model.go

package gemma3

import (
	"fmt"

	"github.com/ollama/ollama/kvcache"
	"github.com/ollama/ollama/ml"
	"github.com/ollama/ollama/model"
	"github.com/ollama/ollama/model/input"
)

type Model struct {
	model.Base
	model.SentencePieceModel

	//*VisionModel `gguf:"v,vision"`
	*TextModel

	//Projector *nn.Linear `gguf:"mm.0"`

	ImageProcessor
}

func New(c ml.Config) (model.Model, error) {
	// Verify unified config
	if c.Uint("vision.block_count") == 0 {
		return nil, fmt.Errorf("non-unified vision model not supported")
	}
	m := Model{
		SentencePieceModel: model.NewSentencePieceModel(
			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
			&model.Vocabulary{
				Values: c.Strings("tokenizer.ggml.tokens"),
				Scores: c.Floats("tokenizer.ggml.scores"),
				Types:  c.Uints("tokenizer.ggml.token_type"),
				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id")),
				AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
			},
		),
		ImageProcessor: newImageProcessor(c),
		//VisionModel:    newVisionModel(c),
		TextModel: newTextModel(c),
	}

	slidingWindowLen := int32(c.Uint("text.attention.sliding_window"))
	m.Cache = kvcache.NewWrapperCache(kvcache.NewSWACache(slidingWindowLen, m.Shift), kvcache.NewCausalCache(m.Shift))

	return &m, nil
}

func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
	if err != nil {
		return nil, err
	}

	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
	if err != nil {
		return nil, err
	}

	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
	if err != nil {
		return nil, err
	}

	return m.TextModel.Forward(ctx, inputs, positions, outputs, m.Cache), nil
}

func init() {
	model.Register("gemma3", New)
}