Initial commit
This commit is contained in:
redclawsystems
@@ -0,0 +1,723 @@
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//! Metal Flash Attention kernel implementation for macOS
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//!
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//! This module provides Metal shader-based Flash Attention implementation
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//! for Apple Silicon and macOS GPU acceleration.
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#![cfg(feature = "metal")]
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use crate::{
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config::FlashAttentionConfig,
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error::{FlashError, FlashResult},
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};
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use rtx_tensor::Tensor;
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use objc2::rc::Retained;
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use objc2::runtime::ProtocolObject;
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use objc2_foundation::{NSString, NSError};
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use objc2_metal::{
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MTLDevice, MTLCommandQueue, MTLComputePipelineState, MTLLibrary,
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MTLCreateSystemDefaultDevice, MTLSize, MTLCommandBuffer, MTLComputeCommandEncoder,
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MTLBuffer, MTLResourceOptions, MTLCommandEncoder,
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};
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use std::ptr::NonNull;
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use std::sync::Arc;
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use std::time::Instant;
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use tracing::{debug, info, warn, error};
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/// Forward pass block sizes (must match MSL shader BLOCK_Q_FWD, BLOCK_KV_FWD)
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/// 32KB threadgroup memory limit: Q(8KB) + K(8KB) + V(8KB) + S(4KB) = 28KB
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const BLOCK_Q_FWD: usize = 32;
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const BLOCK_KV_FWD: usize = 32;
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/// Backward pass block sizes (must match MSL shader BLOCK_Q_BWD, BLOCK_KV_BWD)
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/// Backward needs 5 tiles: Q+K+V+dO+O, so use smaller blocks
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/// 5 tiles * 16 * 128 * 2 = 20KB
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const BLOCK_Q_BWD: usize = 16;
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const BLOCK_KV_BWD: usize = 16;
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/// Maximum head dimension supported
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const MAX_HEAD_DIM: usize = 128;
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/// Flash Attention parameters structure matching the MSL shader
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#[repr(C)]
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#[derive(Debug, Clone, Copy)]
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struct FlashAttentionParams {
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batch_size: u32,
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num_heads: u32,
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seq_len_q: u32,
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seq_len_kv: u32,
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head_dim: u32,
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softmax_scale: f32,
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causal: u32,
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block_size_q: u32,
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block_size_kv: u32,
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}
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/// Metal kernel execution result with performance metrics
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#[derive(Debug, Clone)]
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pub struct MetalKernelResult {
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pub execution_time_us: u64,
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pub occupancy: f32,
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pub memory_throughput: f32,
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pub kernel_efficiency: f32,
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pub shared_memory_usage: usize,
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pub register_usage: usize,
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pub tensor_core_utilization: f32,
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}
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/// Flash Attention Metal kernels implementation
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pub struct FlashMetalKernels {
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config: FlashAttentionConfig,
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device: Retained<ProtocolObject<dyn MTLDevice>>,
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command_queue: Retained<ProtocolObject<dyn MTLCommandQueue>>,
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library: Option<Retained<ProtocolObject<dyn MTLLibrary>>>,
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forward_pipeline: Option<Retained<ProtocolObject<dyn MTLComputePipelineState>>>,
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backward_dq_pipeline: Option<Retained<ProtocolObject<dyn MTLComputePipelineState>>>,
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backward_dkv_pipeline: Option<Retained<ProtocolObject<dyn MTLComputePipelineState>>>,
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}
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impl std::fmt::Debug for FlashMetalKernels {
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fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
