# TensorFlow – How to create one hot tensor

• Last Updated : 01 Aug, 2020

TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks.

One hot tensor is a Tensor in which all the values at indices where i =j and i!=j is same.

Method Used:

• one_hot: This method accepts a Tensor of indices, a scalar defining depth of the one hot dimension and returns a one hot Tensor with default on value 1 and off value 0. These on and off values can be modified.

Example 1:

## Python3

 `# importing the library ` `import` `tensorflow as tf ` ` `  `# Initializing the Input ` `indices ``=` `tf.constant([``1``, ``2``, ``3``]) ` ` `  `# Printing the Input ` `print``(``"Indices: "``, indices) ` ` `  `# Generating one hot Tensor ` `res ``=` `tf.one_hot(indices, depth ``=` `3``) ` ` `  `# Printing the resulting Tensors ` `print``(``"Res: "``, res )`

Output:

```Indices:  tf.Tensor([1 2 3], shape=(3, ), dtype=int32)
Res:  tf.Tensor(
[[0. 1. 0.]
[0. 0. 1.]
[0. 0. 0.]], shape=(3, 3), dtype=float32)

```

Example 2: This example explicitly defines the on and off values for the one hot tensor.

## Python3

 `# importing the library ` `import` `tensorflow as tf ` ` `  `# Initializing the Input ` `indices ``=` `tf.constant([``1``, ``2``, ``3``]) ` ` `  `# Printing the Input ` `print``(``"Indices: "``, indices) ` ` `  `# Generating one hot Tensor ` `res ``=` `tf.one_hot(indices, depth ``=` `3``, on_value ``=` `3``, off_value ``=``-``1``) ` ` `  `# Printing the resulting Tensors ` `print``(``"Res: "``, res )`

Output:

```Indices:  tf.Tensor([1 2 3], shape=(3, ), dtype=int32)
Res:  tf.Tensor(
[[-1  3 -1]
[-1 -1  3]
[-1 -1 -1]], shape=(3, 3), dtype=int32)

```

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