openvino.runtime.opset1.batch_norm_inference¶
- openvino.runtime.opset1.batch_norm_inference(data: Union[openvino.pyopenvino.Node, int, float, numpy.ndarray], gamma: Union[openvino.pyopenvino.Node, int, float, numpy.ndarray], beta: Union[openvino.pyopenvino.Node, int, float, numpy.ndarray], mean: Union[openvino.pyopenvino.Node, int, float, numpy.ndarray], variance: Union[openvino.pyopenvino.Node, int, float, numpy.ndarray], epsilon: float, name: Optional[str] = None) openvino.pyopenvino.Node¶
Perform layer normalizes a input tensor by mean and variance with appling scale and offset.
- Parameters
data – The input tensor with data for normalization.
gamma – The scalar scaling for normalized value.
beta – The bias added to the scaled normalized value.
mean – The value for mean normalization.
variance – The value for variance normalization.
epsilon – The number to be added to the variance to avoid division by zero when normalizing a value.
name – The optional name of the output node.
- Returns
The new node which performs BatchNormInference.