python_backend | Triton backend that enables pre

by triton-inference-server C++ Version: Current License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | python_backend Summary

python_backend is a C++ library. python_backend has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Triton backend that enables pre-process, post-processing and other logic to be implemented in Python.

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Quality

Security

License

Reuse

Support

python_backend has a low active ecosystem.

It has 320 star(s) with 108 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

python_backend has no issues reported. There are 6 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of python_backend is current.

Quality

python_backend has 0 bugs and 6 code smells.

Security

python_backend has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

python_backend code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

python_backend is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

python_backend releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

It has 1326 lines of code, 42 functions and 13 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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python_backend Key Features

No Key Features are available at this moment for python_backend.

python_backend Examples and Code Snippets

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Community Discussions

No Community Discussions are available at this moment for python_backend.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install python_backend

Replace <xx.yy> with the Triton version (e.g. 21.05).
Run the Triton Inference Server container.
Inside the container, clone the Python backend repository.
Install example model.
Start the Triton server.
In the host machine, start the client container.
In the client container, clone the Python backend repository.
Run the example client.

Support

Python Backend User Documentation Quick Start Building from Source Usage initialize execute finalize Model Config File Using Custom Python Execution Environments 1. Building Custom Python Backend Stub 2. Packaging the Conda Environment Important Notes Error Handling Managing Shared MemoryBusiness Logic Scripting Using BLS with Stateful Models LimitationsInteroperability and GPU Support pb_utils.Tensor.to_dlpack() -> PyCapsule pb_utils.Tensor.from_dlpack() -> Tensor pb_utils.Tensor.is_cpu() -> bool Input Tensor Device PlacementExamples AddSub in NumPy AddSubNet in PyTorch Business Logic Scripting PreprocessingRunning with InferentiaReporting problems, asking questions

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