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16 changes: 15 additions & 1 deletion dashboard.py
Original file line number Diff line number Diff line change
Expand Up @@ -351,6 +351,16 @@ def load_data(file_path, cache_key=None):
df["model"] = df["model"].str.strip()
df["version"] = df["version"].str.strip()
df["TP"] = pd.to_numeric(df["TP"], errors="coerce")

# Filter out rows with missing critical fields - these indicate data quality issues
initial_row_count = len(df)
df = df.dropna(subset=["accelerator", "model", "version"])
dropped_rows = initial_row_count - len(df)
if dropped_rows > 0:
logger.warning(
f"Dropped {dropped_rows} rows with missing accelerator/model/version"
)

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return df
except FileNotFoundError:
st.error(
Expand Down Expand Up @@ -10363,6 +10373,10 @@ def convert_epoch_to_date(row):
"dashboard_id": "d35f19c8f56250",
"dashboard_name": "vllm-2b-dcgm-metrics-psap-zeus-syd",
},
"B200_PIRATE": {
"dashboard_id": "b200-pirate-vllm-dcgm",
"dashboard_name": "vllm-2b-dcgm-metrics-b200-pirate",
},
}

_SGLANG_H200_DASHBOARD = {
Expand Down Expand Up @@ -11184,7 +11198,7 @@ def decode_filters_from_url():
all_accelerators = sorted(df["accelerator"].unique().tolist())
all_models = sorted(df["model"].unique().tolist())
all_versions = sorted(df["version"].unique().tolist())
all_profiles = sorted(df["profile"].unique().tolist())
all_profiles = sorted(df["profile"].dropna().astype(str).unique().tolist())
all_tp_sizes = sorted(df["TP"].dropna().unique().tolist())

url_accelerators = []
Expand Down
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