scale
Input
- x:
- Required: yes
- Type: float32, float16
- Description: input tensor
- Restrictions: none
- scale:
- Required: yes
- Type: float32, float16
- Description: scale tensor
- Restrictions: none
- bias:
- Required: no
- Type: float32, float16
- Description: bias tensor
- Restrictions: none
Attribute
- axis:
- Required: no
- Type: int
- Description: the first axis of bottom[0] along which to apply scaling (default = 1). For example, if bottom[0] is 4D with shape 100 x 3 x 40 x 60, the output top[0] will have the same shape, and bottom[1] may have any of the following shapes (for the given value of axis):
(axis == 0 == -4) 100; 100x3; 100x3x40; 100x3x40x60
(axis == 1 == -3) 3; 3x40; 3x40x60
(axis == 2 == -2) 40; 40x60
(axis == 3 == -1) 60
Furthermore, bottom[1] may have the empty shape (regardless of the value of axis) – a scalar multiplier.
- Restriction: Must be in the range [–rank(x), rank(x)).
- num_axes:
- Required: no
- Type: int
- Description: the number of axes of the input covered by the scale parameter (default = 1). Ignored unless just one bottom is given. Set to –1 to cover all axes starting from axis. Set to 0 to multiply with a scalar.
- Restriction: Must be in the range [–1, rank(x)). If axis_= axis > 0: axis, axis + rank(x), then: num_axes + axis_ <= rank(x).
Output
y:
- Required: yes
- Type: float32, float16
- Description: output tensor
- Restrictions: none
Parent topic: Supported Caffe Operators