From 5ff10c8ced9d41e1a4d8c49dc557fdf67ba7565b Mon Sep 17 00:00:00 2001 From: CSWYF3634076 Date: Wed, 24 Sep 2025 19:45:01 +0800 Subject: [PATCH] [Model] Qwen2.5VL support --use-cudagraph and unit testing (#4087) * [BugFix] qwen2.5vl enable_thinking=true and image_patch_id bug fix * [Docs]offine infer add apply_chat_template add_generation_prompt parameter * [Model]qwen2.5VL support --use-cudagraph * [Model]qwen2.5VL support --use-cudagraph buffer and qwenvl test * [Model]qwen2.5VL support --use-cudagraph buffer and qwenvl test * [Model]qwen2.5VL support --use-cudagraph buffer and qwenvl test v2 * [Model]qwen2.5VL support --use-cudagraph buffer and qwenvl test v3 * [Model]qwen2.5VL support --use-cudagraph buffer and qwenvl test v4 * [Model]qwen2.5VL support --use-cudagraph buffer and qwenvl test v5 * [Model]qwen2.5VL support --use-cudagraph buffer and qwenvl test v6 * [Model]qwen2.5VL support --use-cudagraph buffer and qwenvl test v7 --- docs/offline_inference.md | 2 +- docs/zh/offline_inference.md | 2 +- .../models/qwen2_5_vl/qwen2_5_vl.py | 77 +-- .../Qwen2_5_VL/test_Qwen2_5_VL_serving.py | 503 ++++++++++++++++++ tests/e2e/test_Qwen2_5_VL_serving.py | 503 ++++++++++++++++++ 5 files changed, 1048 insertions(+), 39 deletions(-) create mode 100644 tests/ci_use/Qwen2_5_VL/test_Qwen2_5_VL_serving.py create mode 100644 tests/e2e/test_Qwen2_5_VL_serving.py diff --git a/docs/offline_inference.md b/docs/offline_inference.md index 1429ff009..a8efef5ca 100644 --- a/docs/offline_inference.md +++ b/docs/offline_inference.md @@ -107,7 +107,7 @@ messages = [ } ] -prompt = tokenizer.apply_chat_template(messages, tokenize=False) +prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) images, videos = [], [] for message in messages: content = message["content"] diff --git a/docs/zh/offline_inference.md b/docs/zh/offline_inference.md index adac6ff28..1df7154cc 100644 --- a/docs/zh/offline_inference.md +++ b/docs/zh/offline_inference.md @@ -107,7 +107,7 @@ messages = [ } ] -prompt = tokenizer.apply_chat_template(messages, tokenize=False) +prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) images, videos = [], [] for message in messages: content = message["content"] diff --git a/fastdeploy/model_executor/models/qwen2_5_vl/qwen2_5_vl.py b/fastdeploy/model_executor/models/qwen2_5_vl/qwen2_5_vl.py index 1ec312fd6..ddd3cd483 100644 --- a/fastdeploy/model_executor/models/qwen2_5_vl/qwen2_5_vl.py +++ b/fastdeploy/model_executor/models/qwen2_5_vl/qwen2_5_vl.py @@ -27,6 +27,7 @@ from paddleformers.transformers.configuration_utils import PretrainedConfig from paddleformers.utils.log import logger from fastdeploy.config import FDConfig +from fastdeploy.model_executor.forward_meta import ForwardMeta from fastdeploy.model_executor.graph_optimization.decorator import ( support_graph_optimization, ) @@ -39,12 +40,6 @@ from fastdeploy.model_executor.models.model_base import ( ModelRegistry, ) from fastdeploy.model_executor.models.qwen2 import Qwen2DecoderLayer -from fastdeploy.platforms import current_platform - -if current_platform.is_cuda(): - from fastdeploy.model_executor.ops.gpu import extract_text_token_output - -from fastdeploy.model_executor.forward_meta import ForwardMeta @support_graph_optimization @@ -108,31 +103,17 @@ class Qwen2_5_VLModel(nn.Layer): logger.info(f"Start load layer {i}") self.layers[i].load_state_dict(state_dict) + def get_input_embeddings(self, ids_remove_padding: paddle.Tensor) -> paddle.Tensor: + return self.embed_tokens(ids_remove_padding=ids_remove_padding) + def forward( self, + input_embeddings: paddle.Tensor, ids_remove_padding: paddle.Tensor, image_features: Optional[paddle.Tensor], forward_meta: ForwardMeta, ): - - hidden_states = self.embed_tokens(ids_remove_padding=ids_remove_padding) - - # ----------------------- - # 将 image_embeds 替换 input_embeds 里的 image video 占位符 - image_mask = ids_remove_padding == self.image_token_id - image_token_num = image_mask.sum() - - video_mask = ids_remove_padding == self.video_token_id - video_token_num = video_mask.sum() - - # 由于框架只有 image_features，所以目前不支持图片和视频混合 - # TODO(wangyafeng) 后续考虑支持传入 video_features - if image_token_num > 0: - hidden_states[image_mask] = image_features.cast(self._dtype) - if video_token_num > 0: - hidden_states[video_mask] = image_features.cast(self._dtype) - - # ----------------------- + hidden_states = input_embeddings residual = None for i in range(self.num_layers): @@ -144,18 +125,6 @@ class Qwen2_5_VLModel(nn.Layer): hidden_states = hidden_states + residual - # ----------------------- - max_seq_len, max_seq_len_index = paddle.topk(forward_meta.seq_lens_this_time, k=1) - hidden_states = extract_text_token_output( - max_seq_len, - max_seq_len_index.cast("int32"), - image_token_num.cast("int32"), - forward_meta.seq_lens_this_time, - forward_meta.cu_seqlens_q, - hidden_states.cast("float32"), - ).cast(self._dtype) - # ----------------------- - out = self.norm(hidden_states) return out @@ -183,6 +152,12 @@ class Qwen2_5_VLForConditionalGeneration(ModelForCasualLM): # ----------- language model ------------- self.model = Qwen2_5_VLModel(fd_config=fd_config) + # Persistent buffers for CUDA graphs. + self._input_embeddings = paddle.zeros( + [fd_config.parallel_config.max_model_len, fd_config.model_config.hidden_size], + dtype=fd_config.model_config.dtype, + ) + self.ori_vocab_size = fd_config.model_config.ori_vocab_size self.lm_head = ParallelLMHead( @@ -246,14 +221,42 @@ class Qwen2_5_VLForConditionalGeneration(ModelForCasualLM): self.ernie.layers[i].mlp.text_fused_moe(fake_hidden_states) self.ernie.layers[i].mlp.image_fused_moe(fake_hidden_states) + def get_input_embeddings( + self, + ids_remove_padding: paddle.Tensor, + image_features: Optional[paddle.Tensor] = None, + ) -> paddle.Tensor: + + input_embeddings = self.model.get_input_embeddings(ids_remove_padding=ids_remove_padding) + + image_mask = ids_remove_padding == self.model.image_token_id + image_token_num = image_mask.sum() + + video_mask = ids_remove_padding == self.model.video_token_id + video_token_num = video_mask.sum() + + # 由于框架只有 image_features，所以目前不支持图片和视频混合 + # TODO(wangyafeng) 后续考虑支持传入 video_features + if image_token_num > 0: + input_embeddings[image_mask] = image_features.cast(self.model._dtype) + if video_token_num > 0: + input_embeddings[video_mask] = image_features.cast(self.model._dtype) + + return input_embeddings + def forward( self, ids_remove_padding: paddle.Tensor, image_features: Optional[paddle.Tensor], forward_meta: ForwardMeta, ): + input_embeddings = self.get_input_embeddings( + ids_remove_padding=ids_remove_padding, image_features=image_features + ) + self._input_embeddings.copy_(input_embeddings, False) hidden_states = self.model( + input_embeddings=self._input_embeddings, ids_remove_padding=ids_remove_padding, image_features=image_features, forward_meta=forward_meta, diff --git a/tests/ci_use/Qwen2_5_VL/test_Qwen2_5_VL_serving.py b/tests/ci_use/Qwen2_5_VL/test_Qwen2_5_VL_serving.py new file mode 100644 index 000000000..8e0d1722f --- /dev/null +++ b/tests/ci_use/Qwen2_5_VL/test_Qwen2_5_VL_serving.py @@ -0,0 +1,503 @@ +# Copyright (c) 2025 PaddlePaddle Authors. 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. + +import json +import os +import re +import signal +import socket +import subprocess +import sys +import time + +import openai +import pytest +import requests + +# Read ports from environment variables; use default values if not set +FD_API_PORT = int(os.getenv("FD_API_PORT", 8188)) +FD_ENGINE_QUEUE_PORT = int(os.getenv("FD_ENGINE_QUEUE_PORT", 8133)) +FD_METRICS_PORT = int(os.getenv("FD_METRICS_PORT", 8233)) + +# List of ports to clean before and after tests +PORTS_TO_CLEAN = [FD_API_PORT, FD_ENGINE_QUEUE_PORT, FD_METRICS_PORT] + + +def is_port_open(host: str, port: int, timeout=1.0): + """ + Check if a TCP port is open on the given host. + Returns True if connection succeeds, False otherwise. + """ + try: + with socket.create_connection((host, port), timeout): + return True + except Exception: + return False + + +def kill_process_on_port(port: int): + """ + Kill processes that are listening on the given port. + Uses `lsof` to find process ids and sends SIGKILL. + """ + try: + output = subprocess.check_output(f"lsof -i:{port} -t", shell=True).decode().strip() + for pid in output.splitlines(): + os.kill(int(pid), signal.SIGKILL) + print(f"Killed process on port {port}, pid={pid}") + except subprocess.CalledProcessError: + pass + + +def clean_ports(): + """ + Kill all processes occupying the ports listed in PORTS_TO_CLEAN. + """ + for port in PORTS_TO_CLEAN: + kill_process_on_port(port) + + +@pytest.fixture(scope="session", autouse=True) +def setup_and_run_server(): + """ + Pytest fixture that runs once per test session: + - Cleans ports before tests + - Starts the API server as a subprocess + - Waits for server port to open (up to 30 seconds) + - Tears down server after all tests finish + """ + print("Pre-test port cleanup...") + clean_ports() + + model_path = "/ModelData/Qwen2.5-VL-7B-Instruct" + + log_path = "server.log" + limit_mm_str = json.dumps({"image": 100, "video": 100}) + + cmd = [ + sys.executable, + "-m", + "fastdeploy.entrypoints.openai.api_server", + "--model", + model_path, + "--port", + str(FD_API_PORT), + # "--tensor-parallel-size", + # "2", + "--engine-worker-queue-port", + str(FD_ENGINE_QUEUE_PORT), + "--metrics-port", + str(FD_METRICS_PORT), + "--enable-mm", + "--max-model-len", + "32768", + "--max-num-batched-tokens", + "384", + "--max-num-seqs", + "128", + "--limit-mm-per-prompt", + limit_mm_str, + ] + + print(cmd) + # Start subprocess in new process group + with open(log_path, "w") as logfile: + process = subprocess.Popen( + cmd, + stdout=logfile, + stderr=subprocess.STDOUT, + start_new_session=True, # Enables killing full group via os.killpg + ) + + print(f"Started API server with pid {process.pid}") + # Wait up to 10 minutes for API server to be ready + for _ in range(10 * 60): + if is_port_open("127.0.0.1", FD_API_PORT): + print(f"API server is up on port {FD_API_PORT}") + break + time.sleep(1) + else: + print("[TIMEOUT] API server failed to start in 10 minutes. Cleaning up...") + try: + os.killpg(process.pid, signal.SIGTERM) + except Exception as e: + print(f"Failed to kill process group: {e}") + raise RuntimeError(f"API server did not start on port {FD_API_PORT}") + + yield # Run tests + + print("\n===== Post-test server cleanup... =====") + try: + os.killpg(process.pid, signal.SIGTERM) + print(f"API server (pid={process.pid}) terminated") + except Exception as e: + print(f"Failed to terminate API server: {e}") + + +@pytest.fixture(scope="session") +def api_url(request): + """ + Returns the API endpoint URL for chat completions. + """ + return f"http://0.0.0.0:{FD_API_PORT}/v1/chat/completions" + + +@pytest.fixture(scope="session") +def metrics_url(request): + """ + Returns the metrics endpoint URL. + """ + return f"http://0.0.0.0:{FD_METRICS_PORT}/metrics" + + +@pytest.fixture +def headers(): + """ + Returns common HTTP request headers. + """ + return {"Content-Type": "application/json"} + + +@pytest.fixture +def consistent_payload(): + """ + Returns a fixed payload for consistency testing, + including a fixed random seed and temperature. + """ + return { + "messages": [ + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://ku.baidu-int.com/vk-assets-ltd/space/2024/09/13/933d1e0a0760498e94ec0f2ccee865e0", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + } + ], + "temperature": 0.8, + "top_p": 0, # fix top_p to reduce randomness + "seed": 13, # fixed random seed + } + + +# ========================== +# Consistency test for repeated runs with fixed payload +# ========================== +def test_consistency_between_runs(api_url, headers, consistent_payload): + """ + Test that result is same as the base result. + """ + # request + resp1 = requests.post(api_url, headers=headers, json=consistent_payload) + assert resp1.status_code == 200 + result1 = resp1.json() + content1 = result1["choices"][0]["message"]["content"] + file_res_temp = "Qwen2.5-VL-7B-Instruct-temp" + f_o = open(file_res_temp, "a") + f_o.writelines(content1) + f_o.close() + + # base result + content2 = "这张图片展示了一群人在进行手工艺活动。