Inserts a dimension of 1 into a tensor's shape.
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]
`-1-input.dims() <= dim <= input.dims()`
This operation is related to `squeeze()`, which removes dimensions of size 1.
Public Methods
Output <T> |
asOutput
()
Returns the symbolic handle of a tensor.
|
static <T, U extends Number> ExpandDims <T> | |
Output <T> |
output
()
Contains the same data as `input`, but its shape has an additional
dimension of size 1 added.
|
Inherited Methods
Public Methods
public Output <T> asOutput ()
Returns the symbolic handle of a tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
public static ExpandDims <T> create ( Scope scope, Operand <T> input, Operand <U> axis)
Factory method to create a class wrapping a new ExpandDims operation.
Parameters
scope | current scope |
---|---|
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
- a new instance of ExpandDims
public Output <T> output ()
Contains the same data as `input`, but its shape has an additional dimension of size 1 added.