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Runtime error
| import evaluate | |
| from evaluate.utils import parse_readme, infer_gradio_input_types, json_to_string_type,parse_gradio_data | |
| import re | |
| import sys | |
| from pathlib import Path | |
| from evaluate.utils.logging import get_logger | |
| logger = get_logger(__name__) | |
| REGEX_YAML_BLOCK = re.compile(r"---[\n\r]+([\S\s]*?)[\n\r]+---[\n\r]") | |
| module = evaluate.load("JP-SystemsX/nDCG") | |
| def launch_gradio_widget(metric): | |
| """Launches `metric` widget with Gradio.""" | |
| try: | |
| import gradio as gr | |
| except ImportError as error: | |
| logger.error("To create a metric widget with Gradio make sure gradio is installed.") | |
| raise error | |
| local_path = Path(sys.path[0]) | |
| # if there are several input types, use first as default. | |
| if isinstance(metric.features, list): | |
| (feature_names, feature_types) = zip(*metric.features[0].items()) | |
| else: | |
| (feature_names, feature_types) = zip(*metric.features.items()) | |
| gradio_input_types = infer_gradio_input_types(feature_types) | |
| def compute(data): | |
| return metric.compute(**parse_gradio_data(data, gradio_input_types)) | |
| iface = gr.Interface( | |
| fn=compute, | |
| inputs=gr.inputs.Dataframe( | |
| headers=feature_names, | |
| col_count=len(feature_names), | |
| row_count=2, | |
| datatype=json_to_string_type(gradio_input_types), | |
| default=[['[1,2,3]','[1,2,3]'],['[1,1,0]','[0,1,1]']] | |
| ), | |
| outputs=gr.outputs.Textbox(label=metric.name), | |
| description=metric.info.description, | |
| title=f"Metric: {metric.name}", | |
| article=parse_readme(local_path / "README.md"), | |
| ) | |
| iface.launch() | |
| x = launch_gradio_widget(module) | |