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[Misc] Modify the organization of GLM series (#22171)

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Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>
This commit is contained in:
Jee Jee Li
2025-08-04 14:51:20 +08:00
committed by GitHub
parent 8ecb3e9e93
commit a7b8788d2c
16 changed files with 31 additions and 31 deletions
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4
tests/distributed/test_pipeline_parallel.py
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@@ -154,7 +154,7 @@ TEXT_GENERATION_MODELS = {
"baichuan-inc/Baichuan-7B": PPTestSettings.fast(),
"baichuan-inc/Baichuan2-13B-Chat": PPTestSettings.fast(),
"bigscience/bloomz-1b1": PPTestSettings.fast(),
"THUDM/chatglm3-6b": PPTestSettings.fast(),
"zai-org/chatglm3-6b": PPTestSettings.fast(),
"CohereForAI/c4ai-command-r-v01": PPTestSettings.fast(load_format="dummy"),
"databricks/dbrx-instruct": PPTestSettings.fast(load_format="dummy"),
"Deci/DeciLM-7B-instruct": PPTestSettings.fast(),
@@ -224,7 +224,7 @@ MULTIMODAL_MODELS = {
"Salesforce/blip2-opt-6.7b": PPTestSettings.fast(),
"facebook/chameleon-7b": PPTestSettings.fast(),
"adept/fuyu-8b": PPTestSettings.fast(),
"THUDM/glm-4v-9b": PPTestSettings.fast(),
"zai-org/glm-4v-9b": PPTestSettings.fast(),
"OpenGVLab/InternVL2-1B": PPTestSettings.fast(),
"llava-hf/llava-1.5-7b-hf": PPTestSettings.fast(),
"llava-hf/llava-v1.6-mistral-7b-hf": PPTestSettings.fast(),

2
tests/lora/test_add_lora.py
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@@ -14,7 +14,7 @@ from vllm.lora.request import LoRARequest
from vllm.sampling_params import SamplingParams
from vllm.utils import merge_async_iterators
MODEL_PATH = "THUDM/chatglm3-6b"
MODEL_PATH = "zai-org/chatglm3-6b"
LORA_RANK = 64
DEFAULT_MAX_LORAS = 4 * 3

2
tests/lora/test_chatglm3_tp.py
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@@ -6,7 +6,7 @@ from vllm.lora.request import LoRARequest
from ..utils import create_new_process_for_each_test, multi_gpu_test
MODEL_PATH = "THUDM/chatglm3-6b"
MODEL_PATH = "zai-org/chatglm3-6b"
PROMPT_TEMPLATE = """I want you to act as a SQL terminal in front of an example database, you need only to return the sql command to me.Below is an instruction that describes a task, Write a response that appropriately completes the request.\n"\n##Instruction:\nconcert_singer contains tables such as stadium, singer, concert, singer_in_concert. Table stadium has columns such as Stadium_ID, Location, Name, Capacity, Highest, Lowest, Average. Stadium_ID is the primary key.\nTable singer has columns such as Singer_ID, Name, Country, Song_Name, Song_release_year, Age, Is_male. Singer_ID is the primary key.\nTable concert has columns such as concert_ID, concert_Name, Theme, Stadium_ID, Year. concert_ID is the primary key.\nTable singer_in_concert has columns such as concert_ID, Singer_ID. concert_ID is the primary key.\nThe Stadium_ID of concert is the foreign key of Stadium_ID of stadium.\nThe Singer_ID of singer_in_concert is the foreign key of Singer_ID of singer.\nThe concert_ID of singer_in_concert is the foreign key of concert_ID of concert.\n\n###Input:\n{query}\n\n###Response:""" # noqa: E501

2
tests/models/language/generation/test_common.py
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@@ -53,7 +53,7 @@ AITER_MODEL_LIST = [
marks=[pytest.mark.core_model, pytest.mark.cpu_model],
),
pytest.param(
"THUDM/chatglm3-6b", # chatglm (text-only)
"zai-org/chatglm3-6b", # chatglm (text-only)
),
pytest.param(
"meta-llama/Llama-3.2-1B-Instruct", # llama

6
tests/models/multimodal/generation/test_common.py
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@@ -355,7 +355,7 @@ VLM_TEST_SETTINGS = {
num_logprobs=10,
),
"glm4v": VLMTestInfo(
models=["THUDM/glm-4v-9b"],
models=["zai-org/glm-4v-9b"],
test_type=VLMTestType.IMAGE,
prompt_formatter=lambda img_prompt: f"<|user|>\n{img_prompt}<|assistant|>", # noqa: E501
single_image_prompts=IMAGE_ASSETS.prompts({
@@ -374,7 +374,7 @@ VLM_TEST_SETTINGS = {
marks=[large_gpu_mark(min_gb=32)],
),
"glm4_1v": VLMTestInfo(
models=["THUDM/GLM-4.1V-9B-Thinking"],
models=["zai-org/GLM-4.1V-9B-Thinking"],
test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
prompt_formatter=lambda img_prompt: f"<|user|>\n{img_prompt}<|assistant|>", # noqa: E501
img_idx_to_prompt=lambda idx: "<|begin_of_image|><|image|><|end_of_image|>", # noqa: E501
@@ -388,7 +388,7 @@ VLM_TEST_SETTINGS = {
marks=[large_gpu_mark(min_gb=32)],
),
"glm4_1v-video": VLMTestInfo(
models=["THUDM/GLM-4.1V-9B-Thinking"],
models=["zai-org/GLM-4.1V-9B-Thinking"],
# GLM4.1V require include video metadata for input
test_type=VLMTestType.CUSTOM_INPUTS,
max_model_len=4096,

