84 lines
1.5 KiB
Go
84 lines
1.5 KiB
Go
package convert
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import (
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"errors"
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"io"
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"io/fs"
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"strings"
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)
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type Tensor interface {
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Name() string
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Shape() []uint64
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Kind() uint32
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SetRepacker(repacker)
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WriteTo(io.Writer) (int64, error)
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}
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type tensorBase struct {
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name string
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shape []uint64
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repacker
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}
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func (t tensorBase) Name() string {
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return t.name
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}
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func (t tensorBase) Shape() []uint64 {
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return t.shape
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}
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const (
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tensorKindF32 uint32 = iota
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tensorKindF16
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)
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func (t tensorBase) Kind() uint32 {
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if strings.HasSuffix(t.name, ".ffn_gate_inp.weight") ||
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t.name == "token_types.weight" {
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// these tensors are always F32
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return 0
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}
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switch len(t.shape) {
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case 0:
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panic("invalid tensor shape")
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case 1:
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return tensorKindF32
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default:
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return tensorKindF16
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}
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}
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func (t *tensorBase) SetRepacker(fn repacker) {
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t.repacker = fn
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}
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type repacker func(string, []float32, []uint64) ([]float32, error)
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func parseTensors(fsys fs.FS, replacer *strings.Replacer) ([]Tensor, error) {
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patterns := []struct {
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Pattern string
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Func func(fs.FS, *strings.Replacer, ...string) ([]Tensor, error)
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}{
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{"model-*-of-*.safetensors", parseSafetensors},
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{"model.safetensors", parseSafetensors},
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{"pytorch_model-*-of-*.bin", parseTorch},
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{"pytorch_model.bin", parseTorch},
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{"consolidated.*.pth", parseTorch},
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}
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for _, pattern := range patterns {
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matches, err := fs.Glob(fsys, pattern.Pattern)
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if err != nil {
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return nil, err
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}
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if len(matches) > 0 {
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return pattern.Func(fsys, replacer, matches...)
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}
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}
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return nil, errors.New("unknown tensor format")
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}
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