Python - tensorflow.math.softplus() Last Updated : 16 Jun, 2020 Comments Improve Suggest changes Like Article Like Report TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. softplus() is used to compute element wise log(exp(features) + 1). Syntax: tensorflow.math.softplus(features, name) Parameters: features: It's a tensor. Allowed dtypes are half, bfloat16, float32, float64.name(optional): It defines the name for the operation. Returns: It returns a tensor. Example 1: Python3 # importing the library import tensorflow as tf # Initializing the input tensor a = tf.constant([ 5, 7, 9, 15], dtype = tf.float64) # Printing the input tensor print('a: ', a) # Calculating result res = tf.math.softplus(a) # Printing the result print('Result: ', res) Output: a: tf.Tensor([ 5. 7. 9. 15.], shape=(4, ), dtype=float64) Result: tf.Tensor([ 5.00671535 7.00091147 9.0001234 15.00000031], shape=(4, ), 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([ 5, 7, 9, 15], dtype = tf.float64) # Calculating tangent res = tf.math.softplus(a) # Plotting the graph plt.plot(a, res, color ='green') plt.title('tensorflow.math.softplus') plt.xlabel('Input') plt.ylabel('Result') plt.show() Output: Comment More infoAdvertise with us Next Article Python - tensorflow.math.softplus() A aman neekhara Follow Improve Article Tags : Machine Learning AI-ML-DS With Python Practice Tags : Machine Learning Similar Reads Python | Tensorflow nn.softplus() Tensorflow is an open-source machine learning library developed by Google. One of its applications is to develop deep neural networks. The module tensorflow.nn provides support for many basic neural network operations. An activation function is a function which is applied to the output of a neural n 3 min read Python - tensorflow.math.sin() TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning  neural networks. sin() is used to find element wise sine of x. Syntax: tf.math.sin(x, name) Parameters: x: It's the input tensor. Allowed dtype for this tensor are bfloat16, half, float 1 min read Python - tensorflow.math.rint() TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning  neural networks. rint() is used to find element-wise integer closest to x. Syntax: tf.math.rint(x, name) Parameter: x: It's the input tensor. Allowed dtype for this tensor are bfloat16, 2 min read Python - tensorflow.math.sigmoid() TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. sigmoid() is used to find element wise sigmoid of x. Syntax: tensorflow.math.sigmoid(x, name) Parameters: x: It's a tensor. Allowed dtypes are float16, float32, float64, 1 min read Python - tensorflow.math.subtract() TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. subtract() is used to compute element wise (x-y). Syntax: tensorflow.math.subtract(x, y, name) Parameters: x: It's a tensor. Allowed dtypes are bfloat16, half, float32, f 2 min read Like