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test_pipelines_text_generation.py
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test_pipelines_text_generation.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
from transformers import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING, TextGenerationPipeline, pipeline
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from .test_pipelines_common import ANY, PipelineTestCaseMeta
@is_pipeline_test
class TextGenerationPipelineTests(unittest.TestCase, metaclass=PipelineTestCaseMeta):
model_mapping = MODEL_FOR_CAUSAL_LM_MAPPING
tf_model_mapping = TF_MODEL_FOR_CAUSAL_LM_MAPPING
@require_torch
def test_small_model_pt(self):
text_generator = pipeline(task="text-generation", model="sshleifer/tiny-ctrl", framework="pt")
# Using `do_sample=False` to force deterministic output
outputs = text_generator("This is a test", do_sample=False)
self.assertEqual(
outputs,
[
{
"generated_text": "This is a test ☃ ☃ segmental segmental segmental 议议eski eski flutter flutter Lacy oscope. oscope. FiliFili@@"
}
],
)
outputs = text_generator(["This is a test", "This is a second test"])
self.assertEqual(
outputs,
[
[
{
"generated_text": "This is a test ☃ ☃ segmental segmental segmental 议议eski eski flutter flutter Lacy oscope. oscope. FiliFili@@"
}
],
[
{
"generated_text": "This is a second test ☃ segmental segmental segmental 议议eski eski flutter flutter Lacy oscope. oscope. FiliFili@@"
}
],
],
)
@require_tf
def test_small_model_tf(self):
text_generator = pipeline(task="text-generation", model="sshleifer/tiny-ctrl", framework="tf")
# Using `do_sample=False` to force deterministic output
outputs = text_generator("This is a test", do_sample=False)
self.assertEqual(
outputs,
[
{
"generated_text": "This is a test FeyFeyFey(Croatis.), s.), Cannes Cannes Cannes 閲閲Cannes Cannes Cannes 攵 please,"
}
],
)
outputs = text_generator(["This is a test", "This is a second test"], do_sample=False)
self.assertEqual(
outputs,
[
[
{
"generated_text": "This is a test FeyFeyFey(Croatis.), s.), Cannes Cannes Cannes 閲閲Cannes Cannes Cannes 攵 please,"
}
],
[
{
"generated_text": "This is a second test Chieftain Chieftain prefecture prefecture prefecture Cannes Cannes Cannes 閲閲Cannes Cannes Cannes 攵 please,"
}
],
],
)
def run_pipeline_test(self, model, tokenizer, feature_extractor):
text_generator = TextGenerationPipeline(model=model, tokenizer=tokenizer)
outputs = text_generator("This is a test")
self.assertEqual(outputs, [{"generated_text": ANY(str)}])
self.assertTrue(outputs[0]["generated_text"].startswith("This is a test"))
outputs = text_generator("This is a test", return_full_text=False)
self.assertEqual(outputs, [{"generated_text": ANY(str)}])
self.assertNotIn("This is a test", outputs[0]["generated_text"])
text_generator = pipeline(task="text-generation", model=model, tokenizer=tokenizer, return_full_text=False)
outputs = text_generator("This is a test")
self.assertEqual(outputs, [{"generated_text": ANY(str)}])
self.assertNotIn("This is a test", outputs[0]["generated_text"])
outputs = text_generator("This is a test", return_full_text=True)
self.assertEqual(outputs, [{"generated_text": ANY(str)}])
self.assertTrue(outputs[0]["generated_text"].startswith("This is a test"))
# Empty prompt is slighly special
# it requires BOS token to exist.
# Special case for Pegasus which will always append EOS so will
# work even without BOS.
if text_generator.tokenizer.bos_token_id is not None or "Pegasus" in tokenizer.__class__.__name__:
outputs = text_generator("")
self.assertEqual(outputs, [{"generated_text": ANY(str)}])
else:
with self.assertRaises((ValueError, AssertionError)):
outputs = text_generator("")