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tests/runai_model_streamer/test_runai_model_streamer_loader.py
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from vllm import SamplingParams | ||
from vllm.config import LoadConfig, LoadFormat | ||
from vllm.model_executor.model_loader.loader import (RunaiModelStreamerLoader, | ||
get_model_loader) | ||
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test_model = "openai-community/gpt2" | ||
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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) | ||
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def get_runai_model_loader(): | ||
load_config = LoadConfig(load_format=LoadFormat.RUNAI_STREAMER) | ||
return get_model_loader(load_config) | ||
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def test_get_model_loader_with_runai_flag(): | ||
model_loader = get_runai_model_loader() | ||
assert isinstance(model_loader, RunaiModelStreamerLoader) | ||
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def test_runai_model_loader_download_files(vllm_runner): | ||
with vllm_runner(test_model, load_format=LoadFormat.RUNAI_STREAMER) as llm: | ||
deserialized_outputs = llm.generate(prompts, sampling_params) | ||
assert deserialized_outputs |
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import glob | ||
import tempfile | ||
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import huggingface_hub.constants | ||
import torch | ||
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from vllm.model_executor.model_loader.weight_utils import ( | ||
download_weights_from_hf, runai_safetensors_weights_iterator, | ||
safetensors_weights_iterator) | ||
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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 | ||
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runai_model_streamer_tensors = {} | ||
hf_safetensors_tensors = {} | ||
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for name, tensor in runai_safetensors_weights_iterator(safetensors): | ||
runai_model_streamer_tensors[name] = tensor | ||
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for name, tensor in safetensors_weights_iterator(safetensors): | ||
hf_safetensors_tensors[name] = tensor | ||
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assert len(runai_model_streamer_tensors) == len(hf_safetensors_tensors) | ||
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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])) | ||
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if __name__ == "__main__": | ||
test_runai_model_loader() |
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