# What is the meaning of the word logits in TensorFlow ?

What is the meaning of the word logits in TensorFlow ?

In **TensorFlow**, **logits** are the values to be used as input to **softmax.**

Hence that** logits** is a function in maths

The function **σ−1(x)** is called the **logit** in statistics, but this term is more rarely used in machine learning. **σ−1(x)** stands for the inverse function of logistic **sigmoid** function.

For **TensorFlow**, **logits** is commonly seen as the name of last layer

** logits** is the output of the neural network before going through the** softmax** activation function.

We can also use **softmax** as the activation function in the last layer of our design, for computation, we separate **logits**. So that it is more efficient to calculate **softmax** and cross-entropy loss together. Note that **cross-entropy** is a cost function cannot be used in forward propagation.