CRAN release 0.12.0

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: mirai
 Type: Package
 Title: Minimalist Async Evaluation Framework for R
-Version: 0.11.3.9005
+Version: 0.12.0
 Description: Lightweight parallel code execution and distributed computing.
     Designed for simplicity, a 'mirai' evaluates an R expression asynchronously,
     on local or network resources, resolving automatically upon completion.

NEWS.md

@@ -1,4 +1,4 @@
-# mirai 0.11.3.9005 (development)
+# mirai 0.12.0
 
 * More minimal print methods for 'mirai' and 'miraiCluster'.
 * Adds `local_url()` helper to construct a random inter-process communications URL for local daemons (thanks @noamross #90).

vignettes/promises.Rmd

@@ -18,22 +18,28 @@ Alternatively, it may be converted into a promise by `as.promise()`, which then
 The following example outputs "hello" to the console after one second when the 'mirai' resolves.
 
 ```r
+library(mirai)
 library(promises)
+
 p <- mirai({Sys.sleep(1); "hello"}) %...>% cat()
 p
 #> <Promise [pending]>
 ```
 It is possible to both access a 'mirai' value at `$data` and to use a promise for enacting a side effect (assigning the value to an environment in the example below).
 
 ```r
+library(mirai)
 library(promises)
+
 env <- new.env()
 
 m <- mirai({Sys.sleep(1); "hello"})
-p <- as.promise(m)$then(function(x) env[["response"]] <- x)
+p <- as.promise(m)$then(function(x) env$res <- x)
 
 call_mirai(m)$data
 #> [1] "hello"
-env[["response"]]
+
+# after returning to the top level prompt:
+env$res
 #> [1] "hello"
 ```

vignettes/promises.Rmd.orig

@@ -23,18 +23,24 @@ Alternatively, it may be converted into a promise by `as.promise()`, which then
 
 The following example outputs "hello" to the console after one second when the 'mirai' resolves.
 ```{r promises}
+library(mirai)
 library(promises)
+
 p <- mirai({Sys.sleep(1); "hello"}) %...>% cat()
 p
 ```
 It is possible to both access a 'mirai' value at `$data` and to use a promise for enacting a side effect (assigning the value to an environment in the example below).
 ```{r promisesalt}
+library(mirai)
 library(promises)
+
 env <- new.env()
 
 m <- mirai({Sys.sleep(1); "hello"})
-p <- as.promise(m)$then(function(x) env[["response"]] <- x)
+p <- as.promise(m)$then(function(x) env$res <- x)
 
 call_mirai(m)$data
-env[["response"]]
+
+# after returning to the top level prompt:
+env$res
 ```

vignettes/torch.Rmd

@@ -23,7 +23,9 @@ This allows tensors from the [{torch}](https://cran.r-project.org/package=torch)
 
 
 ```r
+library(mirai)
 library(torch)
+
 serialization(refhook = list(torch:::torch_serialize, torch::torch_load))
 daemons(1)
 #> [1] 1
@@ -69,35 +71,35 @@ The returned model is an object containing many tensor elements.
 m$data$parameters$conv1.weight
 #> torch_tensor
 #> (1,1,.,.) = 
-#>  -0.0679  0.1029  0.1385  0.1610 -0.0206
-#>  -0.0851 -0.0514 -0.1901  0.0832  0.1121
-#>   0.1122  0.0309 -0.1937 -0.1249  0.0343
-#>   0.1398 -0.0798  0.0933  0.0672 -0.0778
-#>  -0.0879 -0.0727 -0.1004  0.1328  0.0231
+#>   0.0383  0.1520  0.1109  0.0119 -0.1000
+#>   0.0859 -0.1157  0.0960  0.1383  0.0737
+#>   0.0155  0.1152 -0.1734  0.1927 -0.0850
+#>   0.1287  0.0048 -0.1009  0.1470  0.0258
+#>   0.1092  0.0588  0.0504 -0.0591  0.1244
 #> 
 #> (2,1,.,.) = 
-#>   0.1520 -0.0140  0.0621  0.1891 -0.0192
-#>   0.1381  0.1579  0.0415  0.1586 -0.1211
-#>  -0.0809 -0.0243 -0.1879 -0.1244 -0.1937
-#>   0.0408  0.1539 -0.0597 -0.1490  0.1888
-#>   0.1035  0.0616  0.0775  0.0979 -0.1342
+#>  -0.0541  0.0569  0.1552 -0.1217  0.0598
+#>   0.1246 -0.0290 -0.0351  0.0297  0.1209
+#>   0.0211  0.1039 -0.1791 -0.0348 -0.0183
+#>  -0.1237 -0.1135 -0.1998 -0.1210  0.1453
+#>   0.1361 -0.1181 -0.0830 -0.1544 -0.0032
 #> 
 #> (3,1,.,.) = 
-#>   0.0944 -0.1438 -0.0957 -0.1855 -0.1500
-#>  -0.1392 -0.1959 -0.0065  0.1261 -0.1844
-#>   0.1375  0.0872 -0.0247 -0.1190  0.1837
-#>   0.0579 -0.0641  0.1278 -0.1847 -0.1106
-#>  -0.0202 -0.1681  0.0986 -0.1300  0.1095
+#>  -0.1499  0.0196  0.1844 -0.0930 -0.1070
+#>   0.0126 -0.0639 -0.0543 -0.1243  0.1572
+#>  -0.1456  0.1143  0.1234  0.0045  0.0432
+#>  -0.0010  0.0277 -0.1796  0.1019 -0.1668
+#>  -0.1633 -0.0722 -0.1908 -0.0810 -0.1464
 #> 
 #> (4,1,.,.) = 
-#>   0.0105  0.0562  0.1678  0.1800  0.1642
-#>   0.1107 -0.0196 -0.0244 -0.1933 -0.1752
-#>  -0.1280  0.0362 -0.1671 -0.0661  0.1871
-#>  -0.0716  0.1232  0.0725 -0.0820  0.0994
-#>  -0.1820 -0.1687  0.1173  0.1916 -0.1074
+#>   0.0554 -0.0543  0.1105  0.1958 -0.1307
+#>   0.0055 -0.0285  0.0316 -0.0255 -0.1464
+#>  -0.1972  0.1867  0.1503 -0.0229 -0.1025
+#>   0.1923  0.1258 -0.1582  0.1873  0.1510
+#>  -0.1501  0.0139 -0.0719 -0.1983 -0.0373
 #> 
 #> (5,1,.,.) = 
-#>   0.1298  0.1826  0.1107 -0.0559  0.1817
+#>  -0.0986 -0.1050 -0.0045  0.1681 -0.1684
 #> ... [the output was truncated (use n=-1 to disable)]
 #> [ CPUFloatType{20,1,5,5} ][ requires_grad = TRUE ]
 ```

vignettes/torch.Rmd.orig

@@ -28,7 +28,9 @@ This allows tensors from the [{torch}](https://cran.r-project.org/package=torch)
 3. Use `everywhere()` to make the {torch} package available on all dameons (for convenience, optional).
 
 ```{r tensors}
+library(mirai)
 library(torch)
+
 serialization(refhook = list(torch:::torch_serialize, torch::torch_load))
 daemons(1)
 everywhere(library(torch))