class ngraph::op::v0::MVN¶

Overview¶

Operator performing Mean Variance Normalization. More…

#include <mvn.hpp>

class MVN: public ngraph::op::util::FusedOp
{
public:
    // construction

    MVN();

    MVN(
        const Output<Node>& data,
        bool across_channels = true,
        bool normalize_variance = true,
        double eps = 1e-9
        );

    MVN(
        const Output<Node>& data,
        AxisSet reduction_axes,
        bool normalize_variance = true,
        double eps = 1e-9
        );

    // methods

    virtual OutputVector decompose_op() const;
    virtual void validate_and_infer_types();
    virtual bool visit_attributes(AttributeVisitor& visitor);
    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const;
    double get_eps() const;
    bool get_across_channels() const;
    bool get_normalize_variance() const;
    AxisSet get_reduction_axes() const;
    void set_reduction_axes(AxisSet axes);
};

Detailed Documentation¶

Operator performing Mean Variance Normalization.

Construction¶

MVN(
    const Output<Node>& data,
    bool across_channels = true,
    bool normalize_variance = true,
    double eps = 1e-9
    )

Constructs an MVN operation.

Parameters:

data	Input tensor with data
normalize_variance	flag that denotes whether to perform variance normalization.
across_channels	flag that denotes if mean values are shared across channels.
eps	the number to be added to the variance to avoid division by zero when normalizing the value

MVN(
    const Output<Node>& data,
    AxisSet reduction_axes,
    bool normalize_variance = true,
    double eps = 1e-9
    )

Constructs an MVN operation.

Parameters:

data	Input tensor with data
reduction_axes	A list of axes, along which to reduce.
normalize_variance	flag that denotes whether to perform variance normalization.
eps	the number to be added to the variance to avoid division by zero when normalizing the value

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