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test_pipelines_translation.py
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Sat, Jul 5, 12:31

test_pipelines_translation.py
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# Copyright 2020 The HuggingFace Team. 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 unittest
import pytest
from transformers import pipeline
from transformers.testing_utils import is_pipeline_test, require_torch, slow
from .test_pipelines_common import MonoInputPipelineCommonMixin
class TranslationEnToDePipelineTests(MonoInputPipelineCommonMixin, unittest.TestCase):
pipeline_task = "translation_en_to_de"
small_models = ["patrickvonplaten/t5-tiny-random"] # Default model - Models tested without the @slow decorator
large_models = [None] # Models tested with the @slow decorator
invalid_inputs = [4, "<mask>"]
mandatory_keys = ["translation_text"]
class TranslationEnToRoPipelineTests(MonoInputPipelineCommonMixin, unittest.TestCase):
pipeline_task = "translation_en_to_ro"
small_models = ["patrickvonplaten/t5-tiny-random"] # Default model - Models tested without the @slow decorator
large_models = [None] # Models tested with the @slow decorator
invalid_inputs = [4, "<mask>"]
mandatory_keys = ["translation_text"]
@is_pipeline_test
class TranslationNewFormatPipelineTests(unittest.TestCase):
@require_torch
@slow
def test_default_translations(self):
# We don't provide a default for this pair
with self.assertRaises(ValueError):
pipeline(task="translation_cn_to_ar")
# but we do for this one
pipeline(task="translation_en_to_de")
@require_torch
def test_translation_on_odd_language(self):
model = "patrickvonplaten/t5-tiny-random"
pipeline(task="translation_cn_to_ar", model=model)
@require_torch
def test_translation_default_language_selection(self):
model = "patrickvonplaten/t5-tiny-random"
with pytest.warns(UserWarning, match=r".*translation_en_to_de.*"):
nlp = pipeline(task="translation", model=model)
self.assertEqual(nlp.task, "translation_en_to_de")
@require_torch
def test_translation_with_no_language_no_model_fails(self):
with self.assertRaises(ValueError):
pipeline(task="translation")

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