mirror of
https://github.com/MacRimi/ProxMenux.git
synced 2025-11-18 11:36:17 +00:00
Update flask_server.py
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MacRimi
@@ -2236,6 +2236,7 @@ def get_detailed_gpu_info(gpu):
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print(f"[v0] Parsing fdinfo with {len(fdinfo)} entries", flush=True)
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# CHANGE: Corregir parseo de fdinfo con estructura anidada
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# fdinfo es un diccionario donde las claves son los PIDs (como strings)
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for pid_str, proc_data in fdinfo.items():
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try:
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@@ -2248,9 +2249,16 @@ def get_detailed_gpu_info(gpu):
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print(f"[v0] Processing fdinfo entry: PID={pid_str}, Name={process_info['name']}", flush=True)
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# Parse VRAM usage for this process
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if 'VRAM' in proc_data:
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vram_data = proc_data['VRAM']
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# La estructura real es: proc_data -> usage -> usage -> datos
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# Acceder al segundo nivel de 'usage'
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usage_outer = proc_data.get('usage', {})
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usage_data = usage_outer.get('usage', {})
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print(f"[v0] Usage data keys: {list(usage_data.keys())}", flush=True)
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# Parse VRAM usage for this process (está dentro de usage.usage)
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if 'VRAM' in usage_data:
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vram_data = usage_data['VRAM']
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if isinstance(vram_data, dict) and 'value' in vram_data:
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vram_mb = vram_data['value']
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process_info['memory'] = {
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@@ -2260,80 +2268,97 @@ def get_detailed_gpu_info(gpu):
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}
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print(f"[v0] VRAM: {vram_mb} MB", flush=True)
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# Parse GTT (Graphics Translation Table) usage
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if 'GTT' in proc_data:
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gtt_data = proc_data['GTT']
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# Parse GTT (Graphics Translation Table) usage (está dentro de usage.usage)
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if 'GTT' in usage_data:
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gtt_data = usage_data['GTT']
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if isinstance(gtt_data, dict) and 'value' in gtt_data:
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gtt_mb = gtt_data['value']
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# Add GTT to total memory if not already counted
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if 'total' not in process_info['memory']:
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process_info['memory']['total'] = int(gtt_mb * 1024 * 1024)
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else:
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# Add GTT to existing VRAM
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process_info['memory']['total'] += int(gtt_mb * 1024 * 1024)
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print(f"[v0] GTT: {gtt_mb} MB", flush=True)
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# Parse engine utilization for this process
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if 'usage' in proc_data:
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usage = proc_data['usage']
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print(f"[v0] Usage data: {usage}", flush=True)
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# GFX (Graphics/Render)
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if 'GFX' in usage:
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gfx_usage = usage['GFX']
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if isinstance(gfx_usage, dict) and 'value' in gfx_usage:
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val = gfx_usage['value']
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if val > 0:
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process_info['engines']['Render/3D'] = f"{val:.1f}%"
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print(f"[v0] GFX: {val}%", flush=True)
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# COMP (Compute)
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if 'COMP' in usage:
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comp_usage = usage['COMP']
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if isinstance(comp_usage, dict) and 'value' in comp_usage:
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val = comp_usage['value']
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if val > 0:
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process_info['engines']['Compute'] = f"{val:.1f}%"
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print(f"[v0] COMP: {val}%", flush=True)
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# DMA (Direct Memory Access)
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if 'DMA' in usage:
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dma_usage = usage['DMA']
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if isinstance(dma_usage, dict) and 'value' in dma_usage:
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val = dma_usage['value']
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if val > 0:
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process_info['engines']['DMA'] = f"{val:.1f}%"
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print(f"[v0] DMA: {val}%", flush=True)
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# DEC (Decode/Video)
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if 'DEC' in usage:
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dec_usage = usage['DEC']
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if isinstance(dec_usage, dict) and 'value' in dec_usage:
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val = dec_usage['value']
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if val > 0:
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process_info['engines']['Video'] = f"{val:.1f}%"
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print(f"[v0] DEC: {val}%", flush=True)
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# ENC (Encode)
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if 'ENC' in usage:
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enc_usage = usage['ENC']
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if isinstance(enc_usage, dict) and 'value' in enc_usage:
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val = enc_usage['value']
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if val > 0:
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process_info['engines']['VideoEncode'] = f"{val:.1f}%"
