@spec forward(
  map(),
  keyword()
) ::
  {:ok, Tinkex.Types.ForwardBackwardOutput.t() | map()}
  | {:error, Tinkex.Error.t()}

Forward pass only (inference).

This helper awaits the future internally. Use forward_future/2 to get the raw future response.

@spec forward_backward(
  map(),
  keyword()
) ::
  {:ok, Tinkex.Types.ForwardBackwardOutput.t() | map()}
  | {:error, Tinkex.Error.t()}

Forward-backward pass for gradient computation.

This helper awaits the future internally. Use forward_backward_future/2 to get the raw future response.

Examples

Tinkex.API.Training.forward_backward(
  %{model_id: "...", inputs: [...]},
  config: config
)

@spec forward_backward_future(
  map(),
  keyword()
) :: {:ok, map()} | {:error, Tinkex.Error.t()}

Forward-backward pass that returns a server-side future reference.

@spec forward_future(
  map(),
  keyword()
) :: {:ok, map()} | {:error, Tinkex.Error.t()}

Forward pass that returns a server-side future reference.

Returns a future that can be polled for the forward pass result containing logprobs that can be converted to Nx tensors via TensorData.to_nx/1.

@spec optim_step(
  map(),
  keyword()
) ::
  {:ok, Tinkex.Types.OptimStepResponse.t() | map()} | {:error, Tinkex.Error.t()}

Optimizer step to update model parameters.

@spec optim_step_future(
  map(),
  keyword()
) :: {:ok, map()} | {:error, Tinkex.Error.t()}

Optimizer step that returns a server-side future reference.