ggmlR (version 0.6.1)

ggml_opt_init_for_fit: Initialize optimizer context for R-side epoch loop

Description

Returns a list with `opt_ctx` and `lr_ud` (learning rate userdata pointer). Use `ggml_opt_set_lr()` to update LR between epochs. The optimizer state (momentum) is preserved across epochs.

Usage

ggml_opt_init_for_fit(
  sched,
  loss_type,
  optimizer = ggml_opt_optimizer_type_adamw(),
  opt_period = 1L,
  ctx_compute = NULL,
  inputs = NULL,
  outputs = NULL
)

Value

List with elements `opt_ctx` and `lr_ud`

Arguments

sched

Backend scheduler

loss_type

Loss type constant

optimizer

Optimizer type constant

opt_period

Gradient accumulation period

ctx_compute

Compute context (for static graphs)

inputs

Input tensor (for static graphs)

outputs

Output tensor (for static graphs)

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_default_params(), ggml_opt_epoch(), ggml_opt_eval(), ggml_opt_fit(), ggml_opt_free(), ggml_opt_get_lr(), ggml_opt_grad_acc(), ggml_opt_init(), 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_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()