,

@coty_beier

To get specific rows of a tensor in TensorFlow, you can use the indexing capabilities of TensorFlow. Here's an example:

1 2 3 4 5 6 7 8 9 10 11 12 13 |
import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # Get specific rows rows = tf.constant([0, 2]) # Rows 0 and 2 selected_rows = tf.gather(tensor, rows) # Run the session with tf.Session() as sess: result = sess.run(selected_rows) print(result) |

Output:

1 2 |
[[1 2 3] [7 8 9]] |

In this example, `tf.constant([[1, 2, 3], [4, 5, 6], [7, 8, 9]])`

creates a 3x3 tensor. `tf.constant([0, 2])`

specifies the rows to select, and `tf.gather(tensor, rows)`

selects those rows from the tensor. The result is evaluated using a session and printed.

Note that indexing in TensorFlow starts from 0. If you want to select multiple non-consecutive rows, you can provide a list of row indices in the `rows`

tensor.