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https://github.com/huggingface/text-generation-inference.git
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a785000842
compressed-tensors is a safetensors extension for sparse, quantized tensors. The format is more powerful than earlier AWQ/GPTQ/FP8 quantization, because - Different quantizer configurations can be used for different targets. - The format can specify input/output quantizers in addition to weight quantizers. - Configurable exclusions for quantization. This change adds a dependency on the `compressed-tensors` package for its configuration parsing and layer matching functionality. The following types of quantization are supported in this PR: - W8A16 and W4A16 INT using GPTQ-Marlin kernels. - W8A8 and W8A16 FP using FP8-Marlin and cutlass kernels. Support for other quantization types will be added in subsequent PRs.
87 lines
2.3 KiB
Python
87 lines
2.3 KiB
Python
import pytest
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@pytest.fixture(scope="module")
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def compressed_tensors_wna16_handle(launcher):
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with launcher(
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"neuralmagic/gemma-2-2b-it-quantized.w4a16",
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num_shard=2,
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quantize="compressed-tensors",
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) as handle:
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yield handle
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@pytest.fixture(scope="module")
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async def compressed_tensors_wna16(compressed_tensors_wna16_handle):
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await compressed_tensors_wna16_handle.health(300)
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return compressed_tensors_wna16_handle.client
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@pytest.mark.release
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@pytest.mark.asyncio
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@pytest.mark.private
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async def test_compressed_tensors_wna16(compressed_tensors_wna16, response_snapshot):
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response = await compressed_tensors_wna16.generate(
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"What is deep learning?",
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max_new_tokens=10,
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decoder_input_details=True,
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)
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assert (
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response.generated_text
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== "\n\nDeep learning is a subset of machine learning that"
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)
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assert response.details.generated_tokens == 10
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assert response == response_snapshot
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@pytest.mark.asyncio
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async def test_compressed_tensors_wna16_all_params(
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compressed_tensors_wna16, response_snapshot
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):
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response = await compressed_tensors_wna16.generate(
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"What is deep learning",
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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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== "What is deep learning?\n\nDeep Learning is a subset of machine learning"
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)
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assert response == response_snapshot
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@pytest.mark.release
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@pytest.mark.asyncio
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@pytest.mark.private
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async def test_compressed_tensors_wna16_load(
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compressed_tensors_wna16, generate_load, response_snapshot
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):
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responses = await generate_load(
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compressed_tensors_wna16,
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"What is deep learning?",
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max_new_tokens=10,
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n=4,
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)
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assert (
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responses[0].generated_text
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== "\n\nDeep learning is a subset of machine learning that"
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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 == response_snapshot
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