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

67 lines
1.9 KiB
Python

import pytest
@pytest.fixture(scope="module")
def fused_kernel_mamba_handle(launcher):
with launcher("state-spaces/mamba-130m", num_shard=1) as handle:
yield handle
@pytest.fixture(scope="module")
async def fused_kernel_mamba(fused_kernel_mamba_handle):
await fused_kernel_mamba_handle.health(300)
return fused_kernel_mamba_handle.client
@pytest.mark.asyncio
@pytest.mark.private
async def test_mamba(fused_kernel_mamba, response_snapshot):
response = await fused_kernel_mamba.generate(
"What is Deep Learning?", max_new_tokens=10
)
assert response.details.generated_tokens == 10
assert response.generated_text == "\n\nDeep learning is a new type of machine"
assert response == response_snapshot
@pytest.mark.asyncio
@pytest.mark.private
async def test_mamba_all_params(fused_kernel_mamba, response_snapshot):
response = await fused_kernel_mamba.generate(
"blue, red, yellow, ",
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.generated_text
== "blue, red, yellow, \nand orange (in the order they appear in"
)
assert response == response_snapshot
@pytest.mark.asyncio
@pytest.mark.private
async def test_mamba_load(fused_kernel_mamba, generate_load, response_snapshot):
responses = await generate_load(
fused_kernel_mamba, "What is Deep Learning?", max_new_tokens=10, n=4
)
assert len(responses) == 4
assert all([r.generated_text == responses[0].generated_text for r in responses])
assert responses[0].generated_text == "\n\nDeep learning is a new type of machine"
assert responses == response_snapshot