tensorflow:: ops:: MirrorPad

Pads a tensor with mirrored values.

Summary

This operation pads a input with mirrored values according to the paddings you specify. paddings is an integer tensor with shape [n, 2] , where n is the rank of input . For each dimension D of input , paddings[D, 0] indicates how many values to add before the contents of input in that dimension, and paddings[D, 1] indicates how many values to add after the contents of input in that dimension. Both paddings[D, 0] and paddings[D, 1] must be no greater than input.dim_size(D) (or input.dim_size(D) - 1 ) if copy_border is true (if false, respectively).

The padded size of each dimension D of the output is:

paddings(D, 0) + input.dim_size(D) + paddings(D, 1)

For example:

# 't' is [[1, 2, 3], [4, 5, 6]].
# 'paddings' is [[1, 1]], [2, 2]].
# 'mode' is SYMMETRIC.
# rank of 't' is 2.
pad(t, paddings) ==> [[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]]

Args:

• scope: A Scope object
• input: The input tensor to be padded.
• paddings: A two-column matrix specifying the padding sizes. The number of rows must be the same as the rank of input .
• mode: Either REFLECT or SYMMETRIC . In reflect mode the padded regions do not include the borders, while in symmetric mode the padded regions do include the borders. For example, if input is [1, 2, 3] and paddings is [0, 2] , then the output is [1, 2, 3, 2, 1] in reflect mode, and it is [1, 2, 3, 3, 2] in symmetric mode.

Returns:

• Output : The padded tensor.

Public attributes

Operation operation

::tensorflow::Output output

Public functions

 MirrorPad(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input paddings,
  StringPiece mode
)

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const