I am learning tensorflow using the tensorflow machine learning cookbook (https://github.com/nfmcclure/tensorflow_cookbook). I am currently on the NLP chapter (07). I am very confused about how one decides on the dimensions of the tensorflow variables. For example, in the bag of words example they use:
# Create variables for logistic regression
A = tf.Variable(tf.random_normal(shape=[embedding_size,1]))
b = tf.Variable(tf.random_normal(shape=[1,1]))
# Initialize placeholders
x_data = tf.placeholder(shape=[sentence_size], dtype=tf.int32)
y_target = tf.placeholder(shape=[1, 1], dtype=tf.float32)
and in the tf-idf example they use:
# Create variables for logistic regression
A = tf.Variable(tf.random_normal(shape=[max_features,1]))
b = tf.Variable(tf.random_normal(shape=[1,1]))
x_data = tf.placeholder(shape=[None, max_features], dtype=tf.float32)
y_target = tf.placeholder(shape=[None, 1], dtype=tf.float32)
How does one decide on when to use None vs. 1 in the placeholder shapes? Thank you!