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f.debug_struct("FlashMetalKernels")
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.field("config", &self.config)
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.field("has_library", &self.library.is_some())
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.field("has_forward_pipeline", &self.forward_pipeline.is_some())
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.field("has_backward_dq_pipeline", &self.backward_dq_pipeline.is_some())
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.field("has_backward_dkv_pipeline", &self.backward_dkv_pipeline.is_some())
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.finish()
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}
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}
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impl FlashMetalKernels {
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/// Get the configuration
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pub fn config(&self) -> &FlashAttentionConfig {
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&self.config
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}
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/// MSL shader source embedded at compile time
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const SHADER_SOURCE: &'static str = include_str!("../../metal/flash_attention.metal");
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/// Create new Metal kernels instance
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pub fn new(config: &FlashAttentionConfig) -> FlashResult<Self> {
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info!("Initializing Metal Flash Attention kernels");
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// Get the default Metal device
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let device = unsafe { MTLCreateSystemDefaultDevice() }
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.ok_or_else(|| FlashError::config("No Metal device available"))?;
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// Create command queue
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let command_queue = device.newCommandQueue()
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.ok_or_else(|| FlashError::config("Failed to create Metal command queue"))?;
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info!("Metal device: {}", device.name());
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let mut kernels = Self {
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config: config.clone(),
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device,
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command_queue,
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library: None,
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forward_pipeline: None,
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backward_dq_pipeline: None,
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backward_dkv_pipeline: None,
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};
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// Compile shaders and create pipelines
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kernels.compile_shaders()?;
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info!("Successfully initialized Metal Flash Attention kernels");
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Ok(kernels)
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}
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/// Compile MSL shaders and create compute pipelines
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fn compile_shaders(&mut self) -> FlashResult<()> {
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info!("Compiling Metal Flash Attention shaders");
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// Compile shader source
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let source = NSString::from_str(Self::SHADER_SOURCE);
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let options: Option<&objc2_metal::MTLCompileOptions> = None;
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let library = unsafe {
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self.device.newLibraryWithSource_options_error(&source, options)
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}.map_err(|e| FlashError::kernel_compilation(format!("Failed to compile Metal shaders: {:?}", e)))?;
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// Create forward pipeline
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let forward_fn_name = NSString::from_str("flash_attention_forward");
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let forward_fn = library.newFunctionWithName(&forward_fn_name)
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.ok_or_else(|| FlashError::kernel_compilation("Failed to find flash_attention_forward function"))?;
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let forward_pipeline = unsafe {
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self.device.newComputePipelineStateWithFunction_error(&forward_fn)
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}.map_err(|e| FlashError::kernel_compilation(format!("Failed to create forward pipeline: {:?}", e)))?;
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// Create backward dQ pipeline
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let backward_dq_fn_name = NSString::from_str("flash_attention_backward_dq");
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let backward_dq_fn = library.newFunctionWithName(&backward_dq_fn_name)
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.ok_or_else(|| FlashError::kernel_compilation("Failed to find flash_attention_backward_dq function"))?;
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let backward_dq_pipeline = unsafe {
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self.device.newComputePipelineStateWithFunction_error(&backward_dq_fn)
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}.map_err(|e| FlashError::kernel_compilation(format!("Failed to create backward dQ pipeline: {:?}", e)))?;
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// Create backward dKV pipeline
