TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
gather_nd() is used to gather the slice from input tensor based on the indices provided.
Syntax: tensorflow.gather_nd( params, indices, batch_dims, name)
Parameters:
- params: It is a Tensor with rank greater than or equal to axis+1.
- indices: It is a Tensor of dtype int32 or int64.
- batch_dims: It is an integer representing the number o batch dimension. It must be less than rank(indices).
- name: It defines the name for the operation.
Returns:
It returns a Tensor having same dtype as param.
Example 1:
Python3
# Importing the library import tensorflow as tf # Initializing the input data = tf.constant([[1, 2], [3, 4], [5, 6]]) indices = tf.constant([[1], [0], [1]]) # Printing the input print('data: ',data) print('indices: ',indices) # Calculating result res = tf.gather_nd(data, indices) # Printing the result print('res: ',res) |
Output:
data: tf.Tensor( [[1 2] [3 4] [5 6]], shape=(3, 2), dtype=int32) indices: tf.Tensor( [[1] [0] [1]], shape=(3, 1), dtype=int32) res: tf.Tensor( [[3 4] [1 2] [3 4]], shape=(3, 2), dtype=int32)
Example 2:
Python3
# Importing the library import tensorflow as tf # Initializing the input data = tf.constant([[1, 2, 3], [3, 4, 5], [5, 6, 7]]) indices = tf.constant([[1, 0], [0, 2], [1, 2]]) # Printing the input print('data: ',data) print('indices: ',indices) # Calculating result res = tf.gather_nd(data, indices) # Printing the result print('res: ',res) |
Output:
data: tf.Tensor( [[1 2 3] [3 4 5] [5 6 7]], shape=(3, 3), dtype=int32) indices: tf.Tensor( [[1 0] [0 2] [1 2]], shape=(3, 2), dtype=int32) res: tf.Tensor([3 3 5], shape=(3,), dtype=int32)
