How to select specific columns of a 2D tensor in TensorFlow?

Question

This question is being processed as a generalized slice , what would be the best way to get the columns of op-assemblies of a 2D tensor (matrix)? For example, for a tensor t:

1 2 3 4
5 6 7 8 

and indices [1,3], I would like to get:

2 4
6 8

which is equivalent to numpy t[:, [1,3]].

Answer 1

So far I have created a workaround by smoothing the input and using the command gather:

def gather_cols(params, indices, name=None):
    """Gather columns of a 2D tensor.

    Args:
        params: A 2D tensor.
        indices: A 1D tensor. Must be one of the following types: ''int32'', ''int64''.
        name: A name for the operation (optional).

    Returns:
        A 2D Tensor. Has the same type as ''params''.
    """
    with tf.op_scope([params, indices], name, "gather_cols") as scope:
        # Check input
        params = tf.convert_to_tensor(params, name="params")
        indices = tf.convert_to_tensor(indices, name="indices")
        try:
            params.get_shape().assert_has_rank(2)
        except ValueError:
            raise ValueError('\'params\' must be 2D.')
        try:
            indices.get_shape().assert_has_rank(1)
        except ValueError:
            raise ValueError('\'indices\' must be 1D.')

        # Define op
        p_shape = tf.shape(params)
        p_flat = tf.reshape(params, [-1])
        i_flat = tf.reshape(tf.reshape(tf.range(0, p_shape[0]) * p_shape[1],
                                       [-1, 1]) + indices, [-1])
        return tf.reshape(tf.gather(p_flat, i_flat),
                          [p_shape[0], -1])

For what:

params = tf.constant([[1, 2, 3],
                      [4, 5, 6]])
indices = [0, 2]
op = gather_cols(params, indices)

produces the expected result:

[[1 3]
 [4 6]]

Answer 2

There is a function named that retrieves tensor rows . tf.nn.embedding_lookup(params, ind)params

, , t . tf.transpose(t) ( t). .

import tensorflow as tf


t = tf.constant([[1, 2, 3], 
                 [4, 5, 6]])
ind = tf.constant([0, 2])

result = tf.transpose(tf.nn.embedding_lookup(tf.transpose(t), ind))

with tf.Session() as sess:
    print(sess.run(result))

Answer 3

Meanwhile, the method gatherhas a parameter axis.

import tensorflow as tf
params = tf.constant([[1,2,3],[4,5,6]])
indices = [0,2]
op = tf.gather(params, indices, axis=1)

makes a conclusion

[[1 3]
 [4 6]]