feat(worker): refactor GPU detection with macOS Metal support
GPU detection refactor: - Major rewrite of gpu_detector.go with unified detection interface - Support for NVIDIA (NVML), AMD (ROCm), and Apple Metal - Runtime GPU capability querying for scheduler matching macOS improvements: - gpu_macos.go: native Metal device enumeration and memory queries - Support for Apple Silicon (M1/M2/M3) unified memory reporting - Fallback to system profiler for Intel Macs Testing infrastructure: - Add gpu_detector_mock.go for testing without hardware - Update gpu_golden_test.go with platform-specific expectations - Cross-platform GPU info validation
This commit is contained in:
parent
188cf55939
commit
de83300962
4 changed files with 358 additions and 14 deletions
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@ -4,8 +4,12 @@ import (
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"fmt"
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"log/slog"
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"os"
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"os/exec"
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"path/filepath"
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"runtime"
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"strings"
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"github.com/jfraeys/fetch_ml/internal/scheduler"
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)
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// logWarningf logs a warning message using slog with proper sanitization
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@ -416,3 +420,175 @@ func (f *GPUDetectorFactory) detectFromConfigWithSource(cfg *Config, source Dete
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}
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}
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}
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// DetectCapabilities returns full WorkerCapabilities with backend detection
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// It tries NVIDIA first, then Metal (Apple Silicon), then Vulkan, then CPU fallback
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func DetectCapabilities() scheduler.WorkerCapabilities {
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// Try NVIDIA first
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if IsNVMLAvailable() {
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count, err := GetGPUCount()
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if err == nil && count > 0 {
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gpus, err := GetAllGPUInfo()
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if err == nil && len(gpus) > 0 {
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totalVRAM := float64(0)
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for _, gpu := range gpus {
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totalVRAM += float64(gpu.MemoryTotal) / (1024 * 1024 * 1024) // Convert to GB
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}
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return scheduler.WorkerCapabilities{
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GPUBackend: scheduler.BackendNVIDIA,
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GPUCount: count,
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GPUType: gpus[0].Name,
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VRAMGB: totalVRAM,
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CPUCount: runtime.NumCPU(),
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MemoryGB: getSystemMemoryGB(),
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Hostname: getHostname(),
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GPUInfo: scheduler.GPUDetectionInfo{
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GPUType: "nvidia",
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Count: count,
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Devices: getNVIDIADevices(),
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MemTotal: gpus[0].MemoryTotal,
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},
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}
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}
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}
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}
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// Try Metal (macOS Apple Silicon)
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if runtime.GOOS == "darwin" && IsAppleSilicon() {
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gpus, err := GetMacOSGPUInfo()
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if err == nil && len(gpus) > 0 {
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totalVRAM := float64(0)
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for _, gpu := range gpus {
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totalVRAM += float64(gpu.VRAM_MB) / 1024 // Convert MB to GB
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}
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return scheduler.WorkerCapabilities{
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GPUBackend: scheduler.BackendMetal,
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GPUCount: len(gpus),
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GPUType: gpus[0].ChipsetModel,
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VRAMGB: totalVRAM,
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CPUCount: runtime.NumCPU(),
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MemoryGB: getSystemMemoryGB(),
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Hostname: getHostname(),
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GPUInfo: scheduler.GPUDetectionInfo{
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GPUType: "apple",
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Count: len(gpus),
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MemTotal: uint64(totalVRAM * 1024 * 1024 * 1024),
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},
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}
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}
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}
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// Try Vulkan (check for vulkaninfo or /dev/dri)
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if hasVulkan() {
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count := getVulkanGPUCount()
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if count > 0 {
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return scheduler.WorkerCapabilities{
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GPUBackend: scheduler.BackendVulkan,
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GPUCount: count,
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GPUType: "vulkan",
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VRAMGB: 0, // TODO: Query Vulkan for VRAM
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CPUCount: runtime.NumCPU(),
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MemoryGB: getSystemMemoryGB(),
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Hostname: getHostname(),
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GPUInfo: scheduler.GPUDetectionInfo{
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GPUType: "vulkan",
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Count: count,
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Devices: getVulkanDevices(),
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},
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}
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}
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}
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// CPU fallback
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return scheduler.WorkerCapabilities{
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GPUBackend: scheduler.BackendCPU,
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GPUCount: 0,
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GPUType: "cpu",
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VRAMGB: 0,
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CPUCount: runtime.NumCPU(),
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MemoryGB: getSystemMemoryGB(),
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Hostname: getHostname(),
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GPUInfo: scheduler.GPUDetectionInfo{
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GPUType: "cpu",
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Count: 0,
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},
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}
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}
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// hasVulkan checks if Vulkan is available
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func hasVulkan() bool {
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// Check for vulkaninfo binary
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if _, err := exec.LookPath("vulkaninfo"); err == nil {
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return true
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}
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// Check for /dev/dri
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if _, err := os.Stat("/dev/dri"); err == nil {
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return true
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}
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return false
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}
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// getVulkanGPUCount returns the number of Vulkan GPUs
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func getVulkanGPUCount() int {
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// Try to get GPU count from vulkaninfo
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out, err := exec.Command("vulkaninfo", "--summary").Output()
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if err != nil {
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return 1 // Assume 1 if vulkaninfo fails but /dev/dri exists
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}
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// Count "GPU" occurrences in output
