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Avoid failure TFBlipModelTest::test_pipeline_image_to_text #31827

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merged 3 commits into from
Jul 8, 2024
Merged

Avoid failure TFBlipModelTest::test_pipeline_image_to_text #31827

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407dffe
fix
ydshieh Jul 7, 2024
bb608c4
fix
ydshieh Jul 8, 2024
c5b6116
fix
ydshieh Jul 8, 2024
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6 changes: 6 additions & 0 deletions tests/models/efficientnet/test_modeling_efficientnet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -215,6 +215,12 @@ def test_model_from_pretrained(self):
def test_pipeline_image_feature_extraction(self):
super().test_pipeline_image_feature_extraction()

@is_pipeline_test
@require_vision
@slow
def test_pipeline_image_feature_extraction_fp16(self):
super().test_pipeline_image_feature_extraction_fp16()

@is_pipeline_test
@require_vision
@slow
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4 changes: 4 additions & 0 deletions tests/models/vits/test_modeling_vits.py
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Expand Up @@ -181,6 +181,10 @@ def test_config(self):
def test_pipeline_feature_extraction(self):
super().test_pipeline_feature_extraction()

@is_flaky(description="torch 2.2.0 gives `Timeout >120.0s`")
def test_pipeline_feature_extraction_fp16(self):
super().test_pipeline_feature_extraction_fp16()

@unittest.skip(reason="Need to fix this after #26538")
def test_model_forward(self):
set_seed(12345)
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6 changes: 3 additions & 3 deletions tests/pipelines/test_pipelines_image_to_text.py
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Expand Up @@ -17,7 +17,7 @@
import requests

from transformers import MODEL_FOR_VISION_2_SEQ_MAPPING, TF_MODEL_FOR_VISION_2_SEQ_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines import ImageToTextPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
require_tf,
Expand Down Expand Up @@ -46,8 +46,8 @@ class ImageToTextPipelineTests(unittest.TestCase):
tf_model_mapping = TF_MODEL_FOR_VISION_2_SEQ_MAPPING

def get_test_pipeline(self, model, tokenizer, processor, torch_dtype="float32"):
pipe = pipeline(
"image-to-text", model=model, tokenizer=tokenizer, image_processor=processor, torch_dtype=torch_dtype
pipe = ImageToTextPipeline(
model=model, tokenizer=tokenizer, image_processor=processor, torch_dtype=torch_dtype
)
examples = [
Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"),
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