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. Cos() is used to find element wise cosine of x.
Syntax: tf.raw_ops.Cos(x, name)
Parameters:
- x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64.
- name(optional): It’s 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 library import tensorflow as tf # Initializing the input tensor a = tf.constant([ 1 , 2 , 3 , 4 , 5 ], dtype = tf.float64) # Printing the input tensor print ( 'Input: ' , a) # Calculating cosine res = tf.raw_ops.Cos(x = a) # Printing the result print ( 'Result: ' , res) |
Output:
Input: tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64) Result: tf.Tensor([ 0.54030231 -0.41614684 -0.9899925 -0.65364362 0.28366219], shape=(5, ), dtype=float64)
Example 2: Visualization
Python3
# importing the library import tensorflow as tf import matplotlib.pyplot as plt # Initializing the input tensor a = tf.constant([ 1 , 2 , 3 , 4 , 5 ], dtype = tf.float64) # Calculating cosine res = tf.raw_ops.Cos(x = a) # Plotting the graph plt.plot(a, res, color = 'green' ) plt.title( 'tensorflow.raw_ops.Cos' ) plt.xlabel( 'Input' ) plt.ylabel( 'Result' ) plt.show() |
Output:
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