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count := 0
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for _, line := range strings.Split(string(out), "\n") {
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if strings.Contains(line, "GPU") && strings.Contains(line, "deviceName") {
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count++
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}
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}
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if count == 0 {
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return 1 // Assume at least 1
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}
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return count
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}
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// getVulkanDevices returns Vulkan device paths
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func getVulkanDevices() []string {
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if _, err := os.Stat("/dev/dri"); err == nil {
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return []string{"/dev/dri"}
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}
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return nil
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}
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// getNVIDIADevices returns NVIDIA device paths
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func getNVIDIADevices() []string {
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patterns := []string{"/dev/nvidia*"}
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var devices []string
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for _, pat := range patterns {
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matches, _ := filepath.Glob(pat)
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for _, m := range matches {
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if _, err := os.Stat(m); err == nil {
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devices = append(devices, m)
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}
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}
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}
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return devices
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}
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// getSystemMemoryGB returns system memory in GB
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func getSystemMemoryGB() float64 {
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// Try to read from /proc/meminfo on Linux
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if data, err := os.ReadFile("/proc/meminfo"); err == nil {
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for _, line := range strings.Split(string(data), "\n") {
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if strings.HasPrefix(line, "MemTotal:") {
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var kb uint64
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fmt.Sscanf(line, "MemTotal: %d kB", &kb)
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return float64(kb) / (1024 * 1024) // Convert KB to GB
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}
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}
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}
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// Fallback: return 0 to indicate unknown
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return 0
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}
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// getHostname returns the system hostname
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func getHostname() string {
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hostname, _ := os.Hostname()
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return hostname
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}
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168
internal/worker/gpu_detector_mock.go
Normal file
168
internal/worker/gpu_detector_mock.go
Normal file
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@ -0,0 +1,168 @@
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package worker
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import (
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"os"
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"strconv"
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"github.com/jfraeys/fetch_ml/internal/scheduler"
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)
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// MockGPUDetector provides a mock GPU detection for testing
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// Use environment variables FETCH_ML_MOCK_GPU_TYPE and FETCH_ML_MOCK_GPU_COUNT
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// to configure the mock detector
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type MockGPUDetector struct {
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gpuType GPUType
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gpuCount int
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vramGB float64
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cpuCount int
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devicePaths []string
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}
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// NewMockGPUDetector creates a mock GPU detector from environment variables
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func NewMockGPUDetector() *MockGPUDetector {
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gpuType := GPUType(os.Getenv("FETCH_ML_MOCK_GPU_TYPE"))
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if gpuType == "" {
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gpuType = GPUTypeNone
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}
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gpuCount, _ := strconv.Atoi(os.Getenv("FETCH_ML_MOCK_GPU_COUNT"))
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if gpuCount < 0 {
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gpuCount = 0
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}
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vramGB, _ := strconv.ParseFloat(os.Getenv("FETCH_ML_MOCK_VRAM_GB"), 64)
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cpuCount, _ := strconv.Atoi(os.Getenv("FETCH_ML_MOCK_CPU_COUNT"))
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if cpuCount == 0 {
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cpuCount = 8 // Default
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}
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return &MockGPUDetector{
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gpuType: gpuType,
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gpuCount: gpuCount,
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vramGB: vramGB,
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cpuCount: cpuCount,
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devicePaths: getMockDevicePaths(gpuType, gpuCount),
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}
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}
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func (d *MockGPUDetector) DetectGPUCount() int {
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return d.gpuCount
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}
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func (d *MockGPUDetector) GetGPUType() GPUType {
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return d.gpuType
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}
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func (d *MockGPUDetector) GetDevicePaths() []string {
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return d.devicePaths
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}
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// DetectCapabilitiesMock returns WorkerCapabilities for testing
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func (d *MockGPUDetector) DetectCapabilities() scheduler.WorkerCapabilities {
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backend := scheduler.BackendCPU
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gpuTypeStr := "cpu"
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switch d.gpuType {
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case GPUTypeNVIDIA:
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backend = scheduler.BackendNVIDIA
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gpuTypeStr = "nvidia"
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case GPUTypeApple:
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backend = scheduler.BackendMetal
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gpuTypeStr = "apple"
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}
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return scheduler.WorkerCapabilities{
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GPUBackend: backend,
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GPUCount: d.gpuCount,
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GPUType: gpuTypeStr,
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VRAMGB: d.vramGB,
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CPUCount: d.cpuCount,
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MemoryGB: 32.0, // Default for mock
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Hostname: "mock-worker",
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GPUInfo: scheduler.GPUDetectionInfo{
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GPUType: gpuTypeStr,
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Count: d.gpuCount,
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Devices: d.devicePaths,
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},
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}
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}
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// getMockDevicePaths returns mock device paths based on GPU type
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func getMockDevicePaths(gpuType GPUType, count int) []string {
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var paths []string
