TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow raw_ops provides low level access to all TensorFlow operations. Acos() is used to find element wise acos of x.
Syntax: tf.raw_ops.Acos(x, name)
Arguments:
- x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64.
- name(optional): It defines the name for the operation.
Returns: It returns a tensor of same dtype as x.
Note: It only takes keyword arguments.
Example 1:
Python3
# Importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([.2, .5, .7, 1], dtype=tf.float64)# Printing the input tensorprint('Input: ', a)# Calculating Acosres = tf.raw_ops.Acos(x=a)# Printing the resultprint('Result: ', res) |
Output:
Input: tf.Tensor([0.2 0.5 0.7 1. ], shape=(4,), dtype=float64) Result: tf.Tensor([1.36943841 1.04719755 0.79539883 0. ], shape=(4,), dtype=float64)
Example 2: Visualization
Python3
# importing the libraryimport tensorflow as tfimport matplotlib.pyplot as plt# Initializing the input tensora = tf.constant([.2, .5, .7, 1], dtype=tf.float64)# Calculating Acosres = tf.raw_ops.Acos(x=a)# Plotting the graphplt.plot(a, res, color='green')plt.title('tensorflow.raw_ops.Acos')plt.xlabel('Input')plt.ylabel('Result')plt.show() |
Output:
tensorflow.raw_ops.Acos