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let backward_dkv_fn_name = NSString::from_str("flash_attention_backward_dkv");
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let backward_dkv_fn = library.newFunctionWithName(&backward_dkv_fn_name)
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.ok_or_else(|| FlashError::kernel_compilation("Failed to find flash_attention_backward_dkv function"))?;
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let backward_dkv_pipeline = unsafe {
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self.device.newComputePipelineStateWithFunction_error(&backward_dkv_fn)
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}.map_err(|e| FlashError::kernel_compilation(format!("Failed to create backward dKV pipeline: {:?}", e)))?;
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self.library = Some(library);
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self.forward_pipeline = Some(forward_pipeline);
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self.backward_dq_pipeline = Some(backward_dq_pipeline);
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self.backward_dkv_pipeline = Some(backward_dkv_pipeline);
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info!("Successfully compiled all Metal Flash Attention pipelines");
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Ok(())
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}
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/// Execute Flash Attention forward pass
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pub async fn flash_attention_forward(
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&self,
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q: &Tensor,
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k: &Tensor,
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v: &Tensor,
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output: &mut Tensor,
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lse: &mut Tensor,
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softmax_scale: f32,
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causal: bool,
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) -> FlashResult<MetalKernelResult> {
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debug!("Executing Metal Flash Attention forward pass");
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// Validate inputs
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self.validate_forward_tensors(q, k, v, output, lse)?;
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let batch_size = q.shape()[0];
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let num_heads = q.shape()[1];
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let seq_len_q = q.shape()[2];
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let seq_len_kv = k.shape()[2];
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let head_dim = q.shape()[3];
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if head_dim > MAX_HEAD_DIM {
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return Err(FlashError::config(format!(
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"Head dimension {} exceeds maximum supported {}",
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head_dim, MAX_HEAD_DIM
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)));
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}
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// Get pipeline
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let pipeline = self.forward_pipeline.as_ref()
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.ok_or_else(|| FlashError::kernel_compilation("Forward pipeline not initialized"))?;
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// Create command buffer
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let command_buffer = self.command_queue.commandBuffer()
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.ok_or_else(|| FlashError::kernel_compilation("Failed to create command buffer"))?;
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// Create compute encoder
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let encoder = command_buffer.computeCommandEncoder()
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.ok_or_else(|| FlashError::kernel_compilation("Failed to create compute encoder"))?;
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// Set pipeline state
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encoder.setComputePipelineState(pipeline);
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// Get Metal buffers from tensors
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let q_buffer = self.tensor_to_buffer(q)?;
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let k_buffer = self.tensor_to_buffer(k)?;
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let v_buffer = self.tensor_to_buffer(v)?;
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let output_buffer = self.tensor_to_buffer_mut(output)?;
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let lse_buffer = self.tensor_to_buffer_mut(lse)?;
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// Set buffers
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unsafe {
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encoder.setBuffer_offset_atIndex(Some(&q_buffer), 0, 0);
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encoder.setBuffer_offset_atIndex(Some(&k_buffer), 0, 1);
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encoder.setBuffer_offset_atIndex(Some(&v_buffer), 0, 2);
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encoder.setBuffer_offset_atIndex(Some(&output_buffer), 0, 3);
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encoder.setBuffer_offset_atIndex(Some(&lse_buffer), 0, 4);
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}
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// Set parameters
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let params = FlashAttentionParams {
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batch_size: batch_size as u32,
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num_heads: num_heads as u32,
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seq_len_q: seq_len_q as u32,
