ngraph.batch_norm_inference¶
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ngraph.batch_norm_inference(data: Union[_pyngraph.Node, int, float, numpy.ndarray], gamma: Union[_pyngraph.Node, int, float, numpy.ndarray], beta: Union[_pyngraph.Node, int, float, numpy.ndarray], mean: Union[_pyngraph.Node, int, float, numpy.ndarray], variance: Union[_pyngraph.Node, int, float, numpy.ndarray], epsilon: float, name: Optional[str] = None) → _pyngraph.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.
- Return:
The new node which performs BatchNormInference.