Python – tensorflow.raw_ops.Log1p()

• Last Updated : 05 Jun, 2020

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. Log1p() is used to find element wise logarithm of (1+x) for input x.

Syntax: tf.raw_ops.Log1p(x, name)

Parameters:

• x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64, complex64, complex128.
• 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 logarithm(1 + x) ` `res ``=` `tf.raw_ops.Log1p(x ``=` `a) ` ` `  `# Printing the result ` `print``(``'Result: '``, res) `

Output:

```Input:  tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64)
Result:  tf.Tensor([0.69314718 1.09861229 1.38629436 1.60943791 1.79175947], 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 logarithm(1 + x) ` `res ``=` `tf.raw_ops.Log1p(x ``=` `a) ` ` `  `# Plotting the graph ` `plt.plot(a, res, color ``=``'green'``) ` `plt.title(``'tensorflow.raw_ops.Log1p'``) ` `plt.xlabel(``'Input'``) ` `plt.ylabel(``'Result'``) ` `plt.show() `

Output:

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