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seq_len_kv: seq_len_kv as u32,
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head_dim: head_dim as u32,
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softmax_scale,
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causal: if causal { 1 } else { 0 },
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block_size_q: BLOCK_Q_FWD as u32,
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block_size_kv: BLOCK_KV_FWD as u32,
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};
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unsafe {
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let params_ptr = NonNull::new_unchecked(
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¶ms as *const FlashAttentionParams as *mut std::ffi::c_void
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);
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encoder.setBytes_length_atIndex(
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params_ptr,
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std::mem::size_of::<FlashAttentionParams>(),
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5
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);
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}
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// Calculate threadgroup and grid sizes (using forward block sizes)
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let block_q = BLOCK_Q_FWD.min(seq_len_q);
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let num_q_blocks = (seq_len_q + block_q - 1) / block_q;
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let threadgroup_size = MTLSize {
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width: block_q,
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height: 1,
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depth: 1,
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};
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let grid_size = MTLSize {
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width: num_q_blocks,
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height: num_heads,
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depth: batch_size,
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};
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// Dispatch
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encoder.dispatchThreadgroups_threadsPerThreadgroup(grid_size, threadgroup_size);
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encoder.endEncoding();
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// Execute and measure time
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let start = Instant::now();
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command_buffer.commit();
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command_buffer.waitUntilCompleted();
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let execution_time_us = start.elapsed().as_micros() as u64;
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// Check for errors
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if let Some(error) = command_buffer.error() {
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return Err(FlashError::kernel_compilation(format!(
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"Metal command buffer execution failed: {}",
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error.localizedDescription()
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)));
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}
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// Calculate metrics
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let total_bytes = (batch_size * num_heads * seq_len_q * head_dim * 2 * 4) as f32; // Q, K, V, O in half precision
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let memory_throughput = if execution_time_us > 0 {
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total_bytes / (execution_time_us as f32 / 1_000_000.0) / 1e9 // GB/s
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} else {
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0.0
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};
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// Forward: Q_tile(8KB) + K_tile(8KB) + V_tile(8KB) + S_tile(4KB) = 28KB
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let shared_memory_per_block = (BLOCK_Q_FWD * MAX_HEAD_DIM + 2 * BLOCK_KV_FWD * MAX_HEAD_DIM) * 2 // Q, K, V in half
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+ BLOCK_Q_FWD * BLOCK_KV_FWD * 4; // S in float
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debug!(
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"Flash Attention forward completed in {}us, throughput: {:.2} GB/s",
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execution_time_us, memory_throughput
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);
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Ok(MetalKernelResult {
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execution_time_us,
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occupancy: 0.85, // Estimate
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memory_throughput,
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kernel_efficiency: 0.80, // Estimate
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shared_memory_usage: shared_memory_per_block,
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register_usage: 64, // Estimate
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tensor_core_utilization: 0.0, // Metal doesn't have tensor cores
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})
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}
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/// Execute Flash Attention backward pass
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pub async fn flash_attention_backward(
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&self,
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dout: &Tensor,
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q: &Tensor,
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k: &Tensor,
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v: &Tensor,
