Spaces:
Sleeping
Sleeping
Commit
β’
7682345
1
Parent(s):
4d423a9
clean up
Browse files- app.py +20 -43
- config_store.py +0 -30
app.py
CHANGED
@@ -1,29 +1,27 @@
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import os
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import time
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import traceback
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import gradio as gr
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from huggingface_hub import create_repo, whoami
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from config_store import (
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get_process_config,
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get_inference_config,
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get_openvino_config,
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get_pytorch_config,
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)
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from optimum_benchmark.launchers.base import Launcher # noqa
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from optimum_benchmark.backends.openvino.utils import TASKS_TO_OVMODEL
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from optimum_benchmark.backends.transformers_utils import TASKS_TO_MODEL_LOADERS
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from optimum_benchmark import (
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BenchmarkConfig,
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PyTorchConfig,
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OVConfig,
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ProcessConfig,
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InferenceConfig,
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)
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from optimum_benchmark.logging_utils import setup_logging
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DEVICE = "cpu"
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LAUNCHER = "process"
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gr.LoginButton(min_width=250)
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# add image
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gr.
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"""<img src="https://huggingface.co/spaces/optimum/optimum-benchmark-ui/resolve/main/huggy_bench.png" style="display: block; margin-left: auto; margin-right: auto; width: 30%;">"""
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)
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# title text
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gr.Markdown(
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"<h1 style='text-align: center'>π€ Optimum-Benchmark Interface ποΈ</h1>"
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)
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# explanation text
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gr.HTML(
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"<h3 style='text-align: center'>"
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"Zero code Gradio interface of "
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"<a href='https://github.com/huggingface/optimum-benchmark.git'>"
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"Optimum-Benchmark"
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"</a>"
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"<br>"
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"</h3>"
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"<p style='text-align: center'>"
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"This Space uses Optimum
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"<br>"
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"
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)
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model = gr.Dropdown(
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inference_config = get_inference_config()
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with gr.Row() as backend_configs:
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with gr.Accordion(label="OpenVINO Config", open=False, visible=True):
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openvino_config = get_openvino_config()
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with gr.Accordion(label="PyTorch Config", open=False, visible=True):
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pytorch_config = get_pytorch_config()
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backends.change(
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inputs=backends,
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@@ -209,12 +190,10 @@ def build_demo():
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button = gr.Button(value="Run Benchmark", variant="primary")
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with gr.Row() as md_output:
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with gr.Accordion(label="OpenVINO Output", open=True, visible=True):
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openvino_output = gr.Markdown()
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with gr.Accordion(label="PyTorch Output", open=True, visible=True):
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pytorch_output = gr.Markdown()
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backends.change(
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inputs=backends,
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backends,
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*process_config.values(),
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*inference_config.values(),
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*openvino_config.values(),
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*pytorch_config.values(),
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},
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outputs={
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openvino_output,
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pytorch_output,
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},
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concurrency_limit=1,
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)
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import os
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import time
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import traceback
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+
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import gradio as gr
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from huggingface_hub import create_repo, whoami
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from optimum_benchmark.backends.openvino.utils import TASKS_TO_OVMODEL
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from optimum_benchmark.backends.transformers_utils import TASKS_TO_MODEL_LOADERS
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from optimum_benchmark import (
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Benchmark,
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BenchmarkConfig,
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ProcessConfig,
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InferenceConfig,
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PyTorchConfig,
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OVConfig,
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)
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from optimum_benchmark.logging_utils import setup_logging
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from .config_store import (
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get_process_config,
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get_inference_config,
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get_openvino_config,
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get_pytorch_config,
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)
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DEVICE = "cpu"
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LAUNCHER = "process"
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gr.LoginButton(min_width=250)
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# add image
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gr.HTML(
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"""<img src="https://huggingface.co/spaces/optimum/optimum-benchmark-ui/resolve/main/huggy_bench.png" style="display: block; margin-left: auto; margin-right: auto; width: 30%;">"""
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"<h1 style='text-align: center'>π€ Optimum-Benchmark Interface ποΈ</h1>"
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"<p style='text-align: center'>"
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"This Space uses <a href='https://github.com/huggingface/optimum-benchmark.git'>Optimum-Benchmark</a> to automatically benchmark a model from the Hub on different backends."
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"<br>The results (config and report) will be pushed under your namespace in a benchmark repository on the Hub."
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"</p>"
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)
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model = gr.Dropdown(
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inference_config = get_inference_config()
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with gr.Row() as backend_configs:
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with gr.Accordion(label="PyTorch Config", open=False, visible=True):
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pytorch_config = get_pytorch_config()
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with gr.Accordion(label="OpenVINO Config", open=False, visible=True):
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openvino_config = get_openvino_config()
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backends.change(
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inputs=backends,
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button = gr.Button(value="Run Benchmark", variant="primary")
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with gr.Row() as md_output:
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with gr.Accordion(label="PyTorch Output", open=True, visible=True):
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pytorch_output = gr.Markdown()
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with gr.Accordion(label="OpenVINO Output", open=True, visible=True):
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openvino_output = gr.Markdown()
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backends.change(
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inputs=backends,
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backends,
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*process_config.values(),
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*inference_config.values(),
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*pytorch_config.values(),
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*openvino_config.values(),
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},
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outputs={
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pytorch_output,
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openvino_output,
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},
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concurrency_limit=1,
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)
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config_store.py
CHANGED
@@ -71,32 +71,6 @@ def get_pytorch_config():
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}
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def get_onnxruntime_config():
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return {
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"onnxruntime.export": gr.Checkbox(
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value=True,
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label="onnxruntime.export",
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info="Exports the model to ONNX",
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),
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"onnxruntime.use_cache": gr.Checkbox(
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value=True,
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label="onnxruntime.use_cache",
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info="Uses cached ONNX model if available",
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),
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"onnxruntime.use_merged": gr.Checkbox(
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value=True,
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label="onnxruntime.use_merged",
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info="Uses merged ONNX model if available",
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),
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"onnxruntime.torch_dtype": gr.Dropdown(
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value="float32",
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label="onnxruntime.torch_dtype",
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choices=["bfloat16", "float16", "float32", "auto"],
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info="The dtype to use for the model",
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),
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}
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def get_openvino_config():
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return {
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"openvino.export": gr.Checkbox(
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info="Converts model to half precision",
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),
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}
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def get_ipex_config():
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return {}
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}
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def get_openvino_config():
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return {
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"openvino.export": gr.Checkbox(
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info="Converts model to half precision",
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),
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}
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