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fix: vllm missing logprobs (#5279)
* working to address missing items referencing #3436, #2930 - if i could test it, this might show that the output from the vllm backend is processed and returned to the user Signed-off-by: Wyatt Neal <wyatt.neal+git@gmail.com> * adding in vllm tests to test-extras Signed-off-by: Wyatt Neal <wyatt.neal+git@gmail.com> * adding in tests to pipeline for execution Signed-off-by: Wyatt Neal <wyatt.neal+git@gmail.com> * removing todo block, test via pipeline Signed-off-by: Wyatt Neal <wyatt.neal+git@gmail.com> --------- Signed-off-by: Wyatt Neal <wyatt.neal+git@gmail.com>
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4 changed files with 101 additions and 19 deletions
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@ -194,27 +194,40 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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await iterations.aclose()
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async def _predict(self, request, context, streaming=False):
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# Build the sampling parameters
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# NOTE: this must stay in sync with the vllm backend
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request_to_sampling_params = {
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"N": "n",
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"PresencePenalty": "presence_penalty",
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"FrequencyPenalty": "frequency_penalty",
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"RepetitionPenalty": "repetition_penalty",
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"Temperature": "temperature",
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"TopP": "top_p",
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"TopK": "top_k",
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"MinP": "min_p",
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"Seed": "seed",
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"StopPrompts": "stop",
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"StopTokenIds": "stop_token_ids",
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"BadWords": "bad_words",
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"IncludeStopStrInOutput": "include_stop_str_in_output",
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"IgnoreEOS": "ignore_eos",
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"Tokens": "max_tokens",
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"MinTokens": "min_tokens",
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"Logprobs": "logprobs",
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"PromptLogprobs": "prompt_logprobs",
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"SkipSpecialTokens": "skip_special_tokens",
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"SpacesBetweenSpecialTokens": "spaces_between_special_tokens",
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"TruncatePromptTokens": "truncate_prompt_tokens",
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"GuidedDecoding": "guided_decoding",
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}
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# Build sampling parameters
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sampling_params = SamplingParams(top_p=0.9, max_tokens=200)
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if request.TopP != 0:
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sampling_params.top_p = request.TopP
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if request.Tokens > 0:
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sampling_params.max_tokens = request.Tokens
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if request.Temperature != 0:
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sampling_params.temperature = request.Temperature
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if request.TopK != 0:
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sampling_params.top_k = request.TopK
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if request.PresencePenalty != 0:
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sampling_params.presence_penalty = request.PresencePenalty
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if request.FrequencyPenalty != 0:
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sampling_params.frequency_penalty = request.FrequencyPenalty
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if request.StopPrompts:
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sampling_params.stop = request.StopPrompts
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if request.IgnoreEOS:
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sampling_params.ignore_eos = request.IgnoreEOS
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if request.Seed != 0:
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sampling_params.seed = request.Seed
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for request_field, param_field in request_to_sampling_params.items():
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if hasattr(request, request_field):
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value = getattr(request, request_field)
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if value not in (None, 0, [], False):
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setattr(sampling_params, param_field, value)
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# Extract image paths and process images
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prompt = request.Prompt
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@ -75,6 +75,53 @@ class TestBackendServicer(unittest.TestCase):
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finally:
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self.tearDown()
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def test_sampling_params(self):
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"""
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This method tests if all sampling parameters are correctly processed
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NOTE: this does NOT test for correctness, just that we received a compatible response
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"""
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try:
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self.setUp()
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with grpc.insecure_channel("localhost:50051") as channel:
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stub = backend_pb2_grpc.BackendStub(channel)
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response = stub.LoadModel(backend_pb2.ModelOptions(Model="facebook/opt-125m"))
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self.assertTrue(response.success)
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req = backend_pb2.PredictOptions(
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Prompt="The capital of France is",
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TopP=0.8,
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Tokens=50,
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Temperature=0.7,
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TopK=40,
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PresencePenalty=0.1,
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FrequencyPenalty=0.2,
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RepetitionPenalty=1.1,
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MinP=0.05,
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Seed=42,
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StopPrompts=["\n"],
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StopTokenIds=[50256],
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BadWords=["badword"],
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IncludeStopStrInOutput=True,
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IgnoreEOS=True,
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MinTokens=5,
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Logprobs=5,
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PromptLogprobs=5,
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SkipSpecialTokens=True,
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SpacesBetweenSpecialTokens=True,
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TruncatePromptTokens=10,
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GuidedDecoding=True,
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N=2,
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)
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resp = stub.Predict(req)
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self.assertIsNotNone(resp.message)
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self.assertIsNotNone(resp.logprobs)
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except Exception as err:
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print(err)
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self.fail("sampling params service failed")
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finally:
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self.tearDown()
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def test_embedding(self):
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"""
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This method tests if the embeddings are generated successfully
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