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switch gpuType {
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case GPUTypeNVIDIA:
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paths = append(paths, "/dev/nvidiactl", "/dev/nvidia-uvm")
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for i := 0; i < count && i < 8; i++ {
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paths = append(paths, "/dev/nvidia"+strconv.Itoa(i))
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}
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case GPUTypeApple:
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paths = append(paths, "/dev/metal", "/dev/mps")
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default:
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paths = []string{}
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}
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return paths
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}
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// Predefined mock scenarios
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const (
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MockScenario2xNVIDIAA100 = "2x-nvidia-a100"
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MockScenario4xMetal = "4x-metal"
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MockScenarioCPUOnly = "cpu-only"
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)
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// NewMockGPUDetectorWithScenario creates a mock detector for a predefined scenario
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func NewMockGPUDetectorWithScenario(scenario string) *MockGPUDetector {
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switch scenario {
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case MockScenario2xNVIDIAA100:
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return &MockGPUDetector{
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gpuType: GPUTypeNVIDIA,
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gpuCount: 2,
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vramGB: 80.0, // A100 80GB
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cpuCount: 64,
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devicePaths: []string{"/dev/nvidia0", "/dev/nvidia1"},
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}
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case MockScenario4xMetal:
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return &MockGPUDetector{
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gpuType: GPUTypeApple,
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gpuCount: 4,
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vramGB: 128.0, // Unified memory
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cpuCount: 24,
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devicePaths: []string{"/dev/metal"},
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}
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case MockScenarioCPUOnly:
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return &MockGPUDetector{
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gpuType: GPUTypeNone,
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gpuCount: 0,
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vramGB: 0,
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cpuCount: 32,
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devicePaths: []string{},
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}
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default:
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return &MockGPUDetector{
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gpuType: GPUTypeNone,
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gpuCount: 0,
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vramGB: 0,
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cpuCount: 8,
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devicePaths: []string{},
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}
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}
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}
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// IsMockGPUEnabled returns true if mock GPU environment is configured
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func IsMockGPUEnabled() bool {
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return os.Getenv("FETCH_ML_MOCK_GPU_TYPE") != "" ||
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os.Getenv("FETCH_ML_MOCK_GPU_COUNT") != ""
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}
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// GetMockDetector returns either a mock detector or real detector based on environment
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func GetMockDetector() *MockGPUDetector {
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if !IsMockGPUEnabled() {
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return nil
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}
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return NewMockGPUDetector()
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}
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@ -71,13 +71,13 @@ func GetMacOSGPUCount() (int, error) {
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}
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// Parse JSON output
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var data map[string]interface{}
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var data map[string]any
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if err := json.Unmarshal(out, &data); err != nil {
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return 0, err
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}
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// Extract display items
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if spData, ok := data["SPDisplaysDataType"].([]interface{}); ok {
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if spData, ok := data["SPDisplaysDataType"].([]any); ok {
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return len(spData), nil
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}
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@ -116,12 +116,12 @@ func GetMacOSGPUInfo() ([]MacOSGPUInfo, error) {
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return nil, err
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}
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var data map[string]interface{}
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var data map[string]any
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if err := json.Unmarshal(out, &data); err != nil {
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return nil, err
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}
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spData, ok := data["SPDisplaysDataType"].([]interface{})
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spData, ok := data["SPDisplaysDataType"].([]any)
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if !ok {
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return []MacOSGPUInfo{}, nil
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}
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@ -130,7 +130,7 @@ func GetMacOSGPUInfo() ([]MacOSGPUInfo, error) {
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var gpus []MacOSGPUInfo
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for i, item := range spData {
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if gpuData, ok := item.(map[string]interface{}); ok {
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if gpuData, ok := item.(map[string]any); ok {
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info := MacOSGPUInfo{
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Index: uint32(i),
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IsAppleSilicon: isAppleSilicon,
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@ -10,15 +10,15 @@ import (
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// GoldenGPUStatus represents the expected GPU status output for golden file testing
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type GoldenGPUStatus struct {
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GPUCount int `json:"gpu_count"`
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GPUType string `json:"gpu_type"`
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ConfiguredVendor string `json:"configured_vendor"`
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DetectionMethod string `json:"detection_method"`
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EnvOverrideType string `json:"env_override_type,omitempty"`
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EnvOverrideCount int `json:"env_override_count,omitempty"`
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BuildTags map[string]bool `json:"build_tags"`
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NativeAvailable bool `json:"native_available"`
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Extra map[string]interface{} `json:"extra,omitempty"`
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GPUCount int `json:"gpu_count"`
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GPUType string `json:"gpu_type"`
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ConfiguredVendor string `json:"configured_vendor"`
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DetectionMethod string `json:"detection_method"`
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EnvOverrideType string `json:"env_override_type,omitempty"`
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EnvOverrideCount int `json:"env_override_count,omitempty"`
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BuildTags map[string]bool `json:"build_tags"`
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NativeAvailable bool `json:"native_available"`
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Extra map[string]any `json:"extra,omitempty"`
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}
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// detectBuildTags returns which build tags are active
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Loading…
Reference in a new issue