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a1cda80bcb
The encoder cache needs to know the position of images in the input stream so that it knows when to delete them. Previously images didn't have a position, so we implied one by breaking batches before an image and then assuming the image was in the first position. However, multimodal objects are now given explicit positions in the input stream, so we can use that instead. Breaking batches was also a way to simulate a cross attention mask for mllama. However, given that it only supports a single sequence and a single image, this mask doesn't serve any real purpose. Removing the batch break does not appear to affect the quality of the output. Most of this is simply moving the input data structures to a new package to avoid import cycles.
101 lines
2.2 KiB
Go
101 lines
2.2 KiB
Go
package kvcache
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import (
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"math"
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"github.com/ollama/ollama/ml"
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"github.com/ollama/ollama/model/input"
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)
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// Wrapper cache is a container for multiple types of caches,
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// such as for the encoding and decoding portions of a model.
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type WrapperCache struct {
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// caches we are wrapping
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caches []Cache
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// cache to be used for this layer
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curType int
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}
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func NewWrapperCache(caches ...Cache) *WrapperCache {
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return &WrapperCache{
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caches: caches,
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}
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}
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func (c *WrapperCache) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
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for _, cache := range c.caches {
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cache.Init(backend, dtype, capacity)
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}
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}
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func (c *WrapperCache) SetConfig(config ml.CacheConfig) {
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for _, cache := range c.caches {
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cache.SetConfig(config)
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}
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}
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func (c *WrapperCache) Close() {
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for _, cache := range c.caches {
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cache.Close()
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}
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}
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func (c *WrapperCache) StartForward(ctx ml.Context, opts input.Options) error {
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for i, cache := range c.caches {
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err := cache.StartForward(ctx, opts)
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if err != nil {
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// unwind on error - Remove with endIndex set to math.MaxInt32 does not fail
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for j := i - 1; j >= 0; j-- {
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for k := range opts.Positions {
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_ = c.caches[j].Remove(opts.Sequences[k], opts.Positions[k], math.MaxInt32)
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}
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}
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return err
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}
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}
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c.curType = 0
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return nil
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}
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func (c *WrapperCache) SetLayer(layer int) {
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for _, cache := range c.caches {
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cache.SetLayer(layer)
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}
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}
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func (c *WrapperCache) SetLayerType(layerType int) {
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c.curType = layerType
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}
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func (c *WrapperCache) UnderlyingCache() Cache {
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return c.caches[c.curType]
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}
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func (c *WrapperCache) Get(ctx ml.Context) (ml.Tensor, ml.Tensor, ml.Tensor) {
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return c.caches[c.curType].Get(ctx)
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}
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func (c *WrapperCache) Put(ctx ml.Context, key, value ml.Tensor) {
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c.caches[c.curType].Put(ctx, key, value)
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}
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func (c *WrapperCache) CopyPrefix(srcSeq, dstSeq int, len int32) {
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for _, cache := range c.caches {
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cache.CopyPrefix(srcSeq, dstSeq, len)
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}
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}
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func (c *WrapperCache) Remove(seq int, beginIndex, endIndex int32) error {
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// If the one of these fails, the caller is supposed to retry with endIndex set to math.MaxInt32, which should not fail
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for _, cache := range c.caches {
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err := cache.Remove(seq, beginIndex, endIndex)
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if err != nil {
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return err
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}
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}
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return nil
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}
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