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print(f"[v0] ENC: {val}%", flush=True)
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# CPU (CPU usage by GPU driver)
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if 'CPU' in usage:
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cpu_usage = usage['CPU']
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if isinstance(cpu_usage, dict) and 'value' in cpu_usage:
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val = cpu_usage['value']
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if val > 0:
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process_info['engines']['CPU'] = f"{val:.1f}%"
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print(f"[v0] CPU: {val}%", flush=True)
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# Parse engine utilization for this process (están dentro de usage.usage)
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# GFX (Graphics/Render)
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if 'GFX' in usage_data:
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gfx_usage = usage_data['GFX']
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if isinstance(gfx_usage, dict) and 'value' in gfx_usage:
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val = gfx_usage['value']
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if val > 0:
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process_info['engines']['Render/3D'] = f"{val:.1f}%"
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print(f"[v0] GFX: {val}%", flush=True)
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# Compute
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if 'Compute' in usage_data:
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comp_usage = usage_data['Compute']
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if isinstance(comp_usage, dict) and 'value' in comp_usage:
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val = comp_usage['value']
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if val > 0:
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process_info['engines']['Compute'] = f"{val:.1f}%"
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print(f"[v0] Compute: {val}%", flush=True)
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# DMA (Direct Memory Access)
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if 'DMA' in usage_data:
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dma_usage = usage_data['DMA']
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if isinstance(dma_usage, dict) and 'value' in dma_usage:
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val = dma_usage['value']
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if val > 0:
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process_info['engines']['DMA'] = f"{val:.1f}%"
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print(f"[v0] DMA: {val}%", flush=True)
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# Decode (Video Decode)
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if 'Decode' in usage_data:
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dec_usage = usage_data['Decode']
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if isinstance(dec_usage, dict) and 'value' in dec_usage:
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val = dec_usage['value']
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if val > 0:
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process_info['engines']['Video'] = f"{val:.1f}%"
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print(f"[v0] Decode: {val}%", flush=True)
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# Encode (Video Encode)
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if 'Encode' in usage_data:
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enc_usage = usage_data['Encode']
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if isinstance(enc_usage, dict) and 'value' in enc_usage:
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val = enc_usage['value']
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if val > 0:
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process_info['engines']['VideoEncode'] = f"{val:.1f}%"
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print(f"[v0] Encode: {val}%", flush=True)
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# Media (Media Engine)
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if 'Media' in usage_data:
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media_usage = usage_data['Media']
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if isinstance(media_usage, dict) and 'value' in media_usage:
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val = media_usage['value']
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if val > 0:
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process_info['engines']['Media'] = f"{val:.1f}%"
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print(f"[v0] Media: {val}%", flush=True)
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# CPU (CPU usage by GPU driver)
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if 'CPU' in usage_data:
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cpu_usage = usage_data['CPU']
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if isinstance(cpu_usage, dict) and 'value' in cpu_usage:
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val = cpu_usage['value']
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if val > 0:
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process_info['engines']['CPU'] = f"{val:.1f}%"
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print(f"[v0] CPU: {val}%", flush=True)
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# VCN_JPEG (JPEG Decode)
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if 'VCN_JPEG' in usage_data:
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jpeg_usage = usage_data['VCN_JPEG']
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if isinstance(jpeg_usage, dict) and 'value' in jpeg_usage:
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val = jpeg_usage['value']
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if val > 0:
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process_info['engines']['JPEG'] = f"{val:.1f}%"
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print(f"[v0] VCN_JPEG: {val}%", flush=True)
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# Add the process even if it has no active engines at this moment
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# (may have allocated memory but is not actively using the GPU)
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if process_info['memory'] or process_info['engines']:
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processes.append(process_info)
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print(f"[v0] Added AMD GPU process: {process_info['name']} (PID: {process_info['pid']})", flush=True)
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print(f"[v0] Added AMD GPU process: {process_info['name']} (PID: {process_info['pid']}) - Memory: {process_info['memory']}, Engines: {process_info['engines']}", flush=True)
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else:
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print(f"[v0] Skipped process {process_info['name']} - no memory or engine usage", flush=True)
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