前景中有两个孩子和一个成年人，他们似乎在制作或展示某种手工艺品。成年人手里拿着一个扇子，上面有彩色的图案，可能是在指导孩子们如何制作这个扇子。孩子们看起来很专注，正在认真地观察和学习。背景中还有其他人在进行类似的活动，环境看起来像是在一个教室或工作室里。整体氛围显得非常温馨和积极。" + + # Verify that result is same as the base result + assert content1 == content2 + + +# ========================== +# OpenAI Client Chat Completion Test +# ========================== + + +@pytest.fixture +def openai_client(): + ip = "0.0.0.0" + service_http_port = str(FD_API_PORT) + client = openai.Client( + base_url=f"http://{ip}:{service_http_port}/v1", + api_key="EMPTY_API_KEY", + ) + return client + + +# Non-streaming test +def test_non_streaming_chat(openai_client): + """Test non-streaming chat functionality with the local service""" + response = openai_client.chat.completions.create( + model="default", + messages=[ + { + "role": "system", + "content": "You are a helpful AI assistant.", + }, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://ku.baidu-int.com/vk-assets-ltd/space/2024/09/13/933d1e0a0760498e94ec0f2ccee865e0", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + stream=False, + ) + + assert hasattr(response, "choices") + assert len(response.choices) > 0 + assert hasattr(response.choices[0], "message") + assert hasattr(response.choices[0].message, "content") + + +# Streaming test +def test_streaming_chat(openai_client, capsys): + """Test streaming chat functionality with the local service""" + response = openai_client.chat.completions.create( + model="default", + messages=[ + { + "role": "system", + "content": "You are a helpful AI assistant.", + }, # system不是必需，可选 + {"role": "user", "content": "List 3 countries and their capitals."}, + { + "role": "assistant", + "content": "China(Beijing), France(Paris), Australia(Canberra).", + }, + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://ku.baidu-int.com/vk-assets-ltd/space/2024/09/13/933d1e0a0760498e94ec0f2ccee865e0", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=512, + stream=True, + ) + + output = [] + for chunk in response: + if hasattr(chunk.choices[0], "delta") and hasattr(chunk.choices[0].delta, "content"): + output.append(chunk.choices[0].delta.content) + assert len(output) > 2 + + +# ========================== +# OpenAI Client additional chat/completions test +# ========================== + + +def test_non_streaming_chat_with_return_token_ids(openai_client, capsys): + """ + Test return_token_ids option in non-streaming chat functionality with the local service + """ + # 设定 return_token_ids + response = openai_client.chat.completions.create( + model="default", + messages=[ + {"role": "system", "content": "You are a helpful AI assistant."}, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://paddlenlp.bj.bcebos.com/datasets/paddlemix/demo_images/example2.jpg", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + extra_body={"return_token_ids": True}, + stream=False, + ) + assert hasattr(response, "choices") + assert len(response.choices) > 0 + assert hasattr(response.choices[0], "message") + assert hasattr(response.choices[0].message, "prompt_token_ids") + assert isinstance(response.choices[0].message.prompt_token_ids, list) + assert hasattr(response.choices[0].message, "completion_token_ids") + assert isinstance(response.choices[0].message.completion_token_ids, list) + + # 不设定 return_token_ids + response = openai_client.chat.completions.create( + model="default", + messages=[ + {"role": "system", "content": "You are a helpful AI assistant."}, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://paddlenlp.bj.bcebos.com/datasets/paddlemix/demo_images/example2.jpg", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + extra_body={"return_token_ids": False}, + stream=False, + ) + assert hasattr(response, "choices") + assert len(response.choices) > 0 + assert hasattr(response.choices[0], "message") + assert hasattr(response.choices[0].message, "prompt_token_ids") + assert response.choices[0].message.prompt_token_ids is None + assert hasattr(response.choices[0].message, "completion_token_ids") + assert response.choices[0].message.completion_token_ids is None + + +def test_streaming_chat_with_return_token_ids(openai_client, capsys): + """ + Test return_token_ids option in streaming chat functionality with the local service + """ + # enable return_token_ids + response = openai_client.chat.completions.create( + model="default", + messages=[ + {"role": "system", "content": "You are a helpful AI assistant."}, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://paddlenlp.bj.bcebos.com/datasets/paddlemix/demo_images/example2.jpg", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + extra_body={"return_token_ids": True}, + stream=True, + ) + is_first_chunk = True + for chunk in response: + assert hasattr(chunk, "choices") + assert len(chunk.choices) > 0 + assert hasattr(chunk.choices[0], "delta") + assert hasattr(chunk.choices[0].delta, "prompt_token_ids") + assert hasattr(chunk.choices[0].delta, "completion_token_ids") + if is_first_chunk: + is_first_chunk = False + assert isinstance(chunk.choices[0].delta.prompt_token_ids, list) + assert chunk.choices[0].delta.completion_token_ids is None + else: + assert chunk.choices[0].delta.prompt_token_ids is None + assert isinstance(chunk.choices[0].delta.completion_token_ids, list) + + # disable return_token_ids + response = openai_client.chat.completions.create( + model="default", + messages=[ + {"role": "system", "content": "You are a helpful AI assistant."}, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://paddlenlp.bj.bcebos.com/datasets/paddlemix/demo_images/example2.jpg", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + extra_body={"return_token_ids": False}, + stream=True, + ) + for chunk in response: + assert hasattr(chunk, "choices") + assert len(chunk.choices) > 0 + assert hasattr(chunk.choices[0], "delta") + assert hasattr(chunk.choices[0].delta, "prompt_token_ids") + assert chunk.choices[0].delta.prompt_token_ids is None + assert hasattr(chunk.choices[0].delta, "completion_token_ids") + assert chunk.choices[0].delta.completion_token_ids is None + + +def test_profile_reset_block_num(): + """测试profile reset_block_num功能，与baseline diff不能超过15%""" + log_file = "./log/config.log" + baseline = 30000 + + if not os.path.exists(log_file): + pytest.fail(f"Log file not found: {log_file}") + + with open(log_file, "r") as f: + log_lines = f.readlines() + + target_line = None + for line in log_lines: + if "Reset block num" in line: + target_line = line.strip() + break + + if target_line is None: + pytest.fail("日志中没有Reset block num信息") + + match = re.search(r"total_block_num:(\d+)", target_line) + if not match: + pytest.fail(f"Failed to extract total_block_num from line: {target_line}") + + try: + actual_value = int(match.group(1)) + except ValueError: + pytest.fail(f"Invalid number format: {match.group(1)}") + + lower_bound = baseline * (1 - 0.15) + upper_bound = baseline * (1 + 0.15) + print(f"Reset total_block_num: {actual_value}. baseline: {baseline}") + + assert lower_bound <= actual_value <= upper_bound, ( + f"Reset total_block_num {actual_value} 与 baseline {baseline} diff需要在5%以内" + f"Allowed range: [{lower_bound:.1f}, {upper_bound:.1f}]" + ) diff --git a/tests/e2e/test_Qwen2_5_VL_serving.py b/tests/e2e/test_Qwen2_5_VL_serving.py new file mode 100644 index 000000000..82c5fd6e0 --- /dev/null +++ b/tests/e2e/test_Qwen2_5_VL_serving.py @@ -0,0 +1,503 @@ +# Copyright (c) 2025 PaddlePaddle Authors. 