## mean

Mean of a `Variable`, alongside the specified axis. - `axis` axis to compute the mean. 0-based indexed. - `keepDims` A boolean, whether to keep the dimensions or not. If `keepDims` is `False`, the rank of the `Variable` is reduced by 1. If `keepDims` is `True`, the reduced dimensions are retained with length 1.

Scala example

``````mean(x: Variable[T], axis: Int = 0, keepDims: Boolean = false)
``````

Python example

``````mean(x, axis=0, keepDims=False):
``````

## abs

Element-wise absolute value. - `x` A `Variable`.

Scala example

``````abs(x: Variable[T])
``````

Python example

``````abs(x):
``````

## sum

Sum of the values in a `Variable`, alongside the specified axis. - `axis` axis to compute the mean. 0-based indexed. - `keepDims` A boolean, whether to keep the dimensions or not. If `keepDims` is `False`, the rank of the `Variable` is reduced by 1. If `keepDims` is `True`, the reduced dimensions are retained with length 1.

Scala example

``````sum(x: Variable[T], axis: Int = 0, keepDims: Boolean = false)
``````

Python example

``````sum(x, axis=0, keepDims=False):
``````

## clip

Element-wise value clipping. - `x` A `Variable`. - `min` Double - `max` Double

Scala example

``````clip(x: Variable[T], min: Double, max: Double)
``````

Python example

``````clip(x, min, max)
``````

## square

Element-wise square. - `x` A `Variable`.

Scala example

``````square(x: Variable[T])
``````

Python example

``````square(x):
``````

## sqrt

Element-wise square root. - `x` A `Variable`.

Scala example

``````sqrt(x: Variable[T])
``````

Python example

``````sqrt(x):
``````

## maximum

Element-wise maximum of two `Variables`. - `x` A `Variable`. - `y` A `Variable` or Double.

Scala example

``````maximum(x: Variable[T], y: Variable[T])
``````

Python example

``````maximum(x, y):
``````

## log

Element-wise log. - `x` A `Variable`.

Scala example

``````log(x: Variable[T])
``````

Python example

``````log(x):
``````

## exp

Element-wise exponential. - `x` A `Variable`.

Scala example

``````exp(x: Variable[T])
``````

Python example

``````exp(x):
``````

## pow

Element-wise exponentiation. - `x` A `Variable`. - `a` Double.

Scala example

``````pow(x: Variable[T])
``````

Python example

``````pow(x):
``````

## softsign

Softsign of a `Variable`.

Scala example

``````softsign(x: Variable[T])
``````

Python example

``````softsign(x):
``````

## softplus

Softplus of a `Variable`.

Scala example

``````softplus(x: Variable[T])
``````

Python example

``````softplus(x):
``````

## stack

Stacks a list of rank `R` tensors into a rank `R+1` tensor. You should start from 1 as dim 0 is for batch. - inputs: List of variables (tensors) - axis: xis along which to perform stacking.

Scala example

``````def stack[T: ClassTag](inputs: List[Variable[T]], axis: Int = 1)
``````

Python example

``````def stack(inputs, axis=1)
``````

## expand_dims

Adds a 1-sized dimension at index "axis".

Scala example

``````def expandDims[T: ClassTag](x: Variable[T], axis: Int)
``````

Python example

``````expand_dims(x, axis)
``````

## contiguous

Turn the output and grad to be contiguous for the input Variable

Scala example

``````def contiguous[T: ClassTag](input: Variable[T])
``````

Python example

``````def contiguous(x)
``````

## mm

Module to perform matrix multiplication on two mini-batch inputs, producing a mini-batch. - `x` A variable. - `y` A variable. - `axes` Axes along which to perform multiplication.

Scala example

``````def mm[T: ClassTag](x: Variable[T], y: Variable[T], axes: List[Int])
``````

Python example

``````def mm(x, y, axes)
``````

## batch_dot

Operator that computes a dot product between samples in two tensors. - `x` Shape should only be [batch, xx] - `y` Shape should only be [batch, xx] - `axes` Integer or tuple of integers, axis or axes along which to take the dot product. - `normalize` Whether to L2-normalize samples along the dot product axis before taking the dot product. If set to True, then the output of the dot product is the cosine proximity between the two samples.

Scala example

``````def batchDot[T: ClassTag](x: Variable[T], y: Variable[T], axes: List[Int], normalize: Boolean = false)
``````

Python example

``````def batch_dot(x, y, axes=1, normalize=False)
``````

## l2_normalize

Normalizes a tensor wrt the L2 norm alongside the specified axis. - `x` A variable. - `axis` Axis along which to perform normalization.

Scala example

``````def l2Normalize[T: ClassTag](x: Variable[T], axis: Int)
``````

Python example

``````def l2_normalize(x, axis)
``````