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output: &Tensor,
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lse: &Tensor,
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grad_q: &mut Tensor,
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grad_k: &mut Tensor,
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grad_v: &mut Tensor,
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softmax_scale: f32,
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causal: bool,
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) -> FlashResult<MetalKernelResult> {
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debug!("Executing Metal Flash Attention backward pass");
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let batch_size = q.shape()[0];
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let num_heads = q.shape()[1];
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let seq_len_q = q.shape()[2];
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let seq_len_kv = k.shape()[2];
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let head_dim = q.shape()[3];
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if head_dim > MAX_HEAD_DIM {
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return Err(FlashError::config(format!(
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"Head dimension {} exceeds maximum supported {}",
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head_dim, MAX_HEAD_DIM
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)));
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}
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// Get pipelines
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let dq_pipeline = self.backward_dq_pipeline.as_ref()
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.ok_or_else(|| FlashError::kernel_compilation("Backward dQ pipeline not initialized"))?;
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let dkv_pipeline = self.backward_dkv_pipeline.as_ref()
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.ok_or_else(|| FlashError::kernel_compilation("Backward dKV pipeline not initialized"))?;
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// Create Metal buffers
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let dout_buffer = self.tensor_to_buffer(dout)?;
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let q_buffer = self.tensor_to_buffer(q)?;
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let k_buffer = self.tensor_to_buffer(k)?;
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let v_buffer = self.tensor_to_buffer(v)?;
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let output_buffer = self.tensor_to_buffer(output)?;
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let lse_buffer = self.tensor_to_buffer(lse)?;
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let grad_q_buffer = self.tensor_to_buffer_mut(grad_q)?;
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let grad_k_buffer = self.tensor_to_buffer_mut(grad_k)?;
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let grad_v_buffer = self.tensor_to_buffer_mut(grad_v)?;
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// Backward pass uses smaller block sizes (16x16) to fit 5 tiles in 32KB
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let params = FlashAttentionParams {
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batch_size: batch_size as u32,
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num_heads: num_heads as u32,
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seq_len_q: seq_len_q as u32,
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seq_len_kv: seq_len_kv as u32,
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head_dim: head_dim as u32,
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softmax_scale,
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causal: if causal { 1 } else { 0 },
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block_size_q: BLOCK_Q_BWD as u32,
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block_size_kv: BLOCK_KV_BWD as u32,
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};
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let start = Instant::now();
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// === Execute backward dQ kernel ===
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{
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let command_buffer = self.command_queue.commandBuffer()
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.ok_or_else(|| FlashError::kernel_compilation("Failed to create command buffer for dQ"))?;
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let encoder = command_buffer.computeCommandEncoder()
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.ok_or_else(|| FlashError::kernel_compilation("Failed to create compute encoder for dQ"))?;
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encoder.setComputePipelineState(dq_pipeline);
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unsafe {
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encoder.setBuffer_offset_atIndex(Some(&dout_buffer), 0, 0);
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encoder.setBuffer_offset_atIndex(Some(&q_buffer), 0, 1);
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encoder.setBuffer_offset_atIndex(Some(&k_buffer), 0, 2);
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encoder.setBuffer_offset_atIndex(Some(&v_buffer), 0, 3);
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encoder.setBuffer_offset_atIndex(Some(&output_buffer), 0, 4);
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encoder.setBuffer_offset_atIndex(Some(&lse_buffer), 0, 5);
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encoder.setBuffer_offset_atIndex(Some(&grad_q_buffer), 0, 6);
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let params_ptr = NonNull::new_unchecked(
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¶ms as *const FlashAttentionParams as *mut std::ffi::c_void
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);
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encoder.setBytes_length_atIndex(
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params_ptr,
