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docs/torch/torch.special

torch.special

package torch.special

Members list

Value members

Concrete methods

def digamma[D <: RealNN](input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the logarithmic derivative of the gamma function on input.

Computes the logarithmic derivative of the gamma function on input.

Attributes

Source
package.scala
def erf[D <: RealNN](input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the error function of input.

Computes the error function of input.

Attributes

Source
package.scala
def erfc[D <: RealNN](input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the complementary error function of input.

Computes the complementary error function of input.

Attributes

Source
package.scala
def erfinv[D <: RealNN](input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the inverse error function of input. The inverse error function is defined in the range (−1,1)

Computes the inverse error function of input. The inverse error function is defined in the range (−1,1)

Attributes

Source
package.scala
def exp2[D <: DType](input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the base two exponential function of input.

Computes the base two exponential function of input.

Attributes

Source
package.scala
def expm1[D <: DType](input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the exponential of the elements minus 1 of input.

Computes the exponential of the elements minus 1 of input.

Attributes

Source
package.scala
def i0[D <: RealNN](input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the zeroth order modified Bessel function of the first kind for each element of input.

Computes the zeroth order modified Bessel function of the first kind for each element of input.

Attributes

Source
package.scala
def igamma[D <: RealNN, D2 <: FloatNN](input: Tensor[D], other: Tensor[D2])(using AtLeastOneFloat[D, D2]): Tensor[FloatPromoted[Promoted[D, D2]]]

Computes the regularized lower incomplete gamma function

Computes the regularized lower incomplete gamma function

Attributes

Source
package.scala
def igammac[D <: RealNN, D2 <: FloatNN](input: Tensor[D], other: Tensor[D2])(using AtLeastOneFloat[D, D2]): Tensor[FloatPromoted[Promoted[D, D2]]]

Computes the regularized upper incomplete gamma function

Computes the regularized upper incomplete gamma function

Attributes

Source
package.scala
def logit[D <: RealNN](input: Tensor[D], eps: Option[Double]): Tensor[FloatPromoted[D]]

Returns a new tensor with the logit of the elements of input. input is clamped to [eps, 1 - eps] when eps is not None. When eps is None and input < 0 or input > 1, the function will yields NaN.

Returns a new tensor with the logit of the elements of input. input is clamped to [eps, 1 - eps] when eps is not None. When eps is None and input < 0 or input > 1, the function will yields NaN.

Attributes

Source
package.scala
def mvlgamma[D <: NumericRealNN](input: Tensor[D], p: Int): Tensor[FloatPromoted[D]]

Computes the multivariate log-gamma function with dimension p element-wise

Computes the multivariate log-gamma function with dimension p element-wise

Attributes

Source
package.scala
def polygamma[D <: RealNN](n: Int, input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the nth derivative of the digamma function on input. n≥0 is called the order of the polygamma function.

Computes the nth derivative of the digamma function on input. n≥0 is called the order of the polygamma function.

Attributes

Source
package.scala
def sigmoid[D <: DType](input: Tensor[D]): Tensor[FloatPromoted[D]]

Computes the expit (also known as the logistic sigmoid function) of the elements of input.

Computes the expit (also known as the logistic sigmoid function) of the elements of input.

Attributes

Source
package.scala
def sinc[D <: DType](input: Tensor[D]): Tensor[FloatPromoted[D]]

Returns a new tensor with the normalized sinc of the elements of input.

Returns a new tensor with the normalized sinc of the elements of input.

Attributes

Source
package.scala
def xlogy[D <: RealNN, D2 <: RealNN](input: Tensor[D], other: TensorOrReal[D2]): Tensor[FloatPromoted[D]]

Computes input * log(other) with the following cases.

Computes input * log(other) with the following cases.

Attributes

Source
package.scala
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