chore: import upstream snapshot with attribution

2026-07-13 12:38:16 +08:00
commit 94057c3d3e
7152 changed files with 2120455 additions and 0 deletions
@@ -0,0 +1,46 @@
+_PATTERN_DECODE = (
+    r"(\(\w+ pid=(?P<pid>\d+)(?:,\s*ip=(?P<ip>[\d\.]+))?\))?\s*"
+    r"\[(?P<time>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})"
+    r"(?:\s+DP(?P<dp_rank>\d+))?"
+    r"(?:\s+TP(?P<tp_rank>\d+))?"
+    r"(?:\s+EP(?P<ep_rank>\d+))?"
+    r"(?:\s+PP(?P<pp_rank>\d+))?"
+    r"\]\s+"
+    r"Decode batch( \[\d+\])?,\s+"
+    r"#running-req:\s*(?P<num_running_req>\d+),\s+"
+    r"#token:\s*(?P<num_token>\d+),\s+"
+    r"token usage:\s*(?P<token_usage>[0-9.]+),\s+"
+    r".*?"
+    r"gen throughput \(token/s\):\s*(?P<gen_throughput>[0-9.]+),\s+"
+    r"#queue-req:\s*(?P<queue_req>\d+),"
+)
+
+
+def parse(lines):
+    import polars as pl
+
+    df = pl.DataFrame(dict(line=lines.splitlines()))
+    df = df.with_columns(info=pl.col("line").str.extract_groups(_PATTERN_DECODE))
+    df = df.unnest("info")
+    df = df.filter(pl.col("gen_throughput").is_not_null())
+
+    df = df.with_columns(
+        pl.col("time").str.strptime(pl.Datetime, "%Y-%m-%d %H:%M:%S"),
+        *[
+            pl.col(col).cast(dtype)
+            for col, dtype in [
+                ("pid", pl.Int64),
+                ("dp_rank", pl.Int64),
+                ("tp_rank", pl.Int64),
+                ("ep_rank", pl.Int64),
+                ("pp_rank", pl.Int64),
+                ("num_running_req", pl.Int64),
+                ("num_token", pl.Int64),
+                ("token_usage", pl.Float64),
+                ("gen_throughput", pl.Float64),
+                ("queue_req", pl.Int64),
+            ]
+            if col in df.columns
+        ],
+    )
+    return df