[CI/Build] Consolidate model loader tests and requirements (#25765)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2025-09-27 12:45:20 +08:00
committed by GitHub
parent c242c98031
commit d346ec695e
20 changed files with 48 additions and 90 deletions

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# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm import SamplingParams
from vllm.config.load import LoadConfig
from vllm.model_executor.model_loader import get_model_loader
load_format = "runai_streamer"
test_model = "openai-community/gpt2"
prompts = [
"Hello, my name is",
"The president of the United States is",
"The capital of France is",
"The future of AI is",
]
# Create a sampling params object.
sampling_params = SamplingParams(temperature=0.8, top_p=0.95, seed=0)
def get_runai_model_loader():
load_config = LoadConfig(load_format=load_format)
return get_model_loader(load_config)
def test_get_model_loader_with_runai_flag():
model_loader = get_runai_model_loader()
assert model_loader.__class__.__name__ == "RunaiModelStreamerLoader"
def test_runai_model_loader_download_files(vllm_runner):
with vllm_runner(test_model, load_format=load_format) as llm:
deserialized_outputs = llm.generate(prompts, sampling_params)
assert deserialized_outputs

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# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import glob
import os
import tempfile
import huggingface_hub.constants
from vllm.model_executor.model_loader.weight_utils import (
download_weights_from_hf)
from vllm.transformers_utils.runai_utils import (is_runai_obj_uri,
list_safetensors)
def test_is_runai_obj_uri():
assert is_runai_obj_uri("gs://some-gcs-bucket/path")
assert is_runai_obj_uri("s3://some-s3-bucket/path")
assert not is_runai_obj_uri("nfs://some-nfs-path")
def test_runai_list_safetensors_local():
with tempfile.TemporaryDirectory() as tmpdir:
huggingface_hub.constants.HF_HUB_OFFLINE = False
download_weights_from_hf("openai-community/gpt2",
allow_patterns=["*.safetensors", "*.json"],
cache_dir=tmpdir)
safetensors = glob.glob(f"{tmpdir}/**/*.safetensors", recursive=True)
assert len(safetensors) > 0
parentdir = [
os.path.dirname(safetensor) for safetensor in safetensors
][0]
files = list_safetensors(parentdir)
assert len(safetensors) == len(files)
if __name__ == "__main__":
test_is_runai_obj_uri()
test_runai_list_safetensors_local()

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# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import glob
import tempfile
import huggingface_hub.constants
import torch
from vllm.model_executor.model_loader.weight_utils import (
download_weights_from_hf, runai_safetensors_weights_iterator,
safetensors_weights_iterator)
def test_runai_model_loader():
with tempfile.TemporaryDirectory() as tmpdir:
huggingface_hub.constants.HF_HUB_OFFLINE = False
download_weights_from_hf("openai-community/gpt2",
allow_patterns=["*.safetensors"],
cache_dir=tmpdir)
safetensors = glob.glob(f"{tmpdir}/**/*.safetensors", recursive=True)
assert len(safetensors) > 0
runai_model_streamer_tensors = {}
hf_safetensors_tensors = {}
for name, tensor in runai_safetensors_weights_iterator(
safetensors, True):
runai_model_streamer_tensors[name] = tensor
for name, tensor in safetensors_weights_iterator(safetensors, True):
hf_safetensors_tensors[name] = tensor
assert len(runai_model_streamer_tensors) == len(hf_safetensors_tensors)
for name, runai_tensor in runai_model_streamer_tensors.items():
assert runai_tensor.dtype == hf_safetensors_tensors[name].dtype
assert runai_tensor.shape == hf_safetensors_tensors[name].shape
assert torch.all(runai_tensor.eq(hf_safetensors_tensors[name]))
if __name__ == "__main__":
test_runai_model_loader()