hf_text-generation-inference/integration-tests/models/test_flash_medusa.py

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import pytest
@pytest.fixture(scope="module")
def flash_medusa_handle(launcher):
with launcher("FasterDecoding/medusa-vicuna-7b-v1.3", num_shard=2) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_medusa(flash_medusa_handle):
await flash_medusa_handle.health(300)
return flash_medusa_handle.client
@pytest.mark.asyncio
@pytest.mark.private
async def test_flash_medusa_simple(flash_medusa, response_snapshot):
response = await flash_medusa.generate(
"What is Deep Learning?", max_new_tokens=10, decoder_input_details=True
)
assert response.details.generated_tokens == 10
assert response == response_snapshot
@pytest.mark.asyncio
@pytest.mark.private
async def test_flash_medusa_all_params(flash_medusa, response_snapshot):
response = await flash_medusa.generate(
"What is Deep Learning?",
max_new_tokens=10,
repetition_penalty=1.2,
return_full_text=True,
stop_sequences=["test"],
temperature=0.5,
top_p=0.9,
top_k=10,
truncate=5,
typical_p=0.9,
watermark=True,
decoder_input_details=True,
seed=0,
)
assert response.details.generated_tokens == 10
assert response == response_snapshot
@pytest.mark.asyncio
@pytest.mark.private
async def test_flash_medusa_load(flash_medusa, generate_load, response_snapshot):
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responses = await generate_load(
flash_medusa, "What is Deep Learning?", max_new_tokens=10, n=4
)
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assert len(responses) == 4
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assert all(
[r.generated_text == responses[0].generated_text for r in responses]
), f"{[r.generated_text for r in responses]}"
assert (
responses[0].generated_text == "\nDeep learning is a subset of machine learning"
)
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assert responses == response_snapshot