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s/From*Slice/From*s/ (#12255)

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This commit is contained in:
Michael Yang
2025-10-28 12:08:49 -07:00
committed by GitHub
parent 15c7d30d9a
commit 1188f408dd
24 changed files with 95 additions and 76 deletions
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70
ml/backend/ggml/ggml.go
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@@ -12,6 +12,7 @@ import "C"
import (
"context"
"encoding/binary"
"errors"
"fmt"
"io"
@@ -871,7 +872,7 @@ func pad(length, pad C.size_t) C.size_t {
return ((length + pad - 1) / pad) * pad
}
func (c *Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
func (c *Context) newTensor(dtype ml.DType, shape []int) *Tensor {
if c.buft == nil {
panic("set Input or Layer before creating tensors")
}
@@ -915,7 +916,7 @@ func (c *Context) Empty(dtype ml.DType, shape ...int) ml.Tensor {
func (c *Context) Zeros(dtype ml.DType, shape ...int) ml.Tensor {
t := c.newTensor(dtype, shape)
if c.b.allocMemory {
C.ggml_set_zero(t.(*Tensor).t)
C.ggml_set_zero(t.t)
}
return t
}
@@ -936,25 +937,34 @@ func checkShape[S ~[]E, E any](s S, shape ...int) {
}
}
func (c *Context) FromFloatSlice(s []float32, shape ...int) ml.Tensor {
checkShape(s, shape...)
t := c.newTensor(ml.DTypeF32, shape)
if c.b.allocMemory && len(s) > 0 {
C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
func (c Context) FromBytes(dtype ml.DType, s []uint8, shape ...int) ml.Tensor {
// Unchecked to handle quantized types
t := c.newTensor(dtype, shape)
if c.b.allocMemory {
t.FromBytes(s)
}
return t
}
func (c *Context) FromIntSlice(s []int32, shape ...int) ml.Tensor {
func (c *Context) FromFloats(s []float32, shape ...int) ml.Tensor {
checkShape(s, shape...)
t := c.newTensor(ml.DTypeF32, shape)
if c.b.allocMemory {
t.FromFloats(s)
}
return t
}
func (c *Context) FromInts(s []int32, shape ...int) ml.Tensor {
checkShape(s, shape...)
t := c.newTensor(ml.DTypeI32, shape)
if c.b.allocMemory && len(s) > 0 {
C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
if c.b.allocMemory {
t.FromInts(s)
}
return t
@@ -975,7 +985,7 @@ func (c Context) Arange(start, stop, step float32, dtype ml.DType) ml.Tensor {
arange = append(arange, int32(i))
}
return c.Input().FromIntSlice(arange, len(arange))
return c.Input().FromInts(arange, len(arange))
default:
panic("unsupported dtype for arange")
}
@@ -1045,10 +1055,26 @@ func (t *Tensor) Floats() (data []float32) {
return
}
func (t *Tensor) SetValueFromIntSlice(s []int32) {
if len(s) > 0 {
C.ggml_backend_tensor_set(t.t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.t))
func tensorSet[S ~[]E, E byte | float32 | int32](t *Tensor, s S) {
if len(s) == 0 {
return
}
if int(C.ggml_nbytes(t.t)) != len(s)*binary.Size(s[0]) {
panic("data size does not match tensor size")
}
C.ggml_backend_tensor_set(t.t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.t))
}
func (t *Tensor) FromBytes(s []byte) {
tensorSet(t, s)
}
func (t *Tensor) FromFloats(s []float32) {
tensorSet(t, s)
}
func (t *Tensor) FromInts(s []int32) {
tensorSet(t, s)
}
func (t *Tensor) DType() ml.DType {
@@ -1622,13 +1648,3 @@ func (t *Tensor) Clamp(ctx ml.Context, min, max float32) ml.Tensor {
t: C.ggml_clamp(ctx.(*Context).ctx, t.t, C.float(min), C.float(max)),
}
}
func (c Context) FromBytes(dtype ml.DType, s []uint8, shape ...int) ml.Tensor {
// Unchecked to handle quantized types
t := c.newTensor(dtype, shape)
if c.b.allocMemory && len(s) > 0 {
C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
}
return t
}