we like. In this case, our placeholder can be fed any number of examples, where each example has a 784 value.
Now, we need to define another placeholder for feeding the image labels. Also we'll be ...