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std::mem::size_of::<FlashAttentionParams>(),
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7
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);
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}
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// Backward uses smaller blocks (16x16)
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let block_q = BLOCK_Q_BWD.min(seq_len_q);
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let num_q_blocks = (seq_len_q + block_q - 1) / block_q;
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let threadgroup_size = MTLSize { width: block_q, height: 1, depth: 1 };
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let grid_size = MTLSize {
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width: num_q_blocks,
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height: num_heads,
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depth: batch_size,
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};
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encoder.dispatchThreadgroups_threadsPerThreadgroup(grid_size, threadgroup_size);
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encoder.endEncoding();
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command_buffer.commit();
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command_buffer.waitUntilCompleted();
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if let Some(error) = command_buffer.error() {
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return Err(FlashError::kernel_compilation(format!(
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"Metal backward dQ execution failed: {}",
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error.localizedDescription()
|
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)));
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}
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}
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// === Execute backward dKV kernel ===
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{
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let command_buffer = self.command_queue.commandBuffer()
|
||||
.ok_or_else(|| FlashError::kernel_compilation("Failed to create command buffer for dKV"))?;
|
||||
|
||||
let encoder = command_buffer.computeCommandEncoder()
|
||||
.ok_or_else(|| FlashError::kernel_compilation("Failed to create compute encoder for dKV"))?;
|
||||
|
||||
encoder.setComputePipelineState(dkv_pipeline);
|
||||
|
||||
unsafe {
|
||||
encoder.setBuffer_offset_atIndex(Some(&dout_buffer), 0, 0);
|
||||
encoder.setBuffer_offset_atIndex(Some(&q_buffer), 0, 1);
|
||||
encoder.setBuffer_offset_atIndex(Some(&k_buffer), 0, 2);
|
||||
encoder.setBuffer_offset_atIndex(Some(&v_buffer), 0, 3);
|
||||
encoder.setBuffer_offset_atIndex(Some(&output_buffer), 0, 4);
|
||||
encoder.setBuffer_offset_atIndex(Some(&lse_buffer), 0, 5);
|
||||
encoder.setBuffer_offset_atIndex(Some(&grad_k_buffer), 0, 6);
|
||||
encoder.setBuffer_offset_atIndex(Some(&grad_v_buffer), 0, 7);
|
||||
|
||||
let params_ptr = NonNull::new_unchecked(
|
||||
¶ms as *const FlashAttentionParams as *mut std::ffi::c_void
|
||||
);
|
||||
encoder.setBytes_length_atIndex(
|
||||
params_ptr,
|
||||
std::mem::size_of::<FlashAttentionParams>(),
|
||||
8
|
||||
);
|
||||
}
|
||||
|
||||
// Backward uses smaller blocks (16x16)
|
||||
let block_kv = BLOCK_KV_BWD.min(seq_len_kv);
|
||||
let num_kv_blocks = (seq_len_kv + block_kv - 1) / block_kv;
|
||||
|
||||
let threadgroup_size = MTLSize { width: block_kv, height: 1, depth: 1 };
|
||||
let grid_size = MTLSize {
|
||||
width: num_kv_blocks,
|
||||
height: num_heads,
|
||||
depth: batch_size,
|
||||
};
|
||||
|
||||
encoder.dispatchThreadgroups_threadsPerThreadgroup(grid_size, threadgroup_size);
|
||||
encoder.endEncoding();
|
||||
|
||||
command_buffer.commit();
|
||||
command_buffer.waitUntilCompleted();
|
||||
|
||||
if let Some(error) = command_buffer.error() {
|
||||
return Err(FlashError::kernel_compilation(format!(
|
||||
"Metal backward dKV execution failed: {}",
|
||||
error.localizedDescription()
|
||||
)));
|
||||
}
|
||||
}
|
||||
|
||||
let execution_time_us = start.elapsed().as_micros() as u64;
|
||||
|
||||
// Calculate metrics
|
||||
let total_bytes = (batch_size * num_heads * seq_len_q * head_dim * 2 * 7) as f32; // Multiple tensors
|
||||
let memory_throughput = if execution_time_us > 0 {
|
||||
total_bytes / (execution_time_us as f32 / 1_000_000.0) / 1e9
|
||||
} else {
|
||||
0.0
|
||||
};
|
||||
|
||||
debug!(
|
||||
"Flash Attention backward completed in {}us, throughput: {:.2} GB/s",
|
||||
execution_time_us, memory_throughput
|
||||
);
|
||||
|
||||
// Backward: 5 tiles * 16 * 128 * 2 = 20KB
|
||||
let shared_memory_per_block = 5 * BLOCK_Q_BWD * MAX_HEAD_DIM * 2; // Q, K, V, dO, O in half
|
||||
|
||||
Ok(MetalKernelResult {
|
||||
execution_time_us,
|
||||
occupancy: 0.80,
|
||||
memory_throughput,
|
||||
kernel_efficiency: 0.75,
|
||||
shared_memory_usage: shared_memory_per_block,
|
||||
register_usage: 96,
|
||||
tensor_core_utilization: 0.0,
|
||||
})
|
||||
}
|
||||
|
||||
/// Convert tensor to Metal buffer (for read-only access)
|
||||
fn tensor_to_buffer(&self, tensor: &Tensor) -> FlashResult<Retained<ProtocolObject<dyn MTLBuffer>>> {
|
||||
let data = tensor.data()
|
||||
.map_err(|e| FlashError::memory(format!("Failed to get tensor data: {}", e)))?;
|
||||
|
||||
let byte_length = data.len() * std::mem::size_of::<f32>();
|
||||
|
||||
// Create buffer with shared storage mode
|
||||
let buffer = self.device.newBufferWithLength_options(
|
||||
byte_length,
|
||||
MTLResourceOptions::StorageModeShared
|
||||
).ok_or_else(|| FlashError::memory("Failed to create Metal buffer"))?;
|
||||
|
||||
// Copy data to buffer
|
||||
let ptr = buffer.contents();
|
||||
unsafe {
|
||||
std::ptr::copy_nonoverlapping(
|
||||
data.as_ptr(),
|
||||
ptr.as_ptr() as *mut f32,
|
||||
data.len()
|
||||
);
|
||||
}
|
||||
|
||||
Ok(buffer)
|
||||
}
|
||||
|
||||
/// Convert tensor to Metal buffer (for write access)
|
||||
/// Note: This creates a buffer from current tensor data. After GPU execution,
|
||||
/// results need to be copied back to the tensor.
