HAIAI aee76334d9
[amd_dev] branch rebase (#25753)
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151 lines
5.7 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from typing import Optional
import pytest
from vllm import SamplingParams
from vllm.assets.audio import AudioAsset
from ....conftest import VllmRunner
from ....utils import create_new_process_for_each_test, multi_gpu_test
PROMPTS = [
{
"prompt":
"<|startoftranscript|><|en|><|transcribe|><|notimestamps|>",
"multi_modal_data": {
"audio": AudioAsset("mary_had_lamb").audio_and_sample_rate,
},
},
{ # Test explicit encoder/decoder prompt
"encoder_prompt": {
"prompt": "",
"multi_modal_data": {
"audio": AudioAsset("winning_call").audio_and_sample_rate,
},
},
"decoder_prompt":
"<|startoftranscript|><|en|><|transcribe|><|notimestamps|>",
}
]
EXPECTED = {
"openai/whisper-tiny": [
" He has birth words I spoke in the original corner of that. And a"
" little piece of black coat poetry. Mary had a little sandwich,"
" sweet, with white and snow. And everyone had it very went the last"
" would sure to go.",
" >> And the old one, fit John the way to Edgar Martinez. >> One more"
" to line down the field line for our base camp. Here comes joy. Here"
" is June and the third base. They're going to wave him in. The throw"
" to the plate will be late. The Mariners are going to play for the"
" American League Championship. I don't believe it. It just continues"
" by all five."
],
"openai/whisper-small": [
" The first words I spoke in the original pornograph. A little piece"
" of practical poetry. Mary had a little lamb, its fleece was quite a"
" slow, and everywhere that Mary went the lamb was sure to go.",
" And the old one pitch on the way to Edgar Martinez one month. Here"
" comes joy. Here is Junior to third base. They're gonna wave him"
" in. The throw to the plate will be late. The Mariners are going to"
" play for the American League Championship. I don't believe it. It"
" just continues. My, oh my."
],
"openai/whisper-medium": [
" The first words I spoke in the original phonograph, a little piece"
" of practical poetry. Mary had a little lamb, its fleece was quite as"
" slow, and everywhere that Mary went the lamb was sure to go.",
" And the 0-1 pitch on the way to Edgar Martinez swung on the line"
" down the left field line for Obeyshev. Here comes Joy. Here is"
" Jorgen at third base. They're going to wave him in. The throw to the"
" plate will be late. The Mariners are going to play for the American"
" League Championship. I don't believe it. It just continues. My, oh"
" my."
],
"openai/whisper-large-v3": [
" The first words I spoke in the original phonograph, a little piece"
" of practical poetry. Mary had a little lamb, its feet were quite as"
" slow, and everywhere that Mary went, the lamb was sure to go.",
" And the 0-1 pitch on the way to Edgar Martinez. Swung on the line."
" Now the left field line for a base hit. Here comes Joy. Here is"
" Junior to third base. They're going to wave him in. The throw to the"
" plate will be late. The Mariners are going to play for the American"
" League Championship. I don't believe it. It just continues. My, oh,"
" my."
],
"openai/whisper-large-v3-turbo": [
" The first words I spoke in the original phonograph, a little piece"
" of practical poetry. Mary had a little lamb, its streets were quite"
" as slow, and everywhere that Mary went the lamb was sure to go.",
" And the 0-1 pitch on the way to Edgar Martinez. Swung on the line"
" down the left field line for a base hit. Here comes Joy. Here is"
" Junior to third base. They're going to wave him in. The throw to the"
" plate will be late. The Mariners are going to play for the American"
" League Championship. I don't believe it. It just continues. My, oh,"
" my."
]
}
def run_test(
vllm_runner: type[VllmRunner],
model: str,
*,
tensor_parallel_size: int,
distributed_executor_backend: Optional[str] = None,
) -> None:
prompt_list = PROMPTS * 10
expected_list = EXPECTED[model] * 10
with vllm_runner(
model,
dtype="half",
max_model_len=448,
tensor_parallel_size=tensor_parallel_size,
distributed_executor_backend=distributed_executor_backend,
) as vllm_model:
llm = vllm_model.llm
sampling_params = SamplingParams(
temperature=0,
top_p=1.0,
max_tokens=200,
)
outputs = llm.generate(prompt_list, sampling_params)
for output, expected in zip(outputs, expected_list):
print(output.outputs[0].text)
assert output.outputs[0].text == expected
@pytest.mark.core_model
@pytest.mark.parametrize("model", ["openai/whisper-large-v3-turbo"])
@create_new_process_for_each_test()
def test_models(vllm_runner, model) -> None:
run_test(
vllm_runner,
model,
tensor_parallel_size=1,
)
@multi_gpu_test(num_gpus=2)
@pytest.mark.core_model
@pytest.mark.parametrize("model", ["openai/whisper-large-v3-turbo"])
@pytest.mark.parametrize("distributed_executor_backend", ["ray", "mp"])
@create_new_process_for_each_test()
def test_models_distributed(
vllm_runner,
model,
distributed_executor_backend,
) -> None:
run_test(
vllm_runner,
model,
tensor_parallel_size=2,
distributed_executor_backend=distributed_executor_backend,
)