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import random
import gradio as gr
from optimum_benchmark.task_utils import (
TASKS_TO_AUTOMODELS,
infer_task_from_model_name_or_path,
)
from run import run_benchmark
from configs import (
get_training_config,
get_inference_config,
get_neural_compressor_config,
get_onnxruntime_config,
get_openvino_config,
get_pytorch_config,
)
BACKENDS = ["pytorch", "onnxruntime", "openvino", "neural-compressor"]
BENCHMARKS = ["inference", "training"]
with gr.Blocks() as demo:
# title text
gr.HTML("<h1 style='text-align: center'>🤗 Optimum Benchmark UI 🏋️</h1>")
# explanation text
gr.Markdown("This is a demo space of [Optimum-Benchmark](https://github.com/huggingface/optimum-benchmark.git).")
model = gr.Textbox(
label="model",
value="bert-base-uncased",
)
task = gr.Dropdown(
label="task",
value="text-classification",
choices=list(TASKS_TO_AUTOMODELS.keys()),
)
device = gr.Dropdown(
value="cpu",
label="device",
choices=["cpu", "cuda"],
)
experiment = gr.Textbox(
label="experiment_name",
value=f"experiment_{random.getrandbits(16)}",
)
model.submit(fn=infer_task_from_model_name_or_path, inputs=model, outputs=task)
with gr.Row():
with gr.Column():
with gr.Row():
backend = gr.Dropdown(
label="backend",
choices=BACKENDS,
value=BACKENDS[0],
)
with gr.Row() as backend_configs:
with gr.Accordion(label="Pytorch Config", open=False, visible=True):
pytorch_config = get_pytorch_config()
with gr.Accordion(label="OnnxRunTime Config", open=False, visible=False):
onnxruntime_config = get_onnxruntime_config()
with gr.Accordion(label="OpenVINO Config", open=False, visible=False):
openvino_config = get_openvino_config()
with gr.Accordion(label="Neural Compressor Config", open=False, visible=False):
neural_compressor_config = get_neural_compressor_config()
# hide backend configs based on backend
backend.change(
inputs=backend,
outputs=backend_configs.children,
fn=lambda value: [gr.update(visible=value == key) for key in BACKENDS],
)
with gr.Column():
with gr.Row():
benchmark = gr.Dropdown(
label="benchmark",
choices=BENCHMARKS,
value=BENCHMARKS[0],
)
with gr.Row() as benchmark_configs:
with gr.Accordion(label="Inference Config", open=False, visible=True):
inference_config = get_inference_config()
with gr.Accordion(label="Training Config", open=False, visible=False):
training_config = get_training_config()
# hide benchmark configs based on benchmark
benchmark.change(
inputs=benchmark,
outputs=benchmark_configs.children,
fn=lambda value: [gr.update(visible=value == key) for key in BENCHMARKS],
)
button = gr.Button(value="Run Benchmark", variant="primary")
with gr.Accordion(label="LOGS", open=True, visible=False):
output = gr.HTML()
button.click(
fn=run_benchmark,
inputs={
experiment,
model,
task,
device,
backend,
benchmark,
*pytorch_config,
*openvino_config,
*onnxruntime_config,
*neural_compressor_config,
*inference_config,
*training_config,
},
outputs=output,
queue=True,
)
button.click(
inputs=[],
outputs=output.parent,
fn=lambda: gr.update(visible=True),
)
demo.queue().launch()
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