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# Triton Model Analyzer
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**LATEST RELEASE: You are currently on the main branch which tracks
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under-development progress towards the next release. The latest
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release of the Triton Model Analyzer is 1.28.0 and is available on
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branch
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[r23.05](https://github.com/triton-inference-server/model_analyzer/tree/r23.05).**
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Triton Model Analyzer is a CLI tool which can help you find a more optimal configuration, on a given piece of hardware, for single, multiple, ensemble, or BLS models running on a [Triton Inference Server](https://github.com/triton-inference-server/server/). Model Analyzer will also generate reports to help you better understand the trade-offs of the different configurations along with their compute and memory requirements.
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<br><br>
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# Features
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### Search Modes
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- [Quick Search](docs/config_search.md#quick-search-mode) will **sparsely** search the [Max Batch Size](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#maximum-batch-size),
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[Dynamic Batching](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#dynamic-batcher), and
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[Instance Group](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#instance-groups) spaces by utilizing a heuristic hill-climbing algorithm to help you quickly find a more optimal configuration
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- [Automatic Brute Search](docs/config_search.md#automatic-brute-search) will **exhaustively** search the
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[Max Batch Size](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#maximum-batch-size),
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[Dynamic Batching](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#dynamic-batcher), and
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[Instance Group](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#instance-groups)
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parameters of your model configuration
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- [Manual Brute Search](docs/config_search.md#manual-brute-search) allows you to create manual sweeps for every parameter that can be specified in the model configuration
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### Model Types
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- [Ensemble Model Search](docs/config_search.md#ensemble-model-search): Model Analyzer can help you find the optimal
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settings when profiling an ensemble model, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm
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- [BLS Model Search](docs/config_search.md#bls-model-search): Model Analyzer can help you find the optimal
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settings when profiling a BLS model, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm
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- [Multi-Model Search](docs/config_search.md#multi-model-search-mode): **EARLY ACCESS** - Model Analyzer can help you
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find the optimal settings when profiling multiple concurrent models, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm
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### Other Features
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- [Detailed and summary reports](docs/report.md): Model Analyzer is able to generate
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summarized and detailed reports that can help you better understand the trade-offs
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between different model configurations that can be used for your model.
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- [QoS Constraints](docs/config.md#constraint): Constraints can help you
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filter out the Model Analyzer results based on your QoS requirements. For
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example, you can specify a latency budget to filter out model configurations
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that do not satisfy the specified latency threshold.
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<br><br>
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# Examples and Tutorials
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### **Single Model**
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See the [Single Model Quick Start](docs/quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on a simple PyTorch model.
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### **Multi Model**
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See the [Multi-model Quick Start](docs/mm_quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on two models running concurrently on the same GPU.
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<br><br>
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# Documentation
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- [Installation](docs/install.md)
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- [Model Analyzer CLI](docs/cli.md)
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- [Launch Modes](docs/launch_modes.md)
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- [Configuring Model Analyzer](docs/config.md)
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- [Model Analyzer Metrics](docs/metrics.md)
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- [Model Config Search](docs/config_search.md)
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- [Checkpointing](docs/checkpoints.md)
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- [Model Analyzer Reports](docs/report.md)
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- [Deployment with Kubernetes](docs/kubernetes_deploy.md)
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<br><br>
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# Reporting problems, asking questions
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We appreciate any feedback, questions or bug reporting regarding this
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project. When help with code is needed, follow the process outlined in
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the Stack Overflow (https://stackoverflow.com/help/mcve)
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document. Ensure posted examples are:
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- minimal – use as little code as possible that still produces the
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same problem
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- complete – provide all parts needed to reproduce the problem. Check
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if you can strip external dependency and still show the problem. The
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less time we spend on reproducing problems the more time we have to
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fix it
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- verifiable – test the code you're about to provide to make sure it
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reproduces the problem. Remove all other problems that are not
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related to your request/question.
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**Note** <br>
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You are currently on the r23.05 branch which tracks stabilization towards the next release.<br>
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This branch is not usable during stabilization.

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