Backends/SiaNet.Backend.MxNet/NDArrayOps.cs
/// <summary>
/// Draw random samples from a generalized negative binomial distribution.Samples are distributed according to a generalized negative binomial distribution parametrized by*mu* (mean) and *alpha* (dispersion). *alpha* is defined as *1/k* where *k* is the failure limit of thenumber of unsuccessful experiments (generalized to real numbers).Samples will always be returned as a floating point data type.Example::   generalized_negative_binomial(mu=2.0, alpha=0.3, shape=(2,2)) = [[ 2.,  1.],                                                                    [ 6.,  4.]]Defined in G:\deeplearn\mxnet\src\operator\random\sample_op.cc:L158
/// </summary>
/// <param name="@out">output NDArray</param>
/// <param name="mu">Mean of the negative binomial distribution.</param>
/// <param name="alpha">Alpha (dispersion) parameter of the negative binomial distribution.</param>
/// <param name="shape">Shape of the output.</param>
/// <param name="ctx">Context of output, in format [cpu|gpu|cpu_pinned](n). Only used for imperative calls.</param>
/// <param name="dtype">DType of the output in case this can't be inferred. Defaults to float32 if not defined (dtype=None).</param>
/// <returns>returns new symbol</returns>
Draw random samples from a generalized negative binomial distribution.Samples are distributed according to a generalized negative binomial distribution parametrized by*mu* (mean) and *alpha* (dispersion).
Draw random samples from a generalized negative binomial distribution . Samples are distributed according to a generalized negative binomial distribution parametrized by * mu * ( mean ) and * alpha * ( dispersion ) .
public static NDArray RandomGeneralizedNegativeBinomial(NDArray @out,
        float mu = 1f,
        float alpha = 1f,
        Shape shape = null,
        Context ctx = null,
        DType dtype = null)
        {
            return new Operator("_random_generalized_negative_binomial")
            .SetParam("mu", mu)
            .SetParam("alpha", alpha)
            .SetParam("shape", shape)
            .SetParam("ctx", ctx)
            .SetParam("dtype", dtype)
            .Invoke(@out);
        }
public static NDArray RandomGeneralizedNegativeBinomial ( NDArray @out , float mu = 1f , float alpha = 1f , Shape shape = null , Context ctx = null , DType dtype = null ) { return new Operator ( " " ) . SetParam ( " " , mu ) . SetParam ( " " , alpha ) . SetParam ( " " , shape ) . SetParam ( " " , ctx ) . SetParam ( " " , dtype ) . Invoke ( @out ) ; }
Draw random samples from a generalized negative binomial distribution.Samples are distributed according to a generalized negative binomial distribution parametrized by*mu* (mean) and *alpha* (dispersion).
Draw random samples from a generalized negative binomial distribution . Samples are distributed according to a generalized negative binomial distribution parametrized by * mu * ( mean ) and * alpha * ( dispersion ) .
returns new symbol
returns new symbol
@out
NDArray
None
mu
float
Mean of the negative binomial distribution.
Mean of the negative binomial distribution .
alpha
float
Alpha (dispersion) parameter of the negative binomial distribution.
Alpha ( dispersion ) parameter of the negative binomial distribution .
shape
Shape
Shape of the output.
Shape of the output .
ctx
Context
Context of output, in format [cpu|gpu|cpu_pinned](n). Only used for imperative calls.
Context of output in format [ cpu|gpu|cpu_pinned ] ( n ) . Only used for imperative calls .
dtype
DType
DType of the output in case this can't be inferred. Defaults to float32 if not defined (dtype=None).
DType of the output in case this can ' t be inferred . Defaults to float32 if not defined ( dtype = None ) .