first commit

tests/models/pp_chart2table/test_modeling_pp_chart2table.py

@@ -0,0 +1,85 @@
+# Copyright 2026 The HuggingFace Inc. 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.
+"""Testing suite for the PPChart2Table model."""
+
+import unittest
+
+from transformers import AutoModelForImageTextToText, AutoProcessor
+from transformers.testing_utils import cleanup, require_torch, require_vision, slow, torch_device
+
+from ...test_processing_common import url_to_local_path
+
+
+@slow
+@require_vision
+@require_torch
+class PPChart2TableIntegrationTest(unittest.TestCase):
+    def setUp(self):
+        model_path = "PaddlePaddle/PP-Chart2Table_safetensors"
+        self.model = AutoModelForImageTextToText.from_pretrained(model_path).to(torch_device)
+        self.processor = AutoProcessor.from_pretrained(model_path)
+        self.conversation = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image",
+                        "url": url_to_local_path(
+                            "https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/chart_parsing_02.png"
+                        ),
+                    },
+                ],
+            },
+        ]
+
+    def tearDown(self):
+        cleanup(torch_device, gc_collect=True)
+
+    def test_small_model_integration_test_pp_chart2table(self):
+        inputs = self.processor.apply_chat_template(
+            self.conversation,
+            tokenize=True,
+            add_generation_prompt=True,
+            truncation=True,
+            return_dict=True,
+            return_tensors="pt",
+        ).to(self.model.device)
+
+        generated_ids = self.model.generate(**inputs, do_sample=False, max_new_tokens=32)
+        generated_ids_trimmed = [out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)]
+        decoded_output = self.processor.batch_decode(
+            generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+        )
+
+        expected_output = ["年份 | 单家五星级旅游饭店年平均营收 (百万元) | 单家五星级旅游饭店年平均利润 (百万元)\n"]
+        self.assertEqual(decoded_output, expected_output)
+
+    def test_small_model_integration_test_pp_chart2table_batched(self):
+        inputs = self.processor.apply_chat_template(
+            [self.conversation, self.conversation],
+            tokenize=True,
+            add_generation_prompt=True,
+            truncation=True,
+            return_dict=True,
+            return_tensors="pt",
+        ).to(self.model.device)
+
+        generated_ids = self.model.generate(**inputs, do_sample=False, max_new_tokens=6)
+        generated_ids_trimmed = [out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)]
+        decoded_output = self.processor.batch_decode(
+            generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+        )
+
+        expected_output = ["年份 | 单家", "年份 | 单家"]
+        self.assertEqual(decoded_output, expected_output)