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PyPTO-Lib

PyPTO-Lib is a collection of tensor-level kernels, model implementations, and validation workflows built with PyPTO for Ascend NPUs.

Use this documentation to move from a first simulator run to validated model kernels and systematic precision or performance tuning.

Choose a path

Run a kernel

Start with installation and environment setup, then run your first kernel.

Write a kernel

Use the PyPTO Coding chapter for the canonical kernel style and hand-written CCE extern-kernel conventions.

Examples

Use the example catalog for focused, self-contained kernels organized by learning level.

Models

Use the model pages for end-to-end and component-level model implementations.

Run and Validate

Read the compile and runtime workflow and the Golden Harness overview to understand how a script compiles, executes, and checks its result.

Diagnose and optimize

Begin with the debugging playbook, then choose the precision or performance workflow for the problem at hand.

Ecosystem