zulifeng
375d439abb
- gpu_specs: 新增 H20/H20-3e (中国合规版 H200) 规格定义，并修复 GPU 名称匹配顺序，避免 "H200" 被 "H20" 子串误匹配 - benchmark(compute): 引入 L2 cache 规避的 matrix pool 轮换 + 可选 torch.compile(max-autotune)，FP8 增加 _scaled_mm 探测， 显著提升 FP16/BF16/FP8 实测吞吐准确性 - benchmark(memory): nvbandwidth 增加 --disableAffinity 规避 fabricmanager NVML 不兼容；全 0 结果时自动回退到 PyTorch； D2D 平均值排除对角线零值 - nccl: 各通信操作 (AllReduce/AllToAll/Broadcast 等) 使用独立 带宽阈值比例，避免 AllToAll 误报 WARN - rdma: 仅按 link_layer=InfiniBand 过滤端口，无 IB 硬件或全 DOWN 时直接 SKIP 而非报错 - stress: 计算矩阵尺寸封顶 4096，并改为先并发派发再统一同步， 修复 8 卡串行执行导致 duration 严重超时的问题 - report: 兼容 RDMA SKIP 状态与 PyTorch 回退场景的 Memory 判定， 避免回退结果被误判为 FAIL - config: 新增 benchmark.compute.use_compile 开关 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
512 lines
24 KiB
Python
512 lines
24 KiB
Python
"""Report generation module - export test results to JSON/HTML/Markdown."""
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import json
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import os
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from datetime import datetime
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from pathlib import Path
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from typing import Optional
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try:
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from importlib.metadata import version as _pkg_version
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__version__ = _pkg_version("gpu-server-test-suite")
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except Exception:
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__version__ = "0.2.0"
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from rich.console import Console
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from rich.panel import Panel
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HTML_TEMPLATE = """<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>GPU Test Report - {timestamp}</title>
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<style>
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* {{ margin: 0; padding: 0; box-sizing: border-box; }}
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body {{ font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, monospace;
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background: #0d1117; color: #c9d1d9; padding: 2rem; }}
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.header {{ background: linear-gradient(135deg, #1a1a2e, #16213e);
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padding: 2rem; border-radius: 8px; margin-bottom: 2rem;
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border: 1px solid #30363d; }}
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.header h1 {{ color: #58a6ff; font-size: 1.5rem; }}
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.header .meta {{ color: #8b949e; margin-top: 0.5rem; }}
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.section {{ background: #161b22; border: 1px solid #30363d;
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border-radius: 8px; padding: 1.5rem; margin-bottom: 1.5rem; }}
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.section h2 {{ color: #58a6ff; margin-bottom: 1rem; font-size: 1.2rem;
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border-bottom: 1px solid #30363d; padding-bottom: 0.5rem; }}
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table {{ width: 100%; border-collapse: collapse; margin: 0.5rem 0; }}
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th {{ background: #21262d; color: #8b949e; text-align: left;
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padding: 0.5rem; font-weight: 600; font-size: 0.85rem; }}
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td {{ padding: 0.5rem; border-bottom: 1px solid #21262d; font-size: 0.9rem; }}
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.pass {{ color: #3fb950; }} .warn {{ color: #d29922; }} .fail {{ color: #f85149; }}
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.metric {{ display: inline-block; background: #21262d; padding: 0.75rem 1.5rem;
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border-radius: 6px; margin: 0.25rem; text-align: center; min-width: 120px; }}
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.metric .value {{ font-size: 1.3rem; font-weight: bold; color: #58a6ff; }}
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.metric .label {{ font-size: 0.75rem; color: #8b949e; margin-top: 0.25rem; }}
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.verdict {{ padding: 1rem; border-radius: 6px; text-align: center; font-size: 1.1rem;
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font-weight: bold; margin: 1rem 0; }}
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.verdict.pass {{ background: #0d2818; color: #3fb950; border: 1px solid #238636; }}
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.verdict.fail {{ background: #2d0b0b; color: #f85149; border: 1px solid #da3633; }}
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</style>
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</head>
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<body>
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<div class="header">
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<h1>GPU Training Server Test Report</h1>
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<div class="meta">Generated: {timestamp} | Server: {hostname}</div>
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</div>
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{content}
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</body>
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</html>"""
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class ReportGenerator:
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def __init__(self, config: dict):
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self.config = config
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self.console = Console()
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self.report_cfg = config.get("report", {})
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def generate(self, results: dict, fmt: str = None, output: str = None) -> str:
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fmt = fmt or self.report_cfg.get("format", "json")
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output_dir = self.report_cfg.get("output_dir", "./reports")
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os.makedirs(output_dir, exist_ok=True)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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if not output:
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output = os.path.join(output_dir, f"gpu_report_{timestamp}.{fmt}")
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if fmt == "json":
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return self._generate_json(results, output)
