Check models used for common tests are small (#24824)
* First models * Conditional DETR * Treat DETR models, skip others * Skip LayoutLMv2 as well * Fix last tests
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@@ -321,6 +321,10 @@ class FlavaImageModelTest(ModelTesterMixin, unittest.TestCase):
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def test_save_load_fast_init_to_base(self):
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pass
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@unittest.skip("Will be fixed soon by reducing the size of the model used for common tests.")
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def test_model_is_small(self):
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pass
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@slow
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def test_model_from_pretrained(self):
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for model_name in FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
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@@ -472,6 +476,10 @@ class FlavaTextModelTest(ModelTesterMixin, unittest.TestCase):
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def test_save_load_fast_init_to_base(self):
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pass
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@unittest.skip("Will be fixed soon by reducing the size of the model used for common tests.")
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def test_model_is_small(self):
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pass
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@slow
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def test_model_from_pretrained(self):
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for model_name in FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
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@@ -624,6 +632,10 @@ class FlavaMultimodalModelTest(ModelTesterMixin, unittest.TestCase):
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def test_save_load_fast_init_to_base(self):
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pass
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@unittest.skip("Will be fixed soon by reducing the size of the model used for common tests.")
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def test_model_is_small(self):
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pass
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@slow
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def test_model_from_pretrained(self):
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for model_name in FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
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@@ -731,6 +743,10 @@ class FlavaImageCodebookTest(ModelTesterMixin, unittest.TestCase):
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def test_save_load_fast_init_to_base(self):
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pass
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@unittest.skip("Will be fixed soon by reducing the size of the model used for common tests.")
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def test_model_is_small(self):
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pass
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@slow
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def test_model_from_pretrained(self):
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for model_name in FLAVA_CODEBOOK_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
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@@ -913,6 +929,10 @@ class FlavaModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
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msg=f"Parameter {name} of model {model_class} seems not properly initialized",
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)
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@unittest.skip("Will be fixed soon by reducing the size of the model used for common tests.")
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def test_model_is_small(self):
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pass
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def _create_and_check_torchscript(self, config, inputs_dict):
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if not self.test_torchscript:
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return
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