tf.add_to_collection

(tf.GraphKeys, var_list)

The tf.add_to_collection() function is used to add variables, tensors, or operations to a collection. A collection is a grouping of objects in a TensorFlow graph that can be retrieved or modified as a unit.

The function takes two arguments:

1. GraphKeys: This is a predefined collection of keys that TensorFlow provides. Some examples include GLOBAL_VARIABLES, TRAINABLE_VARIABLES, and LOSSES. These keys are used to group objects by their purpose or properties.

2. var_list: This is a list of variables, tensors, or operations that will be added to the collection.

For example, to add a variable to the GLOBAL_VARIABLES collection, you would use the following code:

import tensorflow as tf

# Define a variable
my_var = tf.Variable(0.0, name='my_variable')

# Add the variable to the GLOBAL_VARIABLES collection
tf.add_to_collection(tf.GraphKeys.GLOBAL_VARIABLES, my_var)

Once an object is added to a collection, it can be retrieved using the tf.get_collection() function. For example, to retrieve all variables in the GLOBAL_VARIABLES collection, you would use the following code:

# Get all variables in the GLOBAL_VARIABLES collection
global_vars = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES)