openvino.runtime.opset9.batch_norm_inference

openvino.runtime.opset9.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.