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#24 Update extra/dashboard/app.py: DataFrame component sorting improved #25

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#24 Update extra/dashboard/app.py: DataFrame component sorting improved #25

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29 changes: 26 additions & 3 deletions extra/dashboard/app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,11 +75,34 @@ def summary_table() -> pd.DataFrame:
['run_id', 'model', 'rate', 'inter_token_latency_ms_p90', 'time_to_first_token_ms_p90',
'e2e_latency_ms_p90',
'token_throughput_secs']]
for metric in ['inter_token_latency_ms_p90', 'time_to_first_token_ms_p90', 'e2e_latency_ms_p90',
'token_throughput_secs']:
data[metric] = data[metric].apply(lambda x: f"{x:.2f}")
data = data.rename(
columns=column_mappings)
# return data # uncomment this line if you want to return the raw DataFrame without rounding

# Ensure numeric columns are properly typed for sorting
numeric_cols_to_ensure = [
'ITL P90 (ms)', 'TTFT P90 (ms)', 'E2E P90 (ms)',
'Throughput (tokens/s)', 'QPS'
]

for col in numeric_cols_to_ensure:
if col in data.columns:
data[col] = pd.to_numeric(data[col], errors='coerce')

# Round numeric columns to reduce decimal places while maintaining sorting
# see https://github.com/huggingface/inference-benchmarker/issues/24
rounding_rules = {
'ITL P90 (ms)': 2,
'TTFT P90 (ms)': 2,
'E2E P90 (ms)': 2,
'Throughput (tokens/s)': 2,
'QPS': 0 # Round to integers
}

for col, decimals in rounding_rules.items():
if col in data.columns:
data[col] = data[col].round(decimals)

return data

def load_bench_results(source) -> pd.DataFrame:
Expand Down