## Summary
- bump tvm-ffi and include the device definition where its `DLDevice`
traits are instantiated
- keep only the required Tensor wrapper layout fix and register
`ir.Type` before reflected `Expr` fields can materialize a fallback
wrapper
- preserve `BaseFunc.with_attr` callers by moving only method-private
results, never the canonical `self` wrapper
## Rationale
The tvm-ffi lifetime update requires a replacement wrapper to fit the
layout already registered for the same type index. `runtime.Tensor`
replaces the core `ffi.Tensor` wrapper, so it must use empty slots. The
ordinary TVM mixins are first-registered with their concrete descendants
and may safely retain normal Python dictionaries; the additional mixin
and explicit-dictionary slot changes are not required.
Object tying also means `BaseFuncCopy(self)` may return `self`. Passing
that wrapper through `_move()` invalidates the caller. The first update
now passes the alias as an lvalue, forcing native copy-on-write to
create a private result. Only later dictionary updates move a result
that is not `self` and has not escaped the method.
## Validation
- built an exact CPython 3.12 wheel from tvm-ffi `21e30c3b1d` and
rebuilt TVM against it
- direct Type/function/detach regressions: 3 passed
- complete IR plus focused Relax coverage: 111 passed
- prior Relax failure set: 157 passed, 9 skipped
- runtime probe for `relax.Function`, `relax.ExternFunc`, and
`tirx.PrimFunc`: original wrappers preserved; single- and
multi-attribute results distinct and valid
- all touched-file pre-commit hooks passed
---------
Co-authored-by: Yaxing Cai <caiyaxing666@gmail.com>
## Summary
Compiler Targets can carry device-type semantics that runtime
device-name parsing does not preserve.
- add `tvm.device_from_target` for canonical Target-to-Device
translation
- use explicit runtime constructors where the device kind is fixed
- update target-derived utilities, tests, and documentation to use the
explicit boundary
## Summary
This PR adds the initial TIRx support needed for low-level programming
of Blackwell-class GPU architectures. As part of the ongoing TIRx
refactor, it introduces TVMScript support for directly scripting
advanced hardware features without relying on scheduling as the primary
programming interface.
The change keeps existing `s_tir` script support intact while making
direct scripting a first-class path for TIRx programs.
## Main Changes
- Add TIRx operator dispatch and layout infrastructure.
- Add TVMScript support for new low-level TIRx operations.
- Add analysis, transform, and lowering support for TIRx IR nodes.
- Add CUDA/Blackwell-oriented codegen and intrinsic coverage.
- Add Python and C++ integration points for TIRx scripting and runtime
support.
## Validation
- `pre-commit run --all-files`
- `ninja -C build -j32`
- `CUDA_VISIBLE_DEVICES=2 pytest tests/python/tirx/ -n 16`
- `1723 passed, 47 skipped, 32 warnings`
- `CUDA_VISIBLE_DEVICES=2 python -m pytest -v
tests/python/all-platform-minimal-test`
- `37 passed, 105 skipped`
- `TVM_TEST_TARGETS=llvm python -m pytest -v tests/python/tirx-analysis
tests/python/tirx-base tests/python/tirx-transform -n 16`
- `664 passed, 25 skipped, 9 xfailed, 1 xpassed`
## Local CI Notes
Some full CI-equivalent jobs were not locally reproducible because this
machine is missing parts of the Apache TVM CI environment, including
`llvm-config-15/17`, Vulkan, ROCm, Maven, Sphinx, Doxygen, Emscripten,
and ARM/QEMU cross-toolchain components. Metal-specific tests were
skipped locally because no Metal runtime is available.
This PR enables ruff pyupgrade (UP) rules with py310 target, auto-fixing
~5600 annotation modernizations (PEP 585 generics, PEP 604 unions,
deprecated typing imports).
Also removes from __future__ import annotations from ir/module.py and
rmsnorm.py, bumps requires-python to >=3.10, and removes absolute_import
aliases from topi/contrib files.
## What
Replace 6 bare `except:` clauses with `except Exception:`.
## Why
Bare `except:` catches `BaseException`, including `KeyboardInterrupt`
and `SystemExit`, which can prevent clean process shutdown and mask
critical errors. Using `except Exception:` catches all application-level
errors while allowing system-level exceptions to propagate correctly.
This PR relax default alignment and continguous requirement in dlpack import.
This allows the ffi to be useful in most settings.
We also provide utility for users to check these requirements themselves.
This PR cleans up the python API to make things more consistent
with existing python array api and torch.
Device update
- device_id => index, to be consistent with torch
- device_type => dlpack_device_type() returns int
- added type property same as torch.device
API updates:
- Move the convenient method like cpu() out into tvm runtime to keep device minimal
- tvm_ffi._init_api => tvm_ffi.init_ffi_api
- tvm_ffi.register_func => tvm_ffi.register_global_func
This PR Updates the NDArray => Tensor.
Both tensor and ndarray are commonly used terms.
Because the term Tensor is getting more common in the context of ML,
we do the rename to stay more aligned with torch.Tensor and DLTensor.
Tianqi Chen