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elif fmt == "html":
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return self._generate_html(results, output)
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elif fmt == "md":
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return self._generate_markdown(results, output)
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else:
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self.console.print(f"[red]Unsupported format: {fmt}[/red]")
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return ""
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def _generate_json(self, results: dict, output: str) -> str:
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with open(output, "w") as f:
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json.dump(results, f, indent=2, default=str)
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self.console.print(f"[green]JSON report saved to: {output}[/green]")
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return output
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def _generate_html(self, results: dict, output: str) -> str:
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import socket
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hostname = socket.gethostname()
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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sections = []
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if "gpu_info" in results:
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gpus = results["gpu_info"].get("gpus", [])
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rows = ""
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for g in gpus:
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rows += f"<tr><td>GPU {g['index']}</td><td>{g['name']}</td>"
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rows += f"<td>{g['vram_total_mb']} MB</td>"
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rows += f"<td>{g['temperature']}°C</td>"
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rows += f"<td>{g['clock_sm']} MHz</td></tr>"
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sections.append(
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f'<div class="section"><h2>GPU Information</h2>'
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f'<p>Driver: {results["gpu_info"].get("driver_version", "N/A")} | '
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f'CUDA: {results["gpu_info"].get("cuda_version", "N/A")} | '
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f'Count: {len(gpus)}</p>'
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f'<table><tr><th>GPU</th><th>Model</th><th>VRAM</th><th>Temp</th><th>SM Clock</th></tr>'
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f'{rows}</table></div>'
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)
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if "health" in results:
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h = results["health"]
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passed = h.get("passed", False)
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cls = "pass" if passed else "fail"
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txt = "ALL PASSED" if passed else "SOME CHECKS FAILED"
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sections.append(f'<div class="verdict {cls}">{txt}</div>')
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if "benchmark" in results and "memory" in results["benchmark"]:
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mem = results["benchmark"]["memory"]
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sections.append(
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f'<div class="section"><h2>Memory Bandwidth</h2>'
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f'<div class="metric"><div class="value">{mem.get("d2d_bandwidth_gbps", "N/A")} GB/s</div>'
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f'<div class="label">D2D (HBM)</div></div>'
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f'<div class="metric"><div class="value">{mem.get("efficiency_pct", "N/A")}%</div>'
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f'<div class="label">Efficiency vs Peak ({mem.get("peak_bandwidth_gbps", "N/A")} GB/s)</div></div>'
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f'</div>'
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)
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if "benchmark" in results and "compute" in results["benchmark"]:
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comp = results["benchmark"]["compute"]
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dtype_rows = ""
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per_dtype = comp.get("per_dtype_tflops", {})
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eff = comp.get("efficiency_pct", {})
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for dt, tflops in per_dtype.items():
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ef = eff.get(dt, 0)
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cls = "pass" if ef >= 80 else ("warn" if ef >= 50 else "fail")
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if isinstance(tflops, (int, float)):
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dtype_rows += f'<tr><td>{dt.upper()}</td><td>{tflops:.1f} TFLOPS</td>'
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dtype_rows += f'<td class="{cls}">{ef:.1f}%</td></tr>'
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if dtype_rows:
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sections.append(
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f'<div class="section"><h2>Compute Throughput</h2>'
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f'<table><tr><th>DType</th><th>Achieved</th><th>Efficiency</th></tr>'
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f'{dtype_rows}</table></div>'
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)
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if "training" in results:
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t = results["training"]
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sections.append(
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f'<div class="section"><h2>Training Simulation</h2>'
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f'<div class="metric"><div class="value">{t.get("throughput_tokens_per_sec", "N/A")}</div>'
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f'<div class="label">Tokens/sec</div></div>'
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f'<div class="metric"><div class="value">{t.get("avg_step_time_ms", "N/A")} ms</div>'
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f'<div class="label">Avg Step Time</div></div>'
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f'<div class="metric"><div class="value">{t.get("peak_memory_gb", "N/A")} GB</div>'
