Tensors generated from library functions

Tensors can also be generated from various TensorFlow functions. These generated tensors can either be assigned to a constant or a variable, or provided to their constructor at the time of initialization.

As an example, the following code generates a vector of 100 zeroes and prints it:

a=tf.zeros((100,))
print(tfs.run(a))

TensorFlow provides different types of functions to populate the tensors at the time of their definition:

• Populating all elements with the same values
• Populating elements with sequences
• Populating elements with a random probability distribution, such as the normal distribution or the uniform distribution