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11 changes: 11 additions & 0 deletions R/LearnerTorch.R
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Expand Up @@ -44,6 +44,17 @@
#' * multi-class classification: The `factor` target variable of a [`TaskClassif`][mlr3::TaskClassif] is a label-encoded
#' [`torch_long`][torch::torch_long] with shape `(batch_size)` where the label-encoding goes from `1` to `n_classes`.
#'
#' @section Important Runtime Considerations:
#' There are a few hyperparameters settings that can have a considerable impact on the runtime of the learner.
#' These include:
#'
#' * `device`: Use a GPU if possible.
#' * `num_threads`: Set this to the number of CPU cores available if training on CPU.
#' * `tensor_dataset`: Set this to `TRUE` (or `"device"` if on a GPU) if the dataset fits into memory.
#' * `batch_size`: Especially for very small models, choose a larger batch size.
#'
#' Also, see the *Early Stopping and Internal Tuning* section for how to terminate training early.
#'
#' @template param_id
#' @template param_task_type
#' @template param_param_vals
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1 change: 0 additions & 1 deletion man-roxygen/paramset_torchlearner.R
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Expand Up @@ -62,7 +62,6 @@
#' **Dataloader**:
#' * `batch_size` :: `integer(1)`\cr
#' The batch size (required).
#' When working with small models or datasets, choosing a larger batch size can considerably speed up training.
#' * `shuffle` :: `logical(1)`\cr
#' Whether to shuffle the instances in the dataset. This is initialized to `TRUE`,
#' which differs from the default (`FALSE`).
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15 changes: 14 additions & 1 deletion man/mlr_learners_torch.Rd

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1 change: 0 additions & 1 deletion man/mlr_pipeops_torch_model.Rd

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