delete my fastnlp/io/dataset_loader.py and add test file

reproduction/Summarization/test/test_dataloader.py

@@ -0,0 +1,36 @@
+
+import unittest
+
+import sys
+sys.path.append('..')
+
+from data.dataloader import SummarizationLoader
+
+vocab_size = 100000
+vocab_path = "testdata/vocab"
+sent_max_len = 100
+doc_max_timesteps = 50
+
+class TestSummarizationLoader(unittest.TestCase):
+
+    def test_case1(self):
+        sum_loader = SummarizationLoader()
+        paths = {"train":"testdata/train.jsonl", "valid":"testdata/val.jsonl", "test":"testdata/test.jsonl"}
+        data = 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)
+        print(data.datasets)
+
+    def test_case2(self):
+        sum_loader = SummarizationLoader()
+        paths = {"train": "testdata/train.jsonl", "valid": "testdata/val.jsonl", "test": "testdata/test.jsonl"}
+        data = 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, domain=True)
+        print(data.datasets, data.vocabs)
+
+    def test_case3(self):
+        sum_loader = SummarizationLoader()
+        paths = {"train": "testdata/train.jsonl", "valid": "testdata/val.jsonl", "test": "testdata/test.jsonl"}
+        data = 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, tag=True)
+        print(data.datasets, data.vocabs)
+
+
+
+

reproduction/Summarization/test_data.py

@@ -0,0 +1,56 @@
+#!/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