Mastering TensorFlow 1.x

Creating tensors from Python objects

We can create tensors from Python objects such as lists and NumPy arrays, using the tf.convert_to_tensor() operation with the following signature:

tf.convert_to_tensor(  value,  dtype=None,  name=None,  preferred_dtype=None  )

Let's create some tensors and print them for practice:

1. Create and print a 0-D Tensor:

tf_t=tf.convert_to_tensor(5.0,dtype=tf.float64)print('tf_t : ',tf_t)print('run(tf_t) : ',tfs.run(tf_t))

The output is as follows: 

tf_t :  Tensor("Const_1:0", shape=(), dtype=float64)run(tf_t) : 5.0

2. Create and print a 1-D Tensor:

a1dim = np.array([1,2,3,4,5.99])print("a1dim Shape : ",a1dim.shape)tf_t=tf.convert_to_tensor(a1dim,dtype=tf.float64)print('tf_t : ',tf_t)print('tf_t[0] : ',tf_t[0])print('tf_t[0] ...