TensorFlow 1.x Deep Learning Cookbook

How to do it...

Let's start with constants:

1. We can declare a scalar constant:

t_1 = tf.constant(4)   

2. A constant vector of shape [1,3] can be declared as follows:

t_2 = tf.constant([4, 3, 2]) 

3. To create a tensor with all elements zero, we use tf.zeros(). This statement creates a zero matrix of shape [M,N] with dtype (int32, float32, and so on):

tf.zeros([M,N],tf.dtype)   

Let's take an example:

zero_t = tf.zeros([2,3],tf.int32) # Results in an 2×3 array of zeros: [[0 0 0], [0 0 0]] 

4. We can also create tensor constants of the same shape as an existing Numpy array or tensor constant as follows:

tf.zeros_like(t_2) # Create a zero matrix of same shape as t_2  tf.ones_like(t_2) # Creates a ones matrix of same shape as t_2

5. We can create a tensor ...