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use 2d pooling

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This commit is contained in:
Michael Yang
2025-03-11 09:00:10 -07:00
parent ab39e08eb9
commit 63a394068c
4 changed files with 36 additions and 25 deletions
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6
ml/backend/ggml/ggml.go
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@@ -247,7 +247,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
createTensor(tensor{source: t}, output.bts)
case strings.HasPrefix(t.Name, "v.") || strings.HasPrefix(t.Name, "mm."):
// TODO: assign vision tensors to the gpu if possible
createTensor(tensor{source: t}, input.bts)
createTensor(tensor{source: t}, output.bts)
case contains(t.Name, "rope_freqs", "rope_factors_long", "rope_factors_short"):
// these tensors should be repeated per layer
for i, layer := range layers {
@@ -952,10 +952,10 @@ func (t *Tensor) Conv2D(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int
}
}
func (t *Tensor) AvgPool1D(ctx ml.Context, k, s, p int) ml.Tensor {
func (t *Tensor) AvgPool2D(ctx ml.Context, k, s int, p float32) ml.Tensor {
return &Tensor{
b: t.b,
t: C.ggml_pool_1d(ctx.(*Context).ctx, t.t, C.GGML_OP_POOL_AVG, C.int(k), C.int(s), C.int(p)),
t: C.ggml_pool_2d(ctx.(*Context).ctx, t.t, C.GGML_OP_POOL_AVG, C.int(k), C.int(k), C.int(s), C.int(s), C.float(p), C.float(p)),
}
}