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f'<div class="label">Peak Memory</div></div>'
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f'</div>'
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)
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content = "\n".join(sections)
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html = HTML_TEMPLATE.format(timestamp=timestamp, hostname=hostname, content=content)
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with open(output, "w") as f:
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f.write(html)
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self.console.print(f"[green]HTML report saved to: {output}[/green]")
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return output
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# ------------------------------------------------------------------
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# Markdown report
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# ------------------------------------------------------------------
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def _generate_markdown(self, results: dict, output: str) -> str:
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import socket
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hostname = socket.gethostname()
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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lines: list[str] = []
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# --- Header ---
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lines.append("# GPU Test Report\n")
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lines.append(f"- **Date:** {timestamp}")
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lines.append(f"- **Host:** {hostname}")
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# Extract GPU info for header
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gpu_info = results.get("gpu_info")
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if gpu_info and not gpu_info.get("error"):
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gpus = gpu_info.get("gpus", [])
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gpu_name = gpus[0]["name"] if gpus else "Unknown"
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lines.append(f"- **GPU:** {gpu_name} x{gpu_info.get('gpu_count', len(gpus))}")
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lines.append(f"- **Driver:** {gpu_info.get('driver_version', 'N/A')} | "
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f"**CUDA:** {gpu_info.get('cuda_version', 'N/A')}")
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lines.append("")
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# --- Summary table ---
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summary_items = self._build_summary(results)
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if summary_items:
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lines.append("## Summary\n")
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lines.append("| Test | Result |")
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lines.append("|------|--------|")
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for name, verdict in summary_items:
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lines.append(f"| {name} | {verdict} |")
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lines.append("")
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# --- GPU Information ---
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if gpu_info and not gpu_info.get("error"):
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lines.append("## GPU Information\n")
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gpus = gpu_info.get("gpus", [])
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lines.append("| GPU | Model | VRAM | Temp | Power | SM Clock |")
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lines.append("|-----|-------|------|------|-------|----------|")
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for g in gpus:
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vram = f"{g.get('vram_total_mb', 0)} MB"
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temp = f"{g.get('temperature', 'N/A')}C"
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power = f"{g.get('power_draw', 0):.0f}/{g.get('power_limit', 0):.0f}W"
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clock = f"{g.get('clock_sm', 0)} MHz"
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lines.append(f"| {g['index']} | {g['name']} | {vram} | {temp} | {power} | {clock} |")
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lines.append("")
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# --- Health Check ---
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health = results.get("health")
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if health and not health.get("error"):
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lines.append("## Health Check\n")
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passed = health.get("passed", False)
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lines.append(f"**Overall: {'PASS' if passed else 'FAIL'}**\n")
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gpu_health = health.get("gpu_health", [])
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if gpu_health:
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lines.append("| GPU | Temp | Power | ECC | PCIe | Throttle | Status |")
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lines.append("|-----|------|-------|-----|------|----------|--------|")
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for gh in gpu_health:
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checks = gh.get("checks", {})
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temp_c = checks.get("temperature", {})
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pwr = checks.get("power", {})
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ecc = checks.get("ecc_errors", {})
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pcie = checks.get("pcie_link", {})
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throttle = checks.get("throttling", {})
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temp_str = f"{temp_c.get('value', '?')}C {temp_c.get('status', '')}"
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pwr_str = f"{pwr.get('value', 0):.0f}W {pwr.get('status', '')}"
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ecc_str = f"S:{ecc.get('single', 0)} D:{ecc.get('double', 0)}"
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pcie_str = f"Gen{pcie.get('gen', '?')}x{pcie.get('width', '?')}"
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throt_str = throttle.get("status", "?")
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status = gh.get("status", "?")
