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https://github.com/huggingface/text-generation-inference.git
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c9d68945cc
* Prepare for release 3.1.0 * Back on main flake. * Fixing stuff. * Upgrade to moe-kernels 0.8.2 for Hip support. * Deactivating the flaky test.
64 lines
1.9 KiB
Python
64 lines
1.9 KiB
Python
import pytest
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@pytest.fixture(scope="module")
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def flash_starcoder_gptq_handle(launcher):
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with launcher("Narsil/starcoder-gptq", num_shard=2, quantize="gptq") as handle:
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yield handle
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@pytest.fixture(scope="module")
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async def flash_starcoder_gptq(flash_starcoder_gptq_handle):
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await flash_starcoder_gptq_handle.health(300)
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return flash_starcoder_gptq_handle.client
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@pytest.mark.release
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@pytest.mark.asyncio
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async def test_flash_starcoder_gptq(flash_starcoder_gptq, generous_response_snapshot):
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response = await flash_starcoder_gptq.generate(
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"def geometric_mean(L: List[float]):",
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max_new_tokens=20,
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decoder_input_details=True,
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)
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assert response.details.generated_tokens == 2
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assert response == generous_response_snapshot
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# Deactivated because it's flaky
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# Only this model seems affected and it's only a logprob precision issue.
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# @pytest.mark.release
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# @pytest.mark.asyncio
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# async def test_flash_starcoder_gptq_default_params(
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# flash_starcoder_gptq, generous_response_snapshot
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# ):
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# response = await flash_starcoder_gptq.generate(
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# "def geometric_mean(L: List[float]):",
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# max_new_tokens=20,
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# temperature=0.2,
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# top_p=0.95,
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# decoder_input_details=True,
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# seed=0,
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# )
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# assert response.details.generated_tokens == 2
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# assert response == generous_response_snapshot
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@pytest.mark.release
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@pytest.mark.asyncio
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async def test_flash_starcoder_gptq_load(
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flash_starcoder_gptq, generate_load, generous_response_snapshot
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):
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responses = await generate_load(
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flash_starcoder_gptq,
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"def geometric_mean(L: List[float]):",
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max_new_tokens=10,
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n=4,
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)
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assert len(responses) == 4
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# XXX: TODO: Fix this test.
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# assert all([r.generated_text == responses[0].generated_text for r in responses])
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# assert responses == generous_response_snapshot
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