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def filter_tags(row, filt, operator): | |
tags = row["tags"] | |
tags[:] = [d for d in tags if isinstance(d, str)] | |
if operator == "All": | |
if all(elem in tags for elem in filt): | |
return True | |
s1 = set(tags) | |
s2 = set(filt) | |
if operator == "Any": | |
if bool(s1 & s2): | |
return True | |
if operator == "None": | |
if len(s1.intersection(s2)) == 0: | |
return True | |
return False | |
def filter_pipeline_data(data, modality, pipeline, library,framework, tags, operator): | |
data = data[data['pipeline'].notna()] | |
if modality != "All": | |
data = data[data["modality"] == modality.lower()] | |
if pipeline != "all": | |
data = data[data["pipeline"] == pipeline] | |
if library != "all" and library != "not transformers": | |
data = data[data["library"] == library] | |
if library == "not transformers": | |
data = data[data["library"] != "transformers"] | |
if framework != "all": | |
print(framework) | |
data = data[data[framework] == 1] | |
if tags != []: | |
data = data[data.apply(filter_tags, axis=1, filt=tags, operator=operator)] | |
tags = data["tags"].explode() | |
tags = tags[tags.notna()].value_counts().rename_axis("tag").to_frame('counts').reset_index() | |
s = tags["tag"] | |
s = s[s.apply(type) == str] | |
return data, s.unique() |