85 lines
3.4 KiB
Python
85 lines
3.4 KiB
Python
# coding=utf-8
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# Copyright 2019 HuggingFace Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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import os
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import tempfile
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import unittest
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from transformers.modelcard import ModelCard
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class ModelCardTester(unittest.TestCase):
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def setUp(self):
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self.inputs_dict = {
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"model_details": {
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"Organization": "testing",
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"Model date": "today",
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"Model version": "v2.1, Developed by Test Corp in 2019.",
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"Architecture": "Convolutional Neural Network.",
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},
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"metrics": "BLEU and ROUGE-1",
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"evaluation_data": {
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"Datasets": {"BLEU": "My-great-dataset-v1", "ROUGE-1": "My-short-dataset-v2.1"},
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"Preprocessing": "See details on https://arxiv.org/pdf/1810.03993.pdf",
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},
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"training_data": {
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"Dataset": "English Wikipedia dump dated 2018-12-01",
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"Preprocessing": (
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"Using SentencePiece vocabulary of size 52k tokens. See details on"
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" https://arxiv.org/pdf/1810.03993.pdf"
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),
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},
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"quantitative_analyses": {"BLEU": 55.1, "ROUGE-1": 76},
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}
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def test_model_card_common_properties(self):
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modelcard = ModelCard.from_dict(self.inputs_dict)
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self.assertTrue(hasattr(modelcard, "model_details"))
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self.assertTrue(hasattr(modelcard, "intended_use"))
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self.assertTrue(hasattr(modelcard, "factors"))
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self.assertTrue(hasattr(modelcard, "metrics"))
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self.assertTrue(hasattr(modelcard, "evaluation_data"))
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self.assertTrue(hasattr(modelcard, "training_data"))
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self.assertTrue(hasattr(modelcard, "quantitative_analyses"))
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self.assertTrue(hasattr(modelcard, "ethical_considerations"))
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self.assertTrue(hasattr(modelcard, "caveats_and_recommendations"))
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def test_model_card_to_json_string(self):
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modelcard = ModelCard.from_dict(self.inputs_dict)
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obj = json.loads(modelcard.to_json_string())
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for key, value in self.inputs_dict.items():
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self.assertEqual(obj[key], value)
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def test_model_card_to_json_file(self):
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model_card_first = ModelCard.from_dict(self.inputs_dict)
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with tempfile.TemporaryDirectory() as tmpdirname:
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filename = os.path.join(tmpdirname, "modelcard.json")
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model_card_first.to_json_file(filename)
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model_card_second = ModelCard.from_json_file(filename)
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self.assertEqual(model_card_second.to_dict(), model_card_first.to_dict())
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def test_model_card_from_and_save_pretrained(self):
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model_card_first = ModelCard.from_dict(self.inputs_dict)
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with tempfile.TemporaryDirectory() as tmpdirname:
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model_card_first.save_pretrained(tmpdirname)
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model_card_second = ModelCard.from_pretrained(tmpdirname)
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self.assertEqual(model_card_second.to_dict(), model_card_first.to_dict())
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