//go:build darwin && arm64 && mlx package mlx /* #include #include "mlx/c/mlx.h" */ import "C" import "unsafe" // RMSNorm applies Root Mean Square normalization using a fused Metal kernel. func RMSNorm(x, weight *Array, eps float32) *Array { out := New("FAST_RMSNORM", x) C.mlx_fast_rms_norm(&out.ctx, x.ctx, weight.ctx, C.float(eps), DefaultStream().ctx) return out } // LayerNorm applies Layer normalization using a fused Metal kernel. func LayerNorm(x, weight, bias *Array, eps float32) *Array { out := New("FAST_LAYERNORM", x) C.mlx_fast_layer_norm(&out.ctx, x.ctx, weight.ctx, bias.ctx, C.float(eps), DefaultStream().ctx) return out } // RoPE applies Rotary Position Embeddings using a fused Metal kernel. func RoPE(x *Array, dims int, traditional bool, base float32, scale float32, offset int) *Array { freqs := New("") out := New("FAST_ROPE", x, freqs) C.mlx_fast_rope( &out.ctx, x.ctx, C.int(dims), C._Bool(traditional), C.mlx_optional_float{ value: C.float(base), has_value: C._Bool(base != 0), }, C.float(scale), C.int(offset), freqs.ctx, DefaultStream().ctx, ) return out } // ScaledDotProductAttention computes attention using a fused Metal kernel. // mask can be nil for causal masking, or set causal=true for auto causal mask. func ScaledDotProductAttention(query, key, value *Array, scale float32, causal bool) *Array { var mask, sinks *Array if causal { mask = New("") sinks = New("") } else { mask = New("") sinks = New("") } mode := "causal" if !causal { mode = "none" } cMode := C.CString(mode) defer C.free(unsafe.Pointer(cMode)) out := New("FAST_SDPA", query, key, value, mask, sinks) C.mlx_fast_scaled_dot_product_attention(&out.ctx, query.ctx, key.ctx, value.ctx, C.float(scale), cMode, mask.ctx, sinks.ctx, DefaultStream().ctx) return out } // ScaledDotProductAttentionWithMask computes attention with an explicit mask. func ScaledDotProductAttentionWithMask(query, key, value, mask *Array, scale float32) *Array { sinks := New("") cMode := C.CString("none") defer C.free(unsafe.Pointer(cMode)) out := New("FAST_SDPA", query, key, value, mask, sinks) C.mlx_fast_scaled_dot_product_attention(&out.ctx, query.ctx, key.ctx, value.ctx, C.float(scale), cMode, mask.ctx, sinks.ctx, DefaultStream().ctx) return out }