ggml_opt_epoch: Run one training epoch

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Run one training epoch

Description

Performs training on the front portion of the dataset and evaluation on the back portion. This gives more control than ggml_opt_fit.

Usage

ggml_opt_epoch(
  opt_ctx,
  dataset,
  result_train = NULL,
  result_eval = NULL,
  idata_split,
  callback_train = TRUE,
  callback_eval = TRUE
)

Arguments

opt_ctx	External pointer to optimizer context
dataset	External pointer to dataset
result_train	Result object to accumulate training stats (or NULL)
result_eval	Result object to accumulate evaluation stats (or NULL)
idata_split	Data index at which to split training and evaluation
callback_train	Callback for training: TRUE for progress bar, FALSE for none, or a function(train, ibatch, ibatch_max, t_start_us, result)
callback_eval	Callback for evaluation: TRUE for progress bar, FALSE for none, or a function(train, ibatch, ibatch_max, t_start_us, result)

Value

NULL invisibly

See Also

Other optimization: ggml_fit_opt(), ggml_opt_alloc(), ggml_opt_context_optimizer_type(), ggml_opt_dataset_data(), ggml_opt_dataset_free(), ggml_opt_dataset_get_batch(), ggml_opt_dataset_init(), ggml_opt_dataset_labels(), ggml_opt_dataset_ndata(), ggml_opt_dataset_shuffle(), ggml_opt_dataset_weights(), ggml_opt_default_params(), ggml_opt_eval(), ggml_opt_fit(), ggml_opt_free(), ggml_opt_get_lr(), ggml_opt_grad_acc(), ggml_opt_init(), ggml_opt_init_for_fit(), ggml_opt_inputs(), ggml_opt_labels(), ggml_opt_loss(), ggml_opt_loss_type_cross_entropy(), ggml_opt_loss_type_mean(), ggml_opt_loss_type_mse(), ggml_opt_loss_type_sum(), ggml_opt_loss_type_weighted_mse(), ggml_opt_ncorrect(), ggml_opt_optimizer_name(), ggml_opt_optimizer_type_adamw(), ggml_opt_optimizer_type_sgd(), ggml_opt_outputs(), ggml_opt_pred(), ggml_opt_prepare_alloc(), ggml_opt_reset(), ggml_opt_result_accuracy(), ggml_opt_result_free(), ggml_opt_result_init(), ggml_opt_result_loss(), ggml_opt_result_ndata(), ggml_opt_result_pred(), ggml_opt_result_reset(), ggml_opt_set_lr(), ggml_opt_static_graphs()

Examples

# Requires full optimizer setup - see ggml_opt_fit() for simpler API
if (FALSE) {
result_train <- ggml_opt_result_init()
result_eval <- ggml_opt_result_init()
ggml_opt_epoch(opt_ctx, dataset, result_train, result_eval,
               idata_split = 900, callback_train = TRUE)
ggml_opt_result_free(result_train)
ggml_opt_result_free(result_eval)
}

ggmlR documentation built on July 14, 2026, 1:08 a.m.