Python API#
Tensor-level intermediate representations, compilation, and runtime execution.
Namespaces#
Namespace |
Purpose |
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Tensors, devices, data types, and runtime modules. |
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Shared expressions, types, statements, and IR modules. |
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Primitive expressions and scalar operators. |
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Pass infrastructure and instrumentation. |
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Symbolic arithmetic, analysis, and simplification. |
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Python syntax registration for IR dialects. |
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Translate Python scripts into IR builder operations. |
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Shared IR builder contexts and statements. |
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Compilation targets and device selection. |
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Tensor IR construction and compilation. |
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Tensor IR operators and intrinsic calls. |
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Tensor IR analysis and verification. |
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Tensor IR transformation passes. |
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Tensor layouts and logical-to-physical index mappings. |
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Tile operations, views, and dispatch. |
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Tensor IR syntax and JIT compilation. |
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Shared code generation and LLVM helpers. |
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Load and register device backends. |
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CUDA backend configuration and registration. |
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CUDA intrinsic builders. |
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CUDA kernel authoring namespace. |
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CUDA shared-memory and tensor-memory layouts. |
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CUDA pipelines, barriers, storage pools, and scheduling. |
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CUDA-specific transformation passes. |
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ROCm backend registration. |
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Metal backend and script namespaces. |
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Metal intrinsic builders. |
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OpenCL backend and script namespaces. |
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Adreno backend registration. |
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Hexagon backend and linker integration. |
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Vulkan backend registration. |
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WebGPU backend registration. |
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Trainium backend and script namespaces. |
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Trainium NKI intrinsic wrappers. |
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Trainium-specific lowering passes. |
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Operators written in Rust. |
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Build tools and system utilities. |
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Test fixtures and numerical checks. |
TVM-FFI APIs#
Page |
Purpose |
|---|---|
Walk, map, visit, and mutate IR. |
Classes#
Alias |
Canonical API |
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Functions#
Use compile() to build a TIRx function or module into an executable.
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Compile a function or module to an executable for the target. |
Alias |
Canonical API |
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