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ml: Panic rather than return error on tensor allocation failure

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FromFloatSlice and FromIntSlice return an error if the shape doesn't
match the passed data or if memory can't be allocated. Since these
are inputs, the memory being allocated is system memory rather than VRAM.

In many cases, the caller can't really handle the error and panics.

Empty and Zeros directly panic if they can't allocate memory.

This makes things consistent by panicing for the first two cases,
removing a fair amount of error handling code. This is also consistent
with how Go typically handles these situations.
This commit is contained in:
Jesse Gross
2025-05-19 10:43:56 -07:00
committed by Jesse Gross
parent 73d6a82cce
commit 1f371ea92f
20 changed files with 68 additions and 209 deletions
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18
kvcache/causal_test.go
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@@ -344,7 +344,7 @@ func testCache(t *testing.T, backend ml.Backend, cache Cache, tests []testCase)
}
cache.SetLayer(0)
tensor, _ := context.FromFloatSlice(test.in, test.inShape...)
tensor := context.FromFloatSlice(test.in, test.inShape...)
cache.Put(context, tensor, tensor)
out, _, mask := cache.Get(context)
@@ -386,7 +386,7 @@ func TestCanResume(t *testing.T) {
}
cache.SetLayer(0)
tensor, _ := context.FromFloatSlice([]float32{1, 2, 3, 4}, 1, 1, 4)
tensor := context.FromFloatSlice([]float32{1, 2, 3, 4}, 1, 1, 4)
cache.Put(context, tensor, tensor)
// with window size 4, nothing has slid out of the window yet
@@ -413,7 +413,7 @@ func TestCanResume(t *testing.T) {
}
cache.SetLayer(0)
tensor, _ = context.FromFloatSlice([]float32{5, 6}, 1, 1, 2)
tensor = context.FromFloatSlice([]float32{5, 6}, 1, 1, 2)
cache.Put(context, tensor, tensor)
// only the latest position has overlapping windows
@@ -470,24 +470,24 @@ func (c *testContext) Zeros(dtype ml.DType, shape ...int) ml.Tensor {
return c.Empty(dtype, shape...)
}
func (c *testContext) FromFloatSlice(s []float32, shape ...int) (ml.Tensor, error) {
func (c *testContext) FromFloatSlice(s []float32, shape ...int) ml.Tensor {
t := c.Empty(ml.DTypeF32, shape...).(*testTensor)
copy(t.data, s)
return t, nil
return t
}
func (c *testContext) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
func (c *testContext) FromIntSlice(s []int32, shape ...int) ml.Tensor {
f := make([]float32, len(s))
for i := range f {
f[i] = float32(s[i])
}
out, _ := c.FromFloatSlice(f, shape...)
out := c.FromFloatSlice(f, shape...)
out.(*testTensor).dtype = ml.DTypeI32
return out, nil
return out
}
func (c *testContext) Arange(start, stop, step float32, dtype ml.DType) ml.Tensor {
@@ -496,7 +496,7 @@ func (c *testContext) Arange(start, stop, step float32, dtype ml.DType) ml.Tenso
s = append(s, i)
}
out, _ := c.FromFloatSlice(s, len(s))
out := c.FromFloatSlice(s, len(s))
out.(*testTensor).dtype = dtype
return out
}