ggml_opt_init: Initialize optimizer context

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Initialize optimizer context

Description

Creates a new optimizer context for training.

Usage

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

Arguments

sched	Backend scheduler
loss_type	Loss type (use ggml_opt_loss_type_* functions)
optimizer	Optimizer type (use ggml_opt_optimizer_type_* functions)
opt_period	Gradient accumulation steps before optimizer step
ctx_compute	Compute context for static graph mode (or NULL)
inputs	Input tensor for static graph mode (or NULL)
outputs	Output tensor for static graph mode (or NULL)

Value

External pointer to optimizer context

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_epoch(), ggml_opt_eval(), ggml_opt_fit(), ggml_opt_free(), ggml_opt_get_lr(), ggml_opt_grad_acc(), 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()

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