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. + +import json +import os +import re +import signal +import socket +import subprocess +import sys +import time + +import openai +import pytest +import requests + +# Read ports from environment variables; use default values if not set +FD_API_PORT = int(os.getenv("FD_API_PORT", 8188)) +FD_ENGINE_QUEUE_PORT = int(os.getenv("FD_ENGINE_QUEUE_PORT", 8133)) +FD_METRICS_PORT = int(os.getenv("FD_METRICS_PORT", 8233)) + +# List of ports to clean before and after tests +PORTS_TO_CLEAN = [FD_API_PORT, FD_ENGINE_QUEUE_PORT, FD_METRICS_PORT] + + +def is_port_open(host: str, port: int, timeout=1.0): + """ + Check if a TCP port is open on the given host. + Returns True if connection succeeds, False otherwise. + """ + try: + with socket.create_connection((host, port), timeout): + return True + except Exception: + return False + + +def kill_process_on_port(port: int): + """ + Kill processes that are listening on the given port. + Uses `lsof` to find process ids and sends SIGKILL. + """ + try: + output = subprocess.check_output(f"lsof -i:{port} -t", shell=True).decode().strip() + for pid in output.splitlines(): + os.kill(int(pid), signal.SIGKILL) + print(f"Killed process on port {port}, pid={pid}") + except subprocess.CalledProcessError: + pass + + +def clean_ports(): + """ + Kill all processes occupying the ports listed in PORTS_TO_CLEAN. + """ + for port in PORTS_TO_CLEAN: + kill_process_on_port(port) + + +@pytest.fixture(scope="session", autouse=True) +def setup_and_run_server(): + """ + Pytest fixture that runs once per test session: + - Cleans ports before tests + - Starts the API server as a subprocess + - Waits for server port to open (up to 30 seconds) + - Tears down server after all tests finish + """ + print("Pre-test port cleanup...") + clean_ports() + + model_path = "/ModelData/Qwen2.5-VL-7B-Instruct" + + log_path = "server.log" + limit_mm_str = json.dumps({"image": 100, "video": 100}) + + cmd = [ + sys.executable, + "-m", + "fastdeploy.entrypoints.openai.api_server", + "--model", + model_path, + "--port", + str(FD_API_PORT), + # "--tensor-parallel-size", + # "2", + "--engine-worker-queue-port", + str(FD_ENGINE_QUEUE_PORT), + "--metrics-port", + str(FD_METRICS_PORT), + "--enable-mm", + "--max-model-len", + "32768", + "--max-num-batched-tokens", + "384", + "--max-num-seqs", + "128", + "--limit-mm-per-prompt", + limit_mm_str, + ] + + print(cmd) + # Start subprocess in new process group + with open(log_path, "w") as logfile: + process = subprocess.Popen( + cmd, + stdout=logfile, + stderr=subprocess.STDOUT, + start_new_session=True, # Enables killing full group via os.killpg + ) + + print(f"Started API server with pid {process.pid}") + # Wait up to 10 minutes for API server to be ready + for _ in range(10 * 60): + if is_port_open("127.0.0.1", FD_API_PORT): + print(f"API server is up on port {FD_API_PORT}") + break + time.sleep(1) + else: + print("[TIMEOUT] API server failed to start in 10 minutes. Cleaning up...") + try: + os.killpg(process.pid, signal.SIGTERM) + except Exception as e: + print(f"Failed to kill process group: {e}") + raise RuntimeError(f"API server did not start on port {FD_API_PORT}") + + yield # Run tests + + print("\n===== Post-test server cleanup... =====") + try: + os.killpg(process.pid, signal.SIGTERM) + print(f"API server (pid={process.pid}) terminated") + except Exception as e: + print(f"Failed to terminate API server: {e}") + + +@pytest.fixture(scope="session") +def api_url(request): + """ + Returns the API endpoint URL for chat completions. + """ + return f"http://0.0.0.0:{FD_API_PORT}/v1/chat/completions" + + +@pytest.fixture(scope="session") +def metrics_url(request): + """ + Returns the metrics endpoint URL. + """ + return f"http://0.0.0.0:{FD_METRICS_PORT}/metrics" + + +@pytest.fixture +def headers(): + """ + Returns common HTTP request headers. + """ + return {"Content-Type": "application/json"} + + +@pytest.fixture +def consistent_payload(): + """ + Returns a fixed payload for consistency testing, + including a fixed random seed and temperature. + """ + return { + "messages": [ + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://ku.baidu-int.com/vk-assets-ltd/space/2024/09/13/933d1e0a0760498e94ec0f2ccee865e0", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + } + ], + "temperature": 