Python | Tensorflow abs() method
tensorflow.math
tf.abs()
tf.math.abs
absolute
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Syntax: tf.abs(x, name=None) or tf.math.abs(x, name=None) Parameters: x: A Tensor or SparseTensor of type float16, float32, float64, int32, int64, complex64 or complex128. name (optional): The name for the operation. Return type: A Tensor or SparseTensor with the same size and type as that of x with absolute values. For complex64 or complex128 input, the returned Tensor will be of type float32 or float64, respectively.
Code #1: For Floating point numbers
Python3
# Importing the Tensorflow library import tensorflow as tf # A constant vector of size 5 a = tf.constant([-0.5, -0.1, 0, 0.1, 0.5], dtype = tf.float32) # Applying the abs function and # storing the result in 'b' b = tf.abs(a, name ='abs') # Initiating a Tensorflow session with tf.Session() as sess: print('Input type:', a) print('Input:', sess.run(a)) print('Return type:', b) print('Output:', sess.run(b)) |
Output:
Input type: Tensor("Const:0", shape=(5, ), dtype=float32)
Input : [-0.5 -0.1 0. 0.1 0.5]
Return Type : Tensor("abs:0", shape=(5, ), dtype=float32)
Output : [0.5 0.1 0. 0.1 0.5]
Code #2:
Python3
# Importing the Tensorflow library import tensorflow as tf # Importing the NumPy library import numpy as np # Importing the matplotlib.pyplot function import matplotlib.pyplot as plt # A vector of size 11 with values from -5 to 5 a = np.linspace(-5, 5, 11) # Applying the absolute function and # storing the result in 'b' b = tf.abs(a, name ='abs') # Initiating a Tensorflow session with tf.Session() as sess: print('Input:', a) print('Output:', sess.run(b)) plt.plot(a, sess.run(b), color = 'red', marker = "o") plt.title("tensorflow.abs") plt.xlabel("X") plt.ylabel("Y") plt.show() |
Output:
Input: [-5. -4. -3. -2. -1. 0. 1. 2. 3. 4. 5.] Output: [5. 4. 3. 2. 1. 0. 1. 2. 3. 4. 5.]
Code #3: For Complex Numbers
Python3
# Importing the Tensorflow library import tensorflow as tf # A constant vector of size 2 a = tf.constant([[-2.25 + 4.75j], [-3.25 + 5.75j]], dtype = tf.complex64) # Applying the abs function and # storing the result in 'b' b = tf.abs(a, name ='abs') # Initiating a Tensorflow session with tf.Session() as sess: print('Input type:', a) print('Input:', sess.run(a)) print('Return type:', b) print('Output:', sess.run(b)) |
Output:
Input type: Tensor("Const_1:0", shape=(2, 1), dtype=complex64)
Input : [[-2.25+4.75j] [-3.25+5.75j]]
Return Type : Tensor("abs_1:0", shape=(2, 1), dtype=float32)
Output : [[5.255949 ] [6.6049223]]
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