kvcache: Use Cast instead of Copy for flash attention masks

Flash attention kernels require the mask of the KV cache be a F16
rather than an F32. We can use the GGML operation ggml_cast to do
this rather than doing it ourselves, which allows reuse of a
preallocated buffer in the graph rather than allocating a new one
for each batch. This improves token generation performance with
flash attention by 10-30% (with gpt-oss). This also makes performance
with flash attention better than without it, as expected.

kvcache/causal.go

@@ -378,9 +378,7 @@ func (c *Causal) buildMask(ctx ml.Context) ml.Tensor {
 	maskTensor := ctx.Input().FromFloatSlice(mask, length, batchSize)
 
 	if c.config.MaskDType != ml.DTypeF32 {
-		out := ctx.Input().Empty(c.config.MaskDType, maskTensor.Shape()...)
-		ctx.Forward(maskTensor.Copy(ctx, out))
-		maskTensor = out
+		maskTensor = maskTensor.Cast(ctx, c.config.MaskDType)
 	}
 
 	return maskTensor