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ee141cc821
In cases where we allocate a tensor and then fully overwrite it with copied data, it is wasteful to first zero out the memory.
129 lines
3.0 KiB
Go
129 lines
3.0 KiB
Go
package kvcache
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import (
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"fmt"
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"github.com/ollama/ollama/ml"
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)
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// Encoder cache stores K and V tensors that are position independent
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//
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// The tensors can be of any shape and will be returned as they were stored
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// The mask is currently always nil
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//
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// Not currently safe for multiple sequences
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type EncoderCache struct {
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// config controls mostly backend-specific optimizations
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config *ml.CacheConfig
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// ** current forward pass **
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// the active layer for Get and Put
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curLayer int
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// if something is stored during this pass, this
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// will be the position (but there is no guarantee
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// anything will be stored)
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curPos int32
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// ** cache metadata **
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// was something stored in the cache?
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encoderCached bool
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// position of the cached data
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encoderPos int32
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// ** cache data storage **
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cacheCtx ml.Context
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keys, values []ml.Tensor
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}
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func NewEncoderCache() *EncoderCache {
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return &EncoderCache{}
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}
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func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
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if c.config == nil {
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var config ml.CacheConfig
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if cc, ok := backend.(ml.BackendCacheConfig); ok {
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config = cc.CacheConfig()
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}
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c.config = &config
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}
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if c.config.CachePadding != 0 && c.config.CachePadding != 1 {
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panic(fmt.Errorf("encoder cache is unable to enforce requested CachePadding (%v)", c.config.CachePadding))
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}
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c.cacheCtx = backend.NewContext()
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}
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func (c *EncoderCache) SetConfig(config ml.CacheConfig) {
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if c.config != nil {
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panic("config cannot be changed after being previously set, either by the model or backend")
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}
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c.config = &config
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}
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func (c *EncoderCache) Close() {
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c.cacheCtx.Close()
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}
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func (c *EncoderCache) StartForward(ctx ml.Context, positions []int32, seqs []int) error {
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// The image is always in the first position
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c.curPos = positions[0]
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return nil
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}
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func (c *EncoderCache) SetLayer(layer int) {
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if layer >= len(c.keys) {
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c.keys = append(c.keys, make([]ml.Tensor, layer-len(c.keys)+1)...)
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c.values = append(c.values, make([]ml.Tensor, layer-len(c.values)+1)...)
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}
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c.curLayer = layer
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}
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func (c *EncoderCache) EncoderCached() bool {
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return c.encoderCached
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}
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func (c *EncoderCache) Get(ctx ml.Context) (ml.Tensor, ml.Tensor, ml.Tensor) {
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return c.keys[c.curLayer], c.values[c.curLayer], nil
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}
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func (c *EncoderCache) Put(ctx ml.Context, key, value ml.Tensor) {
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c.encoderPos = c.curPos
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c.encoderCached = true
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if c.config.PermutedV {
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value = value.Permute(ctx, 1, 2, 0, 3)
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}
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if c.keys[c.curLayer] == nil || c.values[c.curLayer] == nil {
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c.keys[c.curLayer] = c.cacheCtx.Empty(key.DType(), key.Shape()...)
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c.values[c.curLayer] = c.cacheCtx.Empty(value.DType(), value.Shape()...)
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}
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ctx.Forward(
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key.Copy(ctx, c.keys[c.curLayer]),
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value.Copy(ctx, c.values[c.curLayer]),
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)
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}
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func (c *EncoderCache) CopyPrefix(srcSeq, dstSeq int, len int32) {
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panic("encoder cache does not support multiple sequences")
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}
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func (c *EncoderCache) Remove(seq int, beginIndex, endIndex int32) error {
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if c.encoderPos >= beginIndex && c.encoderPos < endIndex {
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c.encoderCached = false
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}
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return nil
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}
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