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| 1 | +# coding=utf-8 |
| 2 | +# Copyright 2018 The Tensor2Tensor Authors. |
| 3 | +# |
| 4 | +# Licensed under the Apache License, Version 2.0 (the "License"); |
| 5 | +# you may not use this file except in compliance with the License. |
| 6 | +# You may obtain a copy of the License at |
| 7 | +# |
| 8 | +# http://www.apache.org/licenses/LICENSE-2.0 |
| 9 | +# |
| 10 | +# Unless required by applicable law or agreed to in writing, software |
| 11 | +# distributed under the License is distributed on an "AS IS" BASIS, |
| 12 | +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 13 | +# See the License for the specific language governing permissions and |
| 14 | +# limitations under the License. |
| 15 | + |
| 16 | +"""Data generators for translation data-sets.""" |
| 17 | + |
| 18 | + |
| 19 | +from tensor2tensor.data_generators import problem |
| 20 | +from tensor2tensor.data_generators import text_encoder |
| 21 | +from tensor2tensor.data_generators import translate |
| 22 | +from tensor2tensor.utils import registry |
| 23 | + |
| 24 | + |
| 25 | +EOS = text_encoder.EOS_ID |
| 26 | + |
| 27 | +_URL = "https://github.com/LauraMartinus/ukuxhumana/blob/master/data/en_tn" |
| 28 | + |
| 29 | +_ENTN_TRAIN_DATASETS = [[ |
| 30 | + _URL + "/eng_tswane.train.tar.gz?raw=true", |
| 31 | + ("entn_parallel.train.en", "entn_parallel.train.tn") |
| 32 | +]] |
| 33 | + |
| 34 | +_ENTN_TEST_DATASETS = [[ |
| 35 | + _URL + "/eng_tswane.dev.tar.gz?raw=true", |
| 36 | + ("entn_parallel.dev.en", "entn_parallel.dev.tn") |
| 37 | +]] |
| 38 | + |
| 39 | + |
| 40 | +@registry.register_problem |
| 41 | +class TranslateEntnRma(translate.TranslateProblem): |
| 42 | + """Problem spec for English-Setswana translation. |
| 43 | +
|
| 44 | + Uses the RMA Autshumato dataset. |
| 45 | + """ |
| 46 | + |
| 47 | + @property |
| 48 | + def approx_vocab_size(self): |
| 49 | + return 2**15 # 32768 |
| 50 | + |
| 51 | + @property |
| 52 | + def vocab_filename(self): |
| 53 | + return "vocab.entn.%d" % self.approx_vocab_size |
| 54 | + |
| 55 | + def source_data_files(self, dataset_split): |
| 56 | + train = dataset_split == problem.DatasetSplit.TRAIN |
| 57 | + return _ENTN_TRAIN_DATASETS if train else _ENTN_TEST_DATASETS |
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