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[CLIP] Fix TF test (#15042)

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This commit is contained in:
Suraj Patil
2022-01-05 16:58:42 +01:00
committed by GitHub
parent 443fdaf29f
commit 2e9af29494
1 changed files with 5 additions and 4 deletions
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9
tests/test_modeling_tf_clip.py
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@@ -254,7 +254,7 @@ class TFCLIPVisionModelTest(TFModelTesterMixin, unittest.TestCase):
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: for model_name in TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = TFCLIPVisionModel.from_pretrained(model_name, from_pt=True) model = TFCLIPVisionModel.from_pretrained(model_name)
self.assertIsNotNone(model) self.assertIsNotNone(model)
@@ -359,7 +359,7 @@ class TFCLIPTextModelTest(TFModelTesterMixin, unittest.TestCase):
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: for model_name in TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = TFCLIPTextModel.from_pretrained(model_name, from_pt=True) model = TFCLIPTextModel.from_pretrained(model_name)
self.assertIsNotNone(model) self.assertIsNotNone(model)
@@ -618,7 +618,7 @@ class TFCLIPModelTest(TFModelTesterMixin, unittest.TestCase):
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: for model_name in TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = TFCLIPModel.from_pretrained(model_name, from_pt=True) model = TFCLIPModel.from_pretrained(model_name)
self.assertIsNotNone(model) self.assertIsNotNone(model)
@@ -630,11 +630,12 @@ def prepare_img():
@require_vision @require_vision
@require_tf
class TFCLIPModelIntegrationTest(unittest.TestCase): class TFCLIPModelIntegrationTest(unittest.TestCase):
@slow @slow
def test_inference(self): def test_inference(self):
model_name = "openai/clip-vit-base-patch32" model_name = "openai/clip-vit-base-patch32"
model = TFCLIPModel.from_pretrained(model_name, from_pt=True) model = TFCLIPModel.from_pretrained(model_name)
processor = CLIPProcessor.from_pretrained(model_name) processor = CLIPProcessor.from_pretrained(model_name)
image = prepare_img() image = prepare_img()