0.8, + "top_p": 0, # fix top_p to reduce randomness + "seed": 13, # fixed random seed + } + + +# ========================== +# Consistency test for repeated runs with fixed payload +# ========================== +def test_consistency_between_runs(api_url, headers, consistent_payload): + """ + Test that result is same as the base result. + """ + # request + resp1 = requests.post(api_url, headers=headers, json=consistent_payload) + assert resp1.status_code == 200 + result1 = resp1.json() + content1 = result1["choices"][0]["message"]["content"] + file_res_temp = "Qwen2.5-VL-7B-Instruct-temp" + f_o = open(file_res_temp, "a") + f_o.writelines(content1) + f_o.close() + + # base result + content2 = "这张图片展示了一群人在进行手工艺活动。前景中有两个孩子和一个成年人，他们似乎在制作或展示某种手工艺品。成年人手里拿着一个扇子，上面有彩色的图案，可能是通过某种方式绘制或涂鸦而成。孩子们看起来很专注，可能是在观察或参与这个过程。\n\n背景中还有其他几个人，其中一个人穿着粉色的衣服，背对着镜头。整个场景看起来像是在一个室内环境中，光线充足，氛围轻松愉快。" + + # Verify that result is same as the base result + assert content1 == content2 + + +# ========================== +# OpenAI Client Chat Completion Test +# ========================== + + +@pytest.fixture +def openai_client(): + ip = "0.0.0.0" + service_http_port = str(FD_API_PORT) + client = openai.Client( + base_url=f"http://{ip}:{service_http_port}/v1", + api_key="EMPTY_API_KEY", + ) + return client + + +# Non-streaming test +def test_non_streaming_chat(openai_client): + """Test non-streaming chat functionality with the local service""" + response = openai_client.chat.completions.create( + model="default", + messages=[ + { + "role": "system", + "content": "You are a helpful AI assistant.", + }, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://ku.baidu-int.com/vk-assets-ltd/space/2024/09/13/933d1e0a0760498e94ec0f2ccee865e0", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + stream=False, + ) + + assert hasattr(response, "choices") + assert len(response.choices) > 0 + assert hasattr(response.choices[0], "message") + assert hasattr(response.choices[0].message, "content") + + +# Streaming test +def test_streaming_chat(openai_client, capsys): + """Test streaming chat functionality with the local service""" + response = openai_client.chat.completions.create( + model="default", + messages=[ + { + "role": "system", + "content": "You are a helpful AI assistant.", + }, # system不是必需，可选 + {"role": "user", "content": "List 3 countries and their capitals."}, + { + "role": "assistant", + "content": "China(Beijing), France(Paris), Australia(Canberra).", + }, + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://ku.baidu-int.com/vk-assets-ltd/space/2024/09/13/933d1e0a0760498e94ec0f2ccee865e0", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=512, + stream=True, + ) + + output = [] + for chunk in response: + if hasattr(chunk.choices[0], "delta") and hasattr(chunk.choices[0].delta, "content"): + output.append(chunk.choices[0].delta.content) + assert len(output) > 2 + + +# ========================== +# OpenAI Client additional chat/completions test +# ========================== + + +def test_non_streaming_chat_with_return_token_ids(openai_client, capsys): + """ + Test return_token_ids option in non-streaming chat functionality with the local service + """ + # 设定 return_token_ids + response = openai_client.chat.completions.create( + model="default", + messages=[ + {"role": "system", "content": "You are a helpful AI assistant."}, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://paddlenlp.bj.bcebos.com/datasets/paddlemix/demo_images/example2.jpg", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + extra_body={"return_token_ids": True}, + stream=False, + ) + assert hasattr(response, "choices") + assert len(response.choices) > 0 + assert hasattr(response.choices[0], "message") + assert hasattr(response.choices[0].message, "prompt_token_ids") + assert isinstance(response.choices[0].message.prompt_token_ids, list) + assert hasattr(response.choices[0].message, "completion_token_ids") + assert isinstance(response.choices[0].message.completion_token_ids, list) + + # 不设定 return_token_ids + response = openai_client.chat.completions.create( + model="default", + messages=[ + {"role": "system", "content": "You are a helpful AI assistant."}, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://paddlenlp.bj.bcebos.com/datasets/paddlemix/demo_images/example2.jpg", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + extra_body={"return_token_ids": False}, + stream=False, + ) + assert hasattr(response, "choices") + assert len(response.choices) > 0 + assert hasattr(response.choices[0], "message") + assert hasattr(response.choices[0].message, "prompt_token_ids") + assert response.choices[0].message.prompt_token_ids is None + assert hasattr(response.choices[0].message, "completion_token_ids") + assert response.choices[0].message.completion_token_ids is None + + +def test_streaming_chat_with_return_token_ids(openai_client, capsys): + """ + Test return_token_ids option in streaming chat functionality with the local service + """ + # enable return_token_ids + response = openai_client.chat.completions.create( + model="default", + messages=[ + {"role": "system", "content": "You are a helpful AI assistant."}, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://paddlenlp.bj.bcebos.com/datasets/paddlemix/demo_images/example2.jpg", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + extra_body={"return_token_ids": True}, + stream=True, + ) + is_first_chunk = True + for chunk in response: + assert hasattr(chunk, "choices") + assert len(chunk.choices) > 0 + assert hasattr(chunk.choices[0], "delta") + assert hasattr(chunk.choices[0].delta, "prompt_token_ids") + assert hasattr(chunk.choices[0].delta, "completion_token_ids") + if is_first_chunk: + is_first_chunk = False + assert isinstance(chunk.choices[0].delta.prompt_token_ids, list) + assert chunk.choices[0].delta.completion_token_ids is None + else: + assert chunk.choices[0].delta.prompt_token_ids is None + assert isinstance(chunk.choices[0].delta.completion_token_ids, list) + + # disable return_token_ids + response = openai_client.chat.completions.create( + model="default", + messages=[ + {"role": "system", "content": "You are a helpful AI assistant."}, # system不是必需，可选 + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "https://paddlenlp.bj.bcebos.com/datasets/paddlemix/demo_images/example2.jpg", + "detail": "high", + }, + }, + {"type": "text", "text": "请描述图片内容"}, + ], + }, + ], + temperature=1, + max_tokens=53, + extra_body={"return_token_ids": False}, + stream=True, + ) + for chunk in response: + assert hasattr(chunk, "choices") + assert len(chunk.choices) > 0 + assert hasattr(chunk.choices[0], "delta") + assert hasattr(chunk.choices[0].delta, "prompt_token_ids") + assert chunk.choices[0].delta.prompt_token_ids is None + assert hasattr(chunk.choices[0].delta, "completion_token_ids") + assert chunk.choices[0].delta.completion_token_ids is None + + +def test_profile_reset_block_num(): + """测试profile reset_block_num功能，与baseline diff不能超过15%""" + log_file = "./log/config.log" + baseline = 30000 + + if not os.path.exists(log_file): + pytest.fail(f"Log file not found: {log_file}") + + with open(log_file, "r") as f: + log_lines = f.readlines() + + target_line = None + for line in log_lines: + if "Reset block num" in line: + target_line = line.strip() + break + + if target_line is None: + pytest.fail("日志中没有Reset block num信息") + + match = re.search(r"total_block_num:(\d+)", target_line) + if not match: + pytest.fail(f"Failed to extract total_block_num from line: {target_line}") + + try: + actual_value = int(match.group(1)) + except ValueError: + pytest.fail(f"Invalid number format: {match.group(1)}") + + lower_bound = baseline * (1 - 0.15) + upper_bound = baseline * (1 + 0.15) + print(f"Reset total_block_num: {actual_value}. baseline: {baseline}") + + assert lower_bound <= actual_value <= upper_bound, ( + f"Reset total_block_num {actual_value} 与 baseline {baseline} diff需要在5%以内" + f"Allowed range: [{lower_bound:.1f}, {upper_bound:.1f}]" + )