tf.pad  |  TensorFlow v2.16.1 (original) (raw)

Pads a tensor.

This operation pads a tensor according to the paddings you specify.paddings is an integer tensor with shape [n, 2], where n is the rank oftensor. For each dimension D of input, paddings[D, 0] indicates how many values to add before the contents of tensor in that dimension, andpaddings[D, 1] indicates how many values to add after the contents oftensor in that dimension. If mode is "REFLECT" then both paddings[D, 0]and paddings[D, 1] must be no greater than tensor.dim_size(D) - 1. Ifmode is "SYMMETRIC" then both paddings[D, 0] and paddings[D, 1] must be no greater than tensor.dim_size(D).

t = tf.constant([[1, 2, 3], [4, 5, 6]])
paddings = tf.constant([[1, 1,], [2, 2]])
# 'constant_values' is 0.
# rank of 't' is 2.
tf.pad(t, paddings, "CONSTANT")  # [[0, 0, 0, 0, 0, 0, 0],
                                 #  [0, 0, 1, 2, 3, 0, 0],
                                 #  [0, 0, 4, 5, 6, 0, 0],
                                 #  [0, 0, 0, 0, 0, 0, 0]]

tf.pad(t, paddings, "REFLECT")  # [[6, 5, 4, 5, 6, 5, 4],
                                #  [3, 2, 1, 2, 3, 2, 1],
                                #  [6, 5, 4, 5, 6, 5, 4],
                                #  [3, 2, 1, 2, 3, 2, 1]]

tf.pad(t, paddings, "SYMMETRIC")  # [[2, 1, 1, 2, 3, 3, 2],
                                  #  [2, 1, 1, 2, 3, 3, 2],
                                  #  [5, 4, 4, 5, 6, 6, 5],
                                  #  [5, 4, 4, 5, 6, 6, 5]]