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

84 lines
2.2 KiB
Python

import pytest
from testing_utils import SYSTEM
@pytest.fixture(scope="module")
def flash_llama_awq_handle(launcher):
if SYSTEM == "rocm":
# On ROCm, for awq checkpoints, we need to use gptq kernel that supports ROCm.
quantize = "gptq"
elif SYSTEM == "xpu":
pytest.skip("AWQ is not supported on xpu")
else:
quantize = "awq"
with launcher(
"abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq",
num_shard=1,
quantize=quantize,
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_llama_awq(flash_llama_awq_handle):
await flash_llama_awq_handle.health()
return flash_llama_awq_handle.client
@pytest.mark.release
@pytest.mark.asyncio
async def test_flash_llama_awq(flash_llama_awq, response_snapshot):
response = await flash_llama_awq.generate(
"What is Deep Learning?", max_new_tokens=10, decoder_input_details=True
)
assert response.details.generated_tokens == 10
assert (
response.generated_text
== "\nWhat is the difference between Deep Learning and Machine"
)
assert response == response_snapshot
@pytest.mark.release
@pytest.mark.asyncio
async def test_flash_llama_awq_all_params(flash_llama_awq, response_snapshot):
response = await flash_llama_awq.generate(
"What is Deep Learning?",
max_new_tokens=10,
repetition_penalty=1.2,
return_full_text=True,
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.release
@pytest.mark.asyncio
async def test_flash_llama_awq_load(flash_llama_awq, generate_load, response_snapshot):
responses = await generate_load(
flash_llama_awq, "What is Deep Learning?", max_new_tokens=10, n=4
)
assert len(responses) == 4
assert all(
[
r.generated_text
== "\nWhat is the difference between Deep Learning and Machine"
for r in responses
]
)
assert responses == response_snapshot