Backends/SiaNet.Backend.MxNet/NDArrayOps.cs
/// <summary>
/// Returns the hyperbolic tangent of the input array, computed element-wise... math::   tanh(x) = sinh(x) / cosh(x)The storage type of ``tanh`` output depends upon the input storage type:   - tanh(default) = default   - tanh(row_sparse) = row_sparseDefined in G:\deeplearn\mxnet\src\operator\tensor\elemwise_unary_op.cc:L823
/// </summary>
/// <param name="@out">output NDArray</param>
/// <param name="data">The input array.</param>
/// <returns>returns new symbol</returns>
Returns the hyperbolic tangent of the input array, computed element-wise...
Returns the hyperbolic tangent of the input array computed element - wise ...
public static NDArray Tanh(NDArray @out,
        NDArray data)
        {
            return new Operator("tanh")
            .SetInput("data", data)
            .Invoke(@out);
        }
public static NDArray Tanh ( NDArray @out , NDArray data ) { return new Operator ( " " ) . SetInput ( " " , data ) . Invoke ( @out ) ; }
Returns the hyperbolic tangent of the input array, computed element-wise... math::   tanh(x) = sinh(x) / cosh(x)The storage type of ``tanh`` output depends upon the input storage type:   - tanh(default) = default   - tanh(row_sparse) = row_sparseDefined in G:\deeplearn\mxnet\src\operator\tensor\elemwise_unary_op.cc:L823
Returns the hyperbolic tangent of the input array computed element - wise ... math :: tanh ( x ) = sinh ( x ) / cosh ( x ) The storage type of ` ` tanh ` ` output depends upon the input storage type : - tanh ( default ) = default - tanh ( row_sparse ) = row_sparseDefined in G : \ deeplearn \ mxnet \ src \ operator \ tensor \ elemwise_unary_op . cc : L823
returns new symbol
returns new symbol
@out
NDArray
None
data
NDArray
The input array.
The input array .