|
||||
fn tensor_to_buffer_mut(&self, tensor: &mut Tensor) -> FlashResult<Retained<ProtocolObject<dyn MTLBuffer>>> {
|
||||
let data = tensor.data()
|
||||
.map_err(|e| FlashError::memory(format!("Failed to get tensor data: {}", e)))?;
|
||||
|
||||
let byte_length = data.len() * std::mem::size_of::<f32>();
|
||||
|
||||
// Create buffer with shared storage mode
|
||||
let buffer = self.device.newBufferWithLength_options(
|
||||
byte_length,
|
||||
MTLResourceOptions::StorageModeShared
|
||||
).ok_or_else(|| FlashError::memory("Failed to create Metal buffer"))?;
|
||||
|
||||
// Copy data to buffer
|
||||
let ptr = buffer.contents();
|
||||
unsafe {
|
||||
std::ptr::copy_nonoverlapping(
|
||||
data.as_ptr(),
|
||||
ptr.as_ptr() as *mut f32,
|
||||
data.len()
|
||||
);
|
||||
}
|
||||
|
||||
Ok(buffer)
|
||||
}
|
||||
|
||||
/// Optimize block sizes for Metal hardware (returns forward pass block sizes)
|
||||
///
|
||||
/// Apple Silicon has 32KB threadgroup memory limit.
|
||||
/// Forward: Q(8KB) + K(8KB) + V(8KB) + S(4KB) = 28KB with 32x32 blocks
|
||||
/// Backward: 5 tiles = 20KB with 16x16 blocks
|
||||
pub fn optimize_block_sizes(&self, seq_len: usize, _head_dim: usize) -> (usize, usize) {
|
||||
// Forward block sizes (32x32 fits in 32KB threadgroup memory)
|
||||
let optimal_q = BLOCK_Q_FWD.min(seq_len);
|
||||
let optimal_kv = BLOCK_KV_FWD.min(seq_len);
|
||||
|
||||
// Ensure alignment to simdgroup size (32 threads for Apple Silicon)
|
||||
let optimal_q = (optimal_q / 32) * 32;
|
||||
let optimal_kv = (optimal_kv / 32) * 32;
|
||||
|
||||
let optimal_q = optimal_q.max(32);
|
||||
let optimal_kv = optimal_kv.max(32);
|
||||
|
||||
debug!(
|
||||
"Optimized Metal block sizes: Q={}, KV={} for seq_len={}",
|
||||
optimal_q, optimal_kv, seq_len
|
||||
);
|
||||
|
||||
(optimal_q, optimal_kv)
|
||||
}
|
||||
|
||||
/// Get Metal device information
|
||||
pub fn get_device_info(&self) -> FlashResult<String> {
|
||||
let device_name = self.device.name().to_string();
|
||||
let max_threadgroup = self.forward_pipeline.as_ref()
|
||||
.map(|p| p.maxTotalThreadsPerThreadgroup())
|
||||
.unwrap_or(0);
|
||||
|
||||
Ok(format!(
|
||||
"Metal Device: {}, Max Threadgroup Size: {}",
|
||||
device_name, max_threadgroup
|
||||
))
|
||||
}
|
||||
|
||||
/// Validate tensor dimensions for forward pass
|
||||
fn validate_forward_tensors(
|
||||
&self,
|
||||
q: &Tensor,
|
||||
k: &Tensor,
|
||||
v: &Tensor,
|
||||
output: &Tensor,
|
||||
lse: &Tensor,
|
||||
) -> FlashResult<()> {
|
||||
let q_shape = q.shape();
|
||||
let k_shape = k.shape();
|
||||
let v_shape = v.shape();
|
||||
let output_shape = output.shape();
|
||||
let lse_shape = lse.shape();
|
||||
|
||||
// Check all tensors have 4D shape except LSE (3D)
|
||||
if q_shape.len() != 4 || k_shape.len() != 4 || v_shape.len() != 4 || output_shape.len() != 4 {
|
||||
return Err(FlashError::config(
|
||||
"Q, K, V, and output tensors must be 4D [batch, heads, seq_len, head_dim]"
|
||||
));
|
||||
}
|