4
tests/models/multimodal/processing/test_common.py
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@@ -271,8 +271,8 @@ def _test_processing_correctness_one(
"microsoft/Florence-2-base",
"adept/fuyu-8b",
"google/gemma-3-4b-it",
"THUDM/glm-4v-9b",
"THUDM/GLM-4.1V-9B-Thinking",
"zai-org/glm-4v-9b",
"zai-org/GLM-4.1V-9B-Thinking",
"ibm-granite/granite-speech-3.3-2b",
"h2oai/h2ovl-mississippi-800m",
"internlm/Intern-S1",

2
tests/models/multimodal/processing/test_glm4_1v.py
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@@ -9,7 +9,7 @@ from vllm.multimodal import MULTIMODAL_REGISTRY
from ...utils import build_model_context
@pytest.mark.parametrize("model_id", ["THUDM/GLM-4.1V-9B-Thinking"])
@pytest.mark.parametrize("model_id", ["zai-org/GLM-4.1V-9B-Thinking"])
@pytest.mark.parametrize("expected_toks_per_frame", [299])
@pytest.mark.parametrize("num_frames", [32, 128])
@pytest.mark.parametrize("fps, expected_grid_t", [(1, 5), (2, 10)])

10
tests/models/registry.py
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@@ -153,7 +153,7 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
extras={"tiny": "hmellor/tiny-random-BambaForCausalLM"}), # noqa: E501
"BloomForCausalLM": _HfExamplesInfo("bigscience/bloom-560m",
{"1b": "bigscience/bloomz-1b1"}),
"ChatGLMModel": _HfExamplesInfo("THUDM/chatglm3-6b",
"ChatGLMModel": _HfExamplesInfo("zai-org/chatglm3-6b",
trust_remote_code=True,
max_transformers_version="4.48"),
"ChatGLMForConditionalGeneration": _HfExamplesInfo("thu-coai/ShieldLM-6B-chatglm3", # noqa: E501
@@ -187,8 +187,8 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
"Gemma3ForCausalLM": _HfExamplesInfo("google/gemma-3-1b-it"),
"Gemma3nForConditionalGeneration": _HfExamplesInfo("google/gemma-3n-E2B-it", # noqa: E501
min_transformers_version="4.53"),
"GlmForCausalLM": _HfExamplesInfo("THUDM/glm-4-9b-chat-hf"),
"Glm4ForCausalLM": _HfExamplesInfo("THUDM/GLM-4-9B-0414"),
"GlmForCausalLM": _HfExamplesInfo("zai-org/glm-4-9b-chat-hf"),
"Glm4ForCausalLM": _HfExamplesInfo("zai-org/GLM-4-9B-0414"),
"Glm4MoeForCausalLM": _HfExamplesInfo("zai-org/GLM-4.5",
min_transformers_version="4.54"), # noqa: E501
"GPT2LMHeadModel": _HfExamplesInfo("openai-community/gpt2",
@@ -380,10 +380,10 @@ _MULTIMODAL_EXAMPLE_MODELS = {
"FuyuForCausalLM": _HfExamplesInfo("adept/fuyu-8b"),
"Gemma3ForConditionalGeneration": _HfExamplesInfo("google/gemma-3-4b-it"),
"GraniteSpeechForConditionalGeneration": _HfExamplesInfo("ibm-granite/granite-speech-3.3-2b"), # noqa: E501
"GLM4VForCausalLM": _HfExamplesInfo("THUDM/glm-4v-9b",
"GLM4VForCausalLM": _HfExamplesInfo("zai-org/glm-4v-9b",
trust_remote_code=True,
hf_overrides={"architectures": ["GLM4VForCausalLM"]}), # noqa: E501
"Glm4vForConditionalGeneration": _HfExamplesInfo("THUDM/GLM-4.1V-9B-Thinking"), # noqa: E501
"Glm4vForConditionalGeneration": _HfExamplesInfo("zai-org/GLM-4.1V-9B-Thinking"), # noqa: E501
"Glm4v_moeForConditionalGeneration": _HfExamplesInfo("zai-org/GLM-4.5V-Air",
is_available_online=False), # noqa: E501
"H2OVLChatModel": _HfExamplesInfo("h2oai/h2ovl-mississippi-800m",

2
tests/tokenization/test_cached_tokenizer.py
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@@ -10,7 +10,7 @@ from vllm.transformers_utils.tokenizer import (AnyTokenizer,
get_cached_tokenizer)
@pytest.mark.parametrize("model_id", ["gpt2", "THUDM/chatglm3-6b"])
@pytest.mark.parametrize("model_id", ["gpt2", "zai-org/chatglm3-6b"])
def test_cached_tokenizer(model_id: str):
reference_tokenizer = AutoTokenizer.from_pretrained(model_id,
trust_remote_code=True)