def create_and_check_model(self, config, pixel_values, labels): model = ConvNextModel(config=config) model.to(torch_device) model.eval() result = model(pixel_values) # expected last hidden states: B, C, H // 32, W // 32 self.parent.assertEqual( result.last_hidden_state.shape, (self.batch_size, self.hidden_sizes[-1], self.image_size // 32, self.image_size // 32), )
def test_model_from_pretrained(self): for model_name in CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: model = ConvNextModel.from_pretrained(model_name) self.assertIsNotNone(model)