Convert to AnvlArray

Use this to canonicalize inputs at the start of a function so it works both with eager executing and in combination with jit(). Use as_anvl_array() for a single input and as_anvl_arrays() for multiple inputs. The latter will also ensure all arrays are from the same backend and live on the same device. Both take a .promote rule saying which data type the input is brought to.

Usage

as_anvl_array(x, device = NULL, .promote = NULL)

as_anvl_arrays(..., .promote = NULL)

Arguments

x

(arrayish)
Input to canonicalize.

device

(NULL | device)
Target device. If x is an AnvlArray on a different device, an error is raised.

.promote

(NULL | function)
Which data type every input is brought to. See promotion_rule for more information. A rule materializes an R value at its answer rather than converting it afterwards, so it keeps every digit.

...

(arrayish)
Inputs to align. Name them to be able to point .promote at one of them.

Value

(One or more arrayish values).

See also

peek_dtype(), nv_promote_to_common()

Examples

as_anvl_array(1L)
#> AnvlArray
#>  1
#> [ CPUi32{} ] 
# a rule builds the R value at the data type it names
as_anvl_array(1, .promote = promotion_dtype("f64"))
#> AnvlArray
#>  1
#> [ CPUf64{} ] 
as_anvl_arrays(nv_array(1:3), 1L)
#> [[1]]
#> AnvlArray
#>  1
#>  2
#>  3
#> [ CPUi32{3} ] 
#> 
#> [[2]]
#> AnvlArray
#>  1
#> [ CPUi32{} ] 
#> 
as_anvl_arrays(nv_array(1L), nv_array(1.5), .promote = promotion_common())
#> [[1]]
#> AnvlArray
#>  1
#> [ CPUf32{1} ] 
#> 
#> [[2]]
#> AnvlArray
#>  1.5000
#> [ CPUf32{1} ] 
#>