Inserts a dimension of 1 into a tensor's shape.
tf.raw_ops.ExpandDims( input, axis, name=None )
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.
Returns | |
---|---|
A Tensor . Has the same type as input . |