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import subprocess
import gradio as gr
import pandas as pd
from ansi2html import Ansi2HTMLConverter
ansi2html_converter = Ansi2HTMLConverter(inline=True)
def run_benchmark(kwargs):
for key, value in kwargs.copy().items():
if key.label == "experiment_name":
experiment_name = value
kwargs.pop(key)
elif key.label == "model":
model = value
kwargs.pop(key)
elif key.label == "task":
task = value
kwargs.pop(key)
elif key.label == "device":
device = value
kwargs.pop(key)
elif key.label == "backend":
backend = value
kwargs.pop(key)
elif key.label == "benchmark":
benchmark = value
kwargs.pop(key)
else:
continue
arguments = [
"optimum-benchmark",
"--config-dir",
"./",
"--config-name",
"base_config",
f"task={task}",
f"model={model}",
f"device={device}",
f"backend={backend}",
f"benchmark={benchmark}",
f"experiment_name={experiment_name}",
]
for component, value in kwargs.items():
if f"{backend}." in component.label or f"{benchmark}." in component.label:
label = component.label.replace(f"{backend}.", "backend.").replace(f"{benchmark}.", "benchmark.")
if isinstance(component, gr.Dataframe):
for sub_key, sub_value in zip(component.headers, value[0]):
arguments.append(f"++{label}.{sub_key}={sub_value}")
else:
arguments.append(f"{label}={value}")
command = " ".join(arguments)
yield gr.update(value=command), gr.update(interactive=False), gr.update(visible=False)
# stream subprocess output
process = subprocess.Popen(
arguments,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
universal_newlines=True,
)
ansi_text = ""
for ansi_line in iter(process.stdout.readline, ""):
# stream process output to stdout
print(ansi_line, end="")
# skip torch.distributed.nn.jit.instantiator messages
if "torch.distributed.nn.jit.instantiator" in ansi_line:
continue
# if the last message is a download message (contains "Downloading ") then remove it and replace it with a new one
if "Downloading " in ansi_text and "Downloading " in ansi_line:
ansi_text = ansi_text.split("\n")[:-2]
print(ansi_text)
ansi_text.append(ansi_line)
ansi_text = "\n".join(ansi_text)
else:
# append line to ansi text
ansi_text += ansi_line
# convert ansi to html
html_text = ansi2html_converter.convert(ansi_text)
# stream html output to gradio
yield gr.update(value=html_text), gr.update(interactive=False), gr.update(visible=False)
# read runs/{experiment_name}/{benchmark}_results.csv
table = pd.read_csv(f"runs/{experiment_name}/{benchmark}_results.csv", index_col=0)
print(table.to_dict("records"))
yield gr.update(value=html_text), gr.update(interactive=True), gr.Dataframe.update(
visible=True, value={"headers": list(table.columns), "data": table.values.tolist()}
)
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