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lines.append(f"| {gh['index']} | {temp_str} | {pwr_str} | "
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f"{ecc_str} | {pcie_str} | {throt_str} | **{status}** |")
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lines.append("")
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# --- Memory Bandwidth ---
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mem_data = self._extract_memory_results(results)
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if mem_data and not mem_data.get("error"):
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lines.append("## Memory Bandwidth\n")
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lines.append(f"Source: {mem_data.get('source', 'unknown')}\n")
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lines.append("| Metric | Value | Peak | Efficiency |")
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lines.append("|--------|-------|------|------------|")
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d2d = mem_data.get("d2d_bandwidth_gbps") or 0
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h2d = mem_data.get("h2d_bandwidth_gbps") or 0
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d2h = mem_data.get("d2h_bandwidth_gbps") or 0
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# New format with per-metric peaks
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h2d_peak = mem_data.get("h2d_peak_gbps") or 0
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d2h_peak = mem_data.get("d2h_peak_gbps") or 0
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d2d_peak = mem_data.get("d2d_peak_gbps") or 0
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h2d_eff = mem_data.get("h2d_efficiency_pct") or 0
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d2h_eff = mem_data.get("d2h_efficiency_pct") or 0
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d2d_eff = mem_data.get("d2d_efficiency_pct") or 0
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# Fallback for old format
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if not d2d_peak:
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d2d_peak = mem_data.get("peak_bandwidth_gbps") or 0
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d2d_eff = mem_data.get("efficiency_pct") or 0
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lines.append(f"| H2D (PCIe) | {h2d:.1f} GB/s | {h2d_peak:.0f} GB/s | {h2d_eff:.1f}% |")
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lines.append(f"| D2H (PCIe) | {d2h:.1f} GB/s | {d2h_peak:.0f} GB/s | {d2h_eff:.1f}% |")
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lines.append(f"| D2D (NVLink) | {d2d:.1f} GB/s | {d2d_peak:.0f} GB/s | {d2d_eff:.1f}% |")
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lines.append("")
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# PyTorch fallback can't accurately measure HBM peak (intra-GPU copy_()
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# only reaches ~20% of HBM bandwidth). When fallback is used, report
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# the number but mark as WARN with a note instead of evaluating as FAIL.
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if mem_data.get("source") == "pytorch":
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lines.append(
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f"**Verdict: WARN** (D2D {d2d:.1f} GB/s via PyTorch fallback; "
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"nvbandwidth unavailable — figure is indicative only, not a true HBM peak)\n"
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)
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else:
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verdict = "PASS" if d2d_eff >= 50 else ("WARN" if d2d_eff >= 30 else "FAIL")
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lines.append(f"**Verdict: {verdict}** (D2D efficiency {d2d_eff:.1f}%)\n")
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# --- Compute Throughput ---
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comp_data = self._extract_compute_results(results)
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if comp_data and not comp_data.get("error"):
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lines.append("## Compute Throughput\n")
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per_dtype = comp_data.get("per_dtype_tflops", {})
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peak_tflops = comp_data.get("peak_tflops", {})
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eff_pct = comp_data.get("efficiency_pct", {})
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lines.append("| DType | Achieved (TFLOPS) | Peak | Efficiency | Status |")
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lines.append("|-------|-------------------|------|------------|--------|")
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worst_eff = 100.0
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for dt, val in per_dtype.items():
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if isinstance(val, str):
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# skipped or error
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lines.append(f"| {dt.upper()} | {val} | - | N/A | SKIP |")
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else:
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pk = peak_tflops.get(dt, 0)
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ef = eff_pct.get(dt, 0)
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if isinstance(ef, (int, float)) and ef > 0:
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worst_eff = min(worst_eff, ef)
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status = "PASS" if ef >= 80 else ("WARN" if ef >= 50 else "FAIL")
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lines.append(f"| {dt.upper()} | {val:.1f} | {pk:.0f} | {ef:.1f}% | {status} |")
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lines.append("")
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overall = "PASS" if worst_eff >= 80 else ("WARN" if worst_eff >= 50 else "FAIL")
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lines.append(f"**Verdict: {overall}** (worst efficiency {worst_eff:.1f}%)\n")
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# --- NCCL ---
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nccl = results.get("nccl")
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if nccl and not nccl.get("error"):
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lines.append("## NCCL Multi-GPU\n")
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lines.append(f"Source: {nccl.get('source', 'unknown')} | "
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f"GPUs: {nccl.get('gpu_count', '?')}\n")
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tests = nccl.get("tests", {})
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if tests:
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lines.append("| Operation | Bus BW (GB/s) | Threshold | Status |")
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lines.append("|-----------|---------------|-----------|--------|")
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for op, data in tests.items():
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if isinstance(data, dict) and not data.get("error"):
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bw = data.get("best_busbw_gbps", 0)
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req = data.get("min_required_gbps", 0)
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status = data.get("status", "?")
