tensorflow::ops::ExpandDims

#include <array_ops.h>

Inserts a dimension of 1 into a tensor's shape.

Summary

Given a tensor input, this operation inserts a dimension of 1 at the dimension index axis of input's shape. The dimension index axis starts at zero; if you specify a negative number for axis it is counted backward from the end.

This operation is useful if you want to add a batch dimension to a single element. For example, if you have a single image of shape [height, width, channels], you can make it a batch of 1 image with expand_dims(image, 0), which will make the shape [1, height, width, channels].

Other examples:

# 't' is a tensor of shape [2]
shape(expand_dims(t, 0)) ==> [1, 2]
shape(expand_dims(t, 1)) ==> [2, 1]
shape(expand_dims(t, -1)) ==> [2, 1]
 

# 't2' is a tensor of shape [2, 3, 5]
shape(expand_dims(t2, 0)) ==> [1, 2, 3, 5]
shape(expand_dims(t2, 2)) ==> [2, 3, 1, 5]
shape(expand_dims(t2, 3)) ==> [2, 3, 5, 1]

This operation requires that:

-1-input.dims() <= dim <= input.dims()

This operation is related to squeeze(), which removes dimensions of size 1.

Arguments:

  • scope: A Scope object
  • axis: 0-D (scalar). Specifies the dimension index at which to expand the shape of input. Must be in the range [-rank(input) - 1, rank(input)].

Returns:

  • Output: Contains the same data as input, but its shape has an additional dimension of size 1 added.

Constructors and Destructors
ExpandDims(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input axis)

Public attributes
operation
output

Public functions
node() const
::tensorflow::Node *
operator::tensorflow::Input() const
operator::tensorflow::Output() const

Public attributes

operation

Operation operation

output

::tensorflow::Output output

Public functions

ExpandDims

 ExpandDims(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input axis
)

node

::tensorflow::Node * node() const

operator::tensorflow::Input

 operator::tensorflow::Input() const

operator::tensorflow::Output

 operator::tensorflow::Output() const