||||
|
||||
if lse_shape.len() != 3 {
|
||||
return Err(FlashError::config(
|
||||
"LSE tensor must be 3D [batch, heads, seq_len]"
|
||||
));
|
||||
}
|
||||
|
||||
// Check batch and head dimensions match
|
||||
if q_shape[0] != k_shape[0] || q_shape[0] != v_shape[0] || q_shape[0] != output_shape[0] {
|
||||
return Err(FlashError::config("Batch dimensions must match"));
|
||||
}
|
||||
|
||||
if q_shape[1] != k_shape[1] || q_shape[1] != v_shape[1] || q_shape[1] != output_shape[1] {
|
||||
return Err(FlashError::config("Number of heads must match"));
|
||||
}
|
||||
|
||||
// Check head_dim matches
|
||||
if q_shape[3] != k_shape[3] || q_shape[3] != v_shape[3] || q_shape[3] != output_shape[3] {
|
||||
return Err(FlashError::config("Head dimensions must match"));
|
||||
}
|
||||
|
||||
// Q and output seq_len must match
|
||||
if q_shape[2] != output_shape[2] {
|
||||
return Err(FlashError::config("Q and output sequence lengths must match"));
|
||||
}
|
||||
|
||||
// K and V seq_len must match
|
||||
if k_shape[2] != v_shape[2] {
|
||||
return Err(FlashError::config("K and V sequence lengths must match"));
|
||||
}
|
||||
|
||||
// Check LSE shape matches first 3 dimensions of Q
|
||||
if lse_shape[0] != q_shape[0] || lse_shape[1] != q_shape[1] || lse_shape[2] != q_shape[2] {
|
||||
return Err(FlashError::config(
|
||||
"LSE tensor shape must match [batch, heads, seq_len] dimensions of Q"
|
||||
));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_metal_device_creation() {
|
||||
// Test that we can create a Metal device
|
||||
let device = unsafe { MTLCreateSystemDefaultDevice() };
|
||||
assert!(device.is_some(), "Metal device should be available on macOS");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_metal_kernels_creation() {
|
||||
let config = FlashAttentionConfig::new(8, 64);
|
||||
let result = FlashMetalKernels::new(&config);
|
||||
|
||||
// This should succeed on macOS with Metal support
|
||||
if let Ok(kernels) = result {
|
||||
assert!(kernels.forward_pipeline.is_some(), "Forward pipeline should be created");
|
||||
assert!(kernels.backward_dq_pipeline.is_some(), "Backward dQ pipeline should be created");
|
||||
assert!(kernels.backward_dkv_pipeline.is_some(), "Backward dKV pipeline should be created");
|
||||
assert!(kernels.get_device_info().is_ok());
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_block_size_optimization() {
|
||||
let config = FlashAttentionConfig::new(8, 64);
|
||||
|
||||
if let Ok(kernels) = FlashMetalKernels::new(&config) {
|
||||
let (block_q, block_kv) = kernels.optimize_block_sizes(1024, 64);
|
||||
|
||||
assert!(block_q >= 32);
|
||||
assert!(block_q <= 256);
|
||||
assert!(block_kv >= 32);
|
||||
assert!(block_kv <= 256);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_params_size() {
|
||||
// Ensure params struct has expected size for Metal buffer alignment
|
||||
assert_eq!(std::mem::size_of::<FlashAttentionParams>(), 36);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user