Logits Processing

For general TensorRT-LLM features and configuration, see the Reference Guide.

Logits processors let you modify the next-token logits at every decoding step (e.g., to apply custom constraints or sampling transforms). Dynamo provides a backend-agnostic interface and an adapter for TensorRT-LLM so you can plug in custom processors.

How it works

• Interface: Implement dynamo.logits_processing.BaseLogitsProcessor which defines __call__(input_ids, logits) and modifies logits in-place.
• TRT-LLM adapter: Use dynamo.trtllm.logits_processing.adapter.create_trtllm_adapters(...) to convert Dynamo processors into TRT-LLM-compatible processors and assign them to SamplingParams.logits_processor.
• Examples: See example processors in lib/bindings/python/src/dynamo/logits_processing/examples/ (temperature, hello_world).

Quick test: HelloWorld processor

You can enable a test-only processor that forces the model to respond with “Hello world!”. This is useful to verify the wiring without modifying your model or engine code.

$
cd $DYNAMO_HOME/examples/backends/trtllm
$
export DYNAMO_ENABLE_TEST_LOGITS_PROCESSOR=1
$
./launch/agg.sh

Bring your own processor

Implement a processor by conforming to BaseLogitsProcessor and modify logits in-place. For example, temperature scaling:

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from typing import Sequence
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import torch
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from dynamo.logits_processing import BaseLogitsProcessor
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class TemperatureProcessor(BaseLogitsProcessor):
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    def __init__(self, temperature: float = 1.0):
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        if temperature <= 0:
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            raise ValueError("Temperature must be positive")
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        self.temperature = temperature
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    def __call__(self, input_ids: Sequence[int], logits: torch.Tensor):
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        if self.temperature == 1.0:
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            return
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        logits.div_(self.temperature)

Wire it into TRT-LLM by adapting and attaching to SamplingParams:

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from dynamo.trtllm.logits_processing.adapter import create_trtllm_adapters
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from dynamo.logits_processing.examples import TemperatureProcessor
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processors = [TemperatureProcessor(temperature=0.7)]
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sampling_params.logits_processor = create_trtllm_adapters(processors)

Current limitations

• Per-request processing only (batch size must be 1); beam width > 1 is not supported.
• Processors must modify logits in-place and not return a new tensor.
• If your processor needs tokenization, ensure the tokenizer is initialized (do not skip tokenizer init).