Use tf.gather_nd() in TensorFlow

Teach me how to use tf.gather_nd()

tf.gather_nd() is a function in TensorFlow that allows you to gather slices from a tensor using indices specified in a multi-dimensional array. It's particularly useful when you want to extract specific elements from a tensor based on their coordinates. Let's break down how to use tf.gather_nd() step by step:

Understanding tf.gather_nd()

1. Parameters:

   • params: The tensor from which to gather values.
   • indices: The index tensor, which must be an integer tensor. Each element in this tensor specifies the coordinates of the values to gather.

2. Returns:

   • A tensor with elements from params specified by indices.

Example Usage

Let's go through a simple example to demonstrate how tf.gather_nd() works.

Imagine you have a 2D tensor (like a matrix) and you want to extract specific elements from it. Your tensor (params) might look like this:

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1[[1, 2], 
2 [3, 4], 
3 [5, 6]]

And you want to extract the elements 2, 4, and 5. To do this, you need to provide their coordinates in the indices tensor:

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1[[0, 1],  # Coordinates for 2
2 [1, 1],  # Coordinates for 4
3 [2, 0]]  # Coordinates for 5

Now, let's put this into code:

python
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1import tensorflow as tf
2
3# Define the tensor (params)
4params = tf.constant([[1, 2], [3, 4], [5, 6]])
5
6# Define the indices
7indices = tf.constant([[0, 1], [1, 1], [2, 0]])
8
9# Use tf.gather_nd
10result = tf.gather_nd(params, indices)
11
12# Print the result
13print(result)  # Output: [2, 4, 5]

Advanced Use Case

tf.gather_nd() becomes more powerful with higher-dimensional tensors. For example, if you have a 3D tensor and want to extract certain 2D slices or 1D vectors, you can do so by adjusting the indices tensor accordingly.

Would you like to see an advanced example or have any specific scenario in mind where you'd like to apply tf.gather_nd()?