44 lines
1.7 KiB
Python
44 lines
1.7 KiB
Python
import pandas as pd
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from BPE import TokeNanoCore as Tokenizer
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class Batcher:
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def __init__(self, dataset_path: str, batch_size:int, tokenizer: Tokenizer) -> None:
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# ABSTRACT, TRIPLE
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# tasks:
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# rdf2text: X: TRIPLE, Y: ABSTRACT
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# text2rdf: X: ABSTRACT, X:TRIPLE
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# masking ( call masker): X: incomplete_triple Y: complete_triple (as exam)
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# completation: X: TRIPLE SUBSET, Y: related TRIPLE SUBSET
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# self._DATASET = pd.read_csv(dataset_path)
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self._dataset_path = dataset_path
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self._batch_size = batch_size
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self._tokenizer = tokenizer
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def get_batch(self):
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for batch in pd.read_csv(self._dataset_path, chunksize= int(self._batch_size/3)): #now we support 3 task
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# each batch get 4 transformation for the 4 tasks and then shuffled
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# now a batch is ["Abstract"], ["Triples"]
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# tokenize the strings:
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tokenized_batch
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tokenized_batch[["Abstract","Triples"]] = batch[["Abstract","Triples"]].map(lambda t: self._tokenizer.encode(t))
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# ??? i hope this works, later will be tested
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rdf2_txt_batch = self.__rdf2txt_transformation(tokenized_batch)
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def __rdf2txt_transformation(self, batch: pd.DataFrame):
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# rename ["Triples"] as ["X"]
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# rename ["Abstract"] as ["Y"]
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# return just them
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batch = batch.rename(columns={"Triples": "X", "Abstract": "Y"})
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return batch[["X", "Y"]] #.sample(frac=1).reset_index(drop=True)
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def __txt2rdf_transformation(self, batch: pd.DataFrame):
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batch = batch.rename(columns={ "Abstract": "X","Triples": "Y"})
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return batch[["X", "Y"]]# .sample(frac=1).reset_index(drop=True)
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def __masking() |