How to fetch specific rows from a tensor in TensorFlow?
How to fetch specific rows from a tensor in TensorFlow?
2 answers
@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:
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[[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.