# mlr_pipeops_nop

##### PipeOpNOP

Simply pushes the input forward.
Can be useful during `Graph`

construction using the `%>>%`

-operator to specify which `PipeOp`

gets connected to which.

##### Format

##### Construction

PipeOpNOP$new(id = "nop", param_vals = list())

`id`

::`character(1)`

Identifier of resulting object, default`"nop"`

.`param_vals`

:: named`list`

List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction. Default`list()`

.

##### Input and Output Channels

`PipeOpNOP`

has one input channel named `"input"`

, taking any input (`"*"`

) both during training and prediction.

`PipeOpNOP`

has one output channel named `"output"`

, producing the object given as input (`"*"`

) without changes.

##### State

The `$state`

is left empty (`list()`

).

##### Parameters

`PipeOpNOP`

has no parameters.

##### Internals

`PipeOpNOP`

is a useful "default" stand-in for a `PipeOp`

/`Graph`

that does nothing.

##### Fields

Only fields inherited from `PipeOp`

.

##### Methods

Only methods inherited from `PipeOp`

.

##### See Also

Other PipeOps:
`PipeOpEnsemble`

,
`PipeOpImpute`

,
`PipeOpTaskPreproc`

,
`PipeOp`

,
`mlr_pipeops_boxcox`

,
`mlr_pipeops_branch`

,
`mlr_pipeops_chunk`

,
`mlr_pipeops_classbalancing`

,
`mlr_pipeops_classifavg`

,
`mlr_pipeops_classweights`

,
`mlr_pipeops_colapply`

,
`mlr_pipeops_collapsefactors`

,
`mlr_pipeops_copy`

,
`mlr_pipeops_encodeimpact`

,
`mlr_pipeops_encodelmer`

,
`mlr_pipeops_encode`

,
`mlr_pipeops_featureunion`

,
`mlr_pipeops_filter`

,
`mlr_pipeops_fixfactors`

,
`mlr_pipeops_histbin`

,
`mlr_pipeops_ica`

,
`mlr_pipeops_imputehist`

,
`mlr_pipeops_imputemean`

,
`mlr_pipeops_imputemedian`

,
`mlr_pipeops_imputenewlvl`

,
`mlr_pipeops_imputesample`

,
`mlr_pipeops_kernelpca`

,
`mlr_pipeops_learner`

,
`mlr_pipeops_missind`

,
`mlr_pipeops_modelmatrix`

,
`mlr_pipeops_mutate`

,
`mlr_pipeops_pca`

,
`mlr_pipeops_quantilebin`

,
`mlr_pipeops_regravg`

,
`mlr_pipeops_removeconstants`

,
`mlr_pipeops_scalemaxabs`

,
`mlr_pipeops_scalerange`

,
`mlr_pipeops_scale`

,
`mlr_pipeops_select`

,
`mlr_pipeops_smote`

,
`mlr_pipeops_spatialsign`

,
`mlr_pipeops_subsample`

,
`mlr_pipeops_unbranch`

,
`mlr_pipeops_yeojohnson`

,
`mlr_pipeops`

Other Placeholder Pipeops:
`mlr_pipeops_copy`

##### Examples

```
# NOT RUN {
library("mlr3")
nop = po("nop")
nop$train(list(1))
# use `gunion` and `%>>%` to create a "bypass"
# next to "pca"
gr = gunion(list(
po("pca"),
nop
)) %>>% po("featureunion")
gr$train(tsk("iris"))[[1]]$data()
# }
```

*Documentation reproduced from package mlr3pipelines, version 0.1.2, License: LGPL-3*