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

65 lines
1.8 KiB
Python

import pytest
@pytest.fixture(scope="module")
def flash_gemma_gptq_handle(launcher):
with launcher("TechxGenus/gemma-2b-GPTQ", num_shard=1, quantize="gptq") as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_gemma_gptq(flash_gemma_gptq_handle):
await flash_gemma_gptq_handle.health(300)
return flash_gemma_gptq_handle.client
@pytest.mark.asyncio
@pytest.mark.private
async def test_flash_gemma_gptq(flash_gemma_gptq, ignore_logprob_response_snapshot):
response = await flash_gemma_gptq.generate(
"Test request", max_new_tokens=10, decoder_input_details=True
)
assert response.details.generated_tokens == 10
assert response == ignore_logprob_response_snapshot
@pytest.mark.asyncio
@pytest.mark.private
async def test_flash_gemma_gptq_all_params(
flash_gemma_gptq, ignore_logprob_response_snapshot
):
response = await flash_gemma_gptq.generate(
"Test request",
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 == ignore_logprob_response_snapshot
@pytest.mark.asyncio
@pytest.mark.private
async def test_flash_gemma_gptq_load(
flash_gemma_gptq, generate_load, ignore_logprob_response_snapshot
):
responses = await generate_load(
flash_gemma_gptq, "Test request", 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 == ignore_logprob_response_snapshot