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)
