69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
import pytest
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@pytest.fixture(scope="module")
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def fused_kernel_mamba_handle(launcher):
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with launcher("state-spaces/mamba-130m", num_shard=1) as handle:
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yield handle
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@pytest.fixture(scope="module")
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async def fused_kernel_mamba(fused_kernel_mamba_handle):
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await fused_kernel_mamba_handle.health(300)
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return fused_kernel_mamba_handle.client
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@pytest.mark.asyncio
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@pytest.mark.private
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async def test_mamba(fused_kernel_mamba, response_snapshot):
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response = await fused_kernel_mamba.generate(
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"What is Deep Learning?", max_new_tokens=10
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)
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assert response.details.generated_tokens == 10
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assert response.generated_text == "\n\nDeep learning is a new type of machine"
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assert response == response_snapshot
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@pytest.mark.asyncio
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@pytest.mark.private
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async def test_mamba_all_params(fused_kernel_mamba, response_snapshot):
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response = await fused_kernel_mamba.generate(
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"blue, red, yellow, ",
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max_new_tokens=10,
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repetition_penalty=1.2,
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return_full_text=True,
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stop_sequences=["test"],
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temperature=0.5,
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top_p=0.9,
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top_k=10,
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truncate=5,
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typical_p=0.9,
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watermark=True,
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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 == 10
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assert (
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response.generated_text
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== "blue, red, yellow, \nand blue colors. A number of different color"
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)
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assert response == response_snapshot
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@pytest.mark.asyncio
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@pytest.mark.private
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async def test_mamba_load(
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fused_kernel_mamba, generate_load, generous_response_snapshot
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):
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responses = await generate_load(
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fused_kernel_mamba, "What is Deep Learning?", max_new_tokens=10, n=4
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)
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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])
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assert responses[0].generated_text == "\n\nDeep learning is a new type of machine"
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assert responses == generous_response_snapshot
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