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lines.append(f"| {op} | {bw:.1f} | >= {req:.0f} | {status} |")
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elif isinstance(data, dict) and data.get("error"):
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lines.append(f"| {op} | - | - | ERROR: {data['error']} |")
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lines.append("")
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passed = nccl.get("passed", False)
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lines.append(f"**Overall: {'PASS' if passed else 'FAIL'}**\n")
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# --- Stress Test ---
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stress = results.get("stress")
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if stress and not stress.get("error"):
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lines.append("## Stress Test\n")
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passed = stress.get("passed", False)
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duration = stress.get("duration_sec") or 0
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elapsed = stress.get("elapsed_sec") or 0
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source = stress.get("source", "unknown")
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lines.append(f"- **Source:** {source}")
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lines.append(f"- **Duration:** {elapsed:.0f}s (requested {duration}s)")
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lines.append(f"- **Result: {'PASS' if passed else 'FAIL'}**")
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lines.append("")
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# --- RDMA ---
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rdma = results.get("rdma")
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if rdma and (rdma.get("skipped") or rdma.get("status") == "SKIP"):
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lines.append("## RDMA/InfiniBand\n")
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lines.append(f"**Overall: SKIP** [{rdma.get('reason', 'no IB hardware detected')}]\n")
|
|
elif rdma and not rdma.get("error"):
|
|
lines.append("## RDMA/InfiniBand\n")
|
|
bw_tests = rdma.get("bandwidth_tests", [])
|
|
lat_tests = rdma.get("latency_tests", [])
|
|
if bw_tests or lat_tests:
|
|
lines.append("| Test | Value | Threshold | Status |")
|
|
lines.append("|------|-------|-----------|--------|")
|
|
for bt in bw_tests:
|
|
if not bt.get("error"):
|
|
lines.append(f"| {bt['test']} | {bt.get('bandwidth_gbps', 0):.1f} GB/s | "
|
|
f">= {bt.get('min_required_gbps', 0)} GB/s | {bt.get('status', '?')} |")
|
|
for lt in lat_tests:
|
|
if not lt.get("error"):
|
|
lines.append(f"| {lt['test']} | {lt.get('latency_us', 0):.2f} us | "
|
|
f"<= {lt.get('max_allowed_us', 0)} us | {lt.get('status', '?')} |")
|
|
lines.append("")
|
|
passed = rdma.get("passed", False)
|
|
lines.append(f"**Overall: {'PASS' if passed else 'FAIL'}**\n")
|
|
|
|
# --- Training ---
|
|
training = results.get("training")
|
|
if training and not training.get("error"):
|
|
lines.append("## Training Simulation\n")
|
|
lines.append("| Metric | Value |")
|
|
lines.append("|--------|-------|")
|
|
lines.append(f"| Model | {training.get('model', 'N/A')} |")
|
|
lines.append(f"| Params | {training.get('total_params_m', 0):.1f}M |")
|
|
lines.append(f"| Throughput | {training.get('throughput_tokens_per_sec', 0):.0f} tokens/sec |")
|
|
lines.append(f"| Avg Step Time | {training.get('avg_step_time_ms', 0):.1f} ms |")
|
|
lines.append(f"| Peak Memory | {training.get('peak_memory_gb', 0):.1f} GB |")
|
|
lines.append(f"| Final Loss | {training.get('final_loss', 'N/A')} |")
|
|
lines.append("")
|
|
|
|
# --- Footer ---
|
|
lines.append("---")
|
|
lines.append(f"*Generated by GPU Test Suite v{__version__}*")
|
|
|
|
content = "\n".join(lines)
|
|
with open(output, "w") as f:
|
|
f.write(content)
|
|
self.console.print(f"[green]Markdown report saved to: {output}[/green]")
|
|
return output
|
|
|
|
def _extract_memory_results(self, results: dict) -> dict:
|
|
"""Extract memory benchmark data from either full-suite or single-test format."""
|
|
if "memory_bench" in results:
|
|
data = results["memory_bench"]
|
|
return data.get("memory", data) if isinstance(data, dict) else {}
|
|
if "benchmark" in results:
|
|
bench = results["benchmark"]
|
|
if isinstance(bench, dict) and "memory" in bench:
|
|
return bench["memory"]
|
|
return {}
|
|
|
|
def _extract_compute_results(self, results: dict) -> dict:
|
|
"""Extract compute benchmark data from either full-suite or single-test format."""
