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import gradio as gr
import datasets
theme = gr.themes.Soft(
primary_hue="green",
)
def check_dataset(dataset_id, dataset_config="default", dataset_split="test"):
try:
configs = datasets.get_dataset_config_names(dataset_id)
except Exception:
# Dataset may not exist
return None, dataset_config, dataset_split
if dataset_config not in configs:
# Need to choose dataset subset (config)
return dataset_id, configs, dataset_split
ds = datasets.load_dataset(dataset_id, dataset_config)
if isinstance(ds, datasets.DatasetDict):
# Need to choose dataset split
if dataset_split not in ds.keys():
return dataset_id, None, list(ds.keys())
elif not isinstance(ds, datasets.Dataset):
# Unknown type
return dataset_id, None, None
return dataset_id, dataset_config, dataset_split
def try_submit(dataset_id, dataset_config, dataset_split):
# Validate dataset
d_id, config, split = check_dataset(dataset_id=dataset_id, dataset_config=dataset_config, dataset_split=dataset_split)
if d_id is None:
gr.Warning(f'Dataset "{dataset_id}" is not accessible. Please set your HF_TOKEN if it is a private dataset.')
if isinstance(config, list):
gr.Warning(f'Dataset "{dataset_id}" does have "{dataset_config}" config. Please choose a valid config.')
config = gr.Dropdown.update(choices=config, value=config[0])
if isinstance(split, list):
gr.Warning(f'Dataset "{dataset_id}" does have "{dataset_split}" split. Please choose a valid split.')
split = gr.Dropdown.update(choices=split, value=split[0])
return config, split
with gr.Blocks(theme=theme) as iface:
with gr.Row():
with gr.Column():
model_id_input = gr.Textbox(
label="Hugging Face model id",
placeholder="cardiffnlp/twitter-roberta-base-sentiment-latest",
)
model_type = gr.Dropdown(
label="Hugging Face model type",
choices=[
("Auto-detect", 0),
("Text Classification", 1),
],
value=0,
)
with gr.Column():
dataset_id_input = gr.Textbox(
label="Hugging Face dataset id",
placeholder="tweet_eval",
)
dataset_config_input = gr.Dropdown(
label="Hugging Face dataset subset",
choices=[
"default",
],
allow_custom_value=True,
value="default",
)
dataset_split_input = gr.Dropdown(
label="Hugging Face dataset split",
choices=[
"test",
],
allow_custom_value=True,
value="test",
)
with gr.Row():
run_btn = gr.Button("Validate and submit", variant="primary")
run_btn.click(
try_submit,
inputs=[
dataset_id_input,
dataset_config_input,
dataset_split_input
],
outputs=[
dataset_config_input,
dataset_split_input
],
)
iface.queue(max_size=20)
iface.launch()
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