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import os |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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ID_POOL = () |
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URL = "https://huggingface.co/datasets/thewall/DeepBindWeight/resolve/main" |
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class DeepBindWeightConfig(datasets.BuilderConfig): |
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pass |
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class DeepBindWeight(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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DeepBindWeightConfig(name=key) for key in ID_POOL |
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] |
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DEFAULT_CONFIG_NAME = "params" |
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def _info(self): |
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return datasets.DatasetInfo( |
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features=datasets.Features( |
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{ |
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"config": datasets.Value("string"), |
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"existed": datasets.Value("bool"), |
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"selex": datasets.Value("string"), |
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"tf": datasets.Value("string") |
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} |
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), |
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homepage="http://tools.genes.toronto.edu/deepbind", |
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) |
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def _split_generators(self, dl_manager): |
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param_url = f"{URL}/params.tar.gz" |
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selex_url = f"{URL}/ERP001824-deepbind.xlsx" |
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tf_url = f"{URL}/ERP001824-UniprotKB.xlsx" |
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aptani2_url = f"{URL}/aptani2_config.tar.gz" |
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downloaded_files = [os.path.join(f"{dl_manager.download_and_extract(param_url)}", "params")] |
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downloaded_files.extend(dl_manager.download([selex_url, tf_url])) |
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downloaded_files.append(f"{dl_manager.download_and_extract(aptani2_url)}") |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files}), |
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] |
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def _generate_examples(self, filepath): |
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"""This function returns the examples in the raw (text) form.""" |
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logger.info("generating examples from = %s", filepath) |
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flag = True |
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for file in filepath: |
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flag = flag and os.path.exists(file) |
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yield 0, {"config": filepath[0], |
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"existed": flag, |
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"selex": filepath[1], |
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'tf': filepath[2]} |
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if __name__=="__main__": |
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from datasets import load_dataset |
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dataset = load_dataset("thewall/deepbindweight", split="all") |
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