|
|
if "compute_bench" in results:
|
|
data = results["compute_bench"]
|
|
return data.get("compute", data) if isinstance(data, dict) else {}
|
|
if "benchmark" in results:
|
|
bench = results["benchmark"]
|
|
if isinstance(bench, dict) and "compute" in bench:
|
|
return bench["compute"]
|
|
return {}
|
|
|
|
def _build_summary(self, results: dict) -> list[tuple[str, str]]:
|
|
"""Build summary verdict list from results."""
|
|
items = []
|
|
|
|
# GPU Info
|
|
if "gpu_info" in results:
|
|
gi = results["gpu_info"]
|
|
if gi.get("error"):
|
|
items.append(("GPU Info", f"ERROR: {gi['error']}"))
|
|
else:
|
|
items.append(("GPU Info", f"PASS ({gi.get('gpu_count', '?')} GPUs detected)"))
|
|
|
|
# Health
|
|
if "health" in results:
|
|
h = results["health"]
|
|
if h.get("error"):
|
|
items.append(("Health Check", f"ERROR: {h['error']}"))
|
|
elif h.get("passed"):
|
|
items.append(("Health Check", "PASS"))
|
|
else:
|
|
items.append(("Health Check", "FAIL"))
|
|
|
|
# Memory Bandwidth
|
|
mem = self._extract_memory_results(results)
|
|
if mem:
|
|
if mem.get("error"):
|
|
items.append(("Memory Bandwidth", f"ERROR: {mem['error']}"))
|
|
elif mem.get("source") == "pytorch":
|
|
# PyTorch fallback can't reach HBM peak — report as WARN, not FAIL.
|
|
d2d = mem.get("d2d_bandwidth_gbps") or 0
|
|
items.append(("Memory Bandwidth", f"WARN ({d2d:.0f} GB/s via PyTorch fallback)"))
|
|
else:
|
|
eff = mem.get("efficiency_pct") or 0
|
|
verdict = "PASS" if eff >= 80 else ("WARN" if eff >= 50 else "FAIL")
|
|
items.append(("Memory Bandwidth", f"{verdict} ({eff:.1f}%)"))
|
|
|
|
# Compute
|
|
comp = self._extract_compute_results(results)
|
|
if comp:
|
|
if comp.get("error"):
|
|
items.append(("Compute Throughput", f"ERROR: {comp['error']}"))
|
|
else:
|
|
eff_pct = comp.get("efficiency_pct", {})
|
|
valid_effs = [v for v in eff_pct.values() if isinstance(v, (int, float)) and v > 0]
|
|
if valid_effs:
|
|
worst = min(valid_effs)
|
|
verdict = "PASS" if worst >= 80 else ("WARN" if worst >= 50 else "FAIL")
|
|
items.append(("Compute Throughput", f"{verdict} (worst {worst:.1f}%)"))
|
|
else:
|
|
items.append(("Compute Throughput", "N/A"))
|
|
|
|
# NCCL
|
|
if "nccl" in results:
|
|
n = results["nccl"]
|
|
if n.get("error"):
|
|
items.append(("NCCL", f"ERROR: {n['error']}"))
|
|
elif n.get("passed"):
|
|
items.append(("NCCL", "PASS"))
|
|
else:
|
|
items.append(("NCCL", "FAIL"))
|
|
|
|
# Stress
|
|
if "stress" in results:
|
|
s = results["stress"]
|
|
if s.get("error"):
|
|
items.append(("Stress Test", f"ERROR: {s['error']}"))
|
|
elif s.get("passed"):
|
|
items.append(("Stress Test", "PASS"))
|
|
else:
|
|
items.append(("Stress Test", "FAIL"))
|
|
|
|
# RDMA
|
|
if "rdma" in results:
|
|
r = results["rdma"]
|
|
if r.get("skipped") or r.get("status") == "SKIP":
|
|
items.append(("RDMA", f"SKIP ({r.get('reason', 'no IB hardware')})"))
|
|
elif r.get("error"):
|
|
items.append(("RDMA", f"ERROR: {r['error']}"))
|
|
elif r.get("passed"):
|
|
items.append(("RDMA", "PASS"))
|
|
else:
|
|
items.append(("RDMA", "FAIL"))
|
|
|
|
# Training
|
|
if "training" in results:
|
|
t = results["training"]
|
|
if t.get("error"):
|
|
items.append(("Training", f"ERROR: {t['error']}"))
|
|
else:
|
|
tps = t.get("throughput_tokens_per_sec", 0)
|
|
items.append(("Training", f"PASS ({tps:.0f} tokens/sec)"))
|
|
|
|
return items
|