,

@coty_beier

To fetch specific rows from a tensor in TensorFlow, you can use the indexing syntax `tensor[start:end]`

. Here's an example:

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import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # Fetch specific rows specific_rows = tensor[1:3] # Run a TensorFlow session to print the result with tf.Session() as sess: result = sess.run(specific_rows) print(result) |

Output:

1 2 |
[[4 5 6] [7 8 9]] |

In this example, `specific_rows = tensor[1:3]`

fetches rows 1 and 2 from the tensor `tensor`

. The resulting tensor `specific_rows`

contains the selected rows.

,

@coty_beier

To fetch specific rows from a tensor in TensorFlow, you can use tf.gather() function which allows you to gather slices of a tensor according to the indices provided.

Here's an example of how to fetch specific rows from a tensor using tf.gather():

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import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # Define the indices of the rows you want to fetch indices = [1, 2] # Fetch specific rows using tf.gather() specific_rows = tf.gather(tensor, indices) # Run a TensorFlow session to print the result with tf.Session() as sess: result = sess.run(specific_rows) print(result) |

Output:

1 2 |
[[4 5 6] [7 8 9]] |

In this example, `indices = [1, 2]`

specifies that we want to fetch rows at indices 1 and 2 from the tensor. The `tf.gather()`

function is then used to retrieve these specific rows, resulting in a new tensor containing the selected rows.