fix documentation of sits_train and torch models

Author: gilbertocamara

R/sits_lighttae.R

@@ -278,7 +278,7 @@ sits_lighttae <- function(samples = NULL,
                 # by .ml_normalize.torch_model function
             }
         )
-        # torch 12.0 with luz not working with Apple MPS
+        # verify if GPU is available
         cpu_train <- .torch_cpu_train()
         # Train the model using luz
         torch_model <-
@@ -331,7 +331,6 @@ sits_lighttae <- function(samples = NULL,
             # Verifies if torch package is installed
             .check_require_packages("torch")
             # Set torch threads to 1
-            # Note: function does not work on MacOS
             suppressWarnings(torch::torch_set_num_threads(1L))
             # Unserialize model
             torch_model[["model"]] <- .torch_unserialize_model(serialized_model)

R/sits_lstm_fcn.R

@@ -310,7 +310,6 @@ sits_lstm_fcn <- function(samples = NULL,
             # Verifies if torch package is installed
             .check_require_packages("torch")
             # Set torch threads to 1
-            # Note: function does not work on MacOS
             suppressWarnings(torch::torch_set_num_threads(1L))
             # Unserialize model
             torch_model[["model"]] <- .torch_unserialize_model(serialized_model)

R/sits_mlp.R

@@ -262,7 +262,6 @@ sits_mlp <- function(samples = NULL,
             # Verifies if torch package is installed
             .check_require_packages("torch")
             # Set torch threads to 1
-            # Note: function does not work on MacOS
             suppressWarnings(torch::torch_set_num_threads(1L))
             # Unserialize model
             torch_model[["model"]] <- .torch_unserialize_model(serialized_model)

R/sits_resnet.R

@@ -338,7 +338,6 @@ sits_resnet <- function(samples = NULL,
             # Verifies if torch package is installed
             .check_require_packages("torch")
             # Set torch threads to 1
-            # Note: function does not work on MacOS
             suppressWarnings(torch::torch_set_num_threads(1L))
             # Unserialize model
             torch_model[["model"]] <- .torch_unserialize_model(serialized_model)

R/sits_tae.R

@@ -240,7 +240,7 @@ sits_tae <- function(samples = NULL,
                 # softmax is done after classification - removed from here
             }
         )
-        # torch 12.0 not working with Apple MPS
+        # train with CPU or GPU?
         cpu_train <- .torch_cpu_train()
         # train the model using luz
         torch_model <-
@@ -287,7 +287,6 @@ sits_tae <- function(samples = NULL,
             # Verifies if torch package is installed
             .check_require_packages("torch")
             # Set torch threads to 1
-            # Note: function does not work on MacOS
             suppressWarnings(torch::torch_set_num_threads(1L))
             # Unserialize model
             torch_model[["model"]] <- .torch_unserialize_model(serialized_model)

R/sits_tempcnn.R

@@ -325,7 +325,6 @@ sits_tempcnn <- function(samples = NULL,
             # Verifies if torch package is installed
             .check_require_packages("torch")
             # Set torch threads to 1
-            # Note: function does not work on MacOS
             suppressWarnings(torch::torch_set_num_threads(1L))
             # Unserialize model
             torch_model[["model"]] <- .torch_unserialize_model(serialized_model)

R/sits_train.R

@@ -5,7 +5,7 @@
 #' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
 #' @author Alexandre Ywata de Carvalho, \email{alexandre.ywata@@ipea.gov.br}
 #'
-#' @description Given a tibble with a set of distance measures,
+#' @description Given a tibble with a set of time series,
 #'    returns trained models. Currently, sits supports the following models:
 #' \itemize{
 #'      \item{support vector machines:  \code{\link[sits]{sits_svm}};}