# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import paddle def create_dataloader(dataset, mode="train", batch_size=1, batchify_fn=None, trans_fn=None): if trans_fn: dataset = dataset.map(trans_fn) shuffle = True if mode == "train" else False if mode == "train": batch_sampler = paddle.io.DistributedBatchSampler(dataset, batch_size=batch_size, shuffle=shuffle) else: batch_sampler = paddle.io.BatchSampler(dataset, batch_size=batch_size, shuffle=shuffle) return paddle.io.DataLoader(dataset=dataset, batch_sampler=batch_sampler, collate_fn=batchify_fn, return_list=True) def read_text_pair(data_path): """Reads data.""" with open(data_path, "r", encoding="utf-8") as f: for line in f: data = line.rstrip().split("\t") if len(data) != 2: continue yield {"query": data[0], "title": data[1]} def convert_example(example, tokenizer, max_seq_length=512, phase="train"): query, title = example["query"], example["title"] query_encoded_inputs = tokenizer(text=query, max_seq_len=max_seq_length) query_input_ids = query_encoded_inputs["input_ids"] query_token_type_ids = query_encoded_inputs["token_type_ids"] title_encoded_inputs = tokenizer(text=title, max_seq_len=max_seq_length) title_input_ids = title_encoded_inputs["input_ids"] title_token_type_ids = title_encoded_inputs["token_type_ids"] return query_input_ids, query_token_type_ids, title_input_ids, title_token_type_ids