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- #!/usr/bin/python
- # -*- coding: utf-8 -*-
-
- # __author__="Danqing Wang"
-
- #
- # 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 os
- import sys
-
- sys.path.append('/remote-home/dqwang/FastNLP/fastNLP_brxx/')
-
- from fastNLP.core.const import Const
-
- from data.dataloader import SummarizationLoader
- from tools.data import ExampleSet, Vocab
-
- vocab_size = 100000
- vocab_path = "test/testdata/vocab"
- sent_max_len = 100
- doc_max_timesteps = 50
-
- # paths = {"train": "test/testdata/train.jsonl", "valid": "test/testdata/val.jsonl"}
- paths = {"train": "/remote-home/dqwang/Datasets/CNNDM/train.label.jsonl", "valid": "/remote-home/dqwang/Datasets/CNNDM/val.label.jsonl"}
- sum_loader = SummarizationLoader()
- dataInfo = sum_loader.process(paths=paths, vocab_size=vocab_size, vocab_path=vocab_path, sent_max_len=sent_max_len, doc_max_timesteps=doc_max_timesteps, load_vocab_file=True)
- trainset = dataInfo.datasets["train"]
-
- vocab = Vocab(vocab_path, vocab_size)
- dataset = ExampleSet(paths["train"], vocab, doc_max_timesteps, sent_max_len)
-
- # print(trainset[0]["text"])
- # print(dataset.get_example(0).original_article_sents)
- # print(trainset[0]["words"])
- # print(dataset[0][0].numpy().tolist())
- b_size = len(trainset)
- for i in range(b_size):
- if i <= 7327:
- continue
- print(trainset[i][Const.INPUT])
- print(dataset[i][0].numpy().tolist())
- assert trainset[i][Const.INPUT] == dataset[i][0].numpy().tolist(), i
- assert trainset[i][Const.INPUT_LEN] == dataset[i][2].numpy().tolist(), i
- assert trainset[i][Const.TARGET] == dataset[i][1].numpy().tolist(), i
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