This PR adds an autoload mechanism for out-of-tree backends, simplifies
TVM's Python library loading, and removes `TVMError` in favor of native
Python errors.
## Autoload out-of-tree backends
Out-of-tree packages can register an autoload callable under the
`tvm.backends` entry-point group (mirroring torch's device-backend
autoload). At `import tvm` startup each entry point is discovered and
its callable invoked once, after the core runtime and the `tvm`
namespace are fully initialized, so an extension can register
ops/targets/funcs or load extra libraries.
```toml
[project.entry-points."tvm.backends"]
tvm_foo = "tvm_foo:_autoload"
```
A failing extension is caught and surfaced via `warnings.warn` so it
cannot break `import tvm`. Autoload can be disabled with
`TVM_DEVICE_BACKEND_AUTOLOAD=0`.
## Simplify library loading
The library-loading path in `base.py` is consolidated around a single
`_LOADED_LIBS` dict (basename to ctypes handle) so downstream and
autoloaded extensions can skip already-loaded libraries; the per-backend
runtime DSO list is folded into `load_backend_libs`. Accumulated cruft
is removed: the Python-3.9 check, the readline shim, the `_FFI_MODE`
ctypes check, the `base.__version__` re-export, and `py_str` (call sites
inline `.decode("utf-8")`).
## Remove TVMError in favor of native Python errors
`TVMError` added a layer atop `RuntimeError` that downstream code had to
import and learn. It is removed; the registered FFI error kinds
(`InternalError`, `RPCError`, `OpError`, `DiagnosticError`,
`ScheduleError`) now subclass `RuntimeError` directly while staying
registered, so the FFI keeps throwing the right kinds. All `TVMError`
imports, `except`/`raise`/`isinstance` uses, and
`pytest.raises(tvm.TVMError)` sites move to the `RuntimeError` builtin.
## Summary
Lifts 10 host-toolchain / CLI / process / utility modules from
`python/tvm/contrib/` to a new `python/tvm/support/` package, and
deletes two dead contrib shims.
`tvm.support` is the home for Python helpers that integrate TVM with
external CLIs and host-side tools — compilers, archivers, subprocess
pools, and build-info queries. These are load-bearing internal pieces
that TVM's compile/link/run paths depend on. `tvm.contrib` is reserved
for optional vendor SDK integrations and experimental features. The
distinction is documented in the `tvm.support` package docstring.
Moved (one commit each):
- `tvm.contrib.cc` → `tvm.support.cc`
- `tvm.contrib.nvcc` → `tvm.support.nvcc`
- `tvm.contrib.rocm` → `tvm.support.rocm`
- `tvm.contrib.ndk` → `tvm.support.ndk`
- `tvm.contrib.xcode` → `tvm.support.xcode`
- `tvm.contrib.clang` → `tvm.support.clang`
- `tvm.contrib.emcc` → `tvm.support.emcc`
- `tvm.contrib.popen_pool` → `tvm.support.popen_pool`
- `tvm.contrib.utils` → `tvm.support.utils`
- `tvm.contrib.tar` → `tvm.support.tar`
Deleted:
- `tvm.contrib.spirv` — single `optimize()` wrapping `spirv-opt`; zero
importers.
- `tvm.contrib.rpc` — self-deprecation shim with "removed in 0.5"
banner; honoring it.
Package conversion:
- `python/tvm/support.py` → `python/tvm/support/__init__.py` with
inclusion-rule docstring.
- `libinfo()` extracted into `python/tvm/support/libinfo.py`.
- `FrontendTestModule` dropped (audit confirmed zero callers outside its
own definition).
## Compatibility
Hard break — no `tvm.contrib.<mod>` re-export shims. All callers updated
in this PR.
C++-side FFI registry keys (`tvm.contrib.nvcc.*`, etc.) are unchanged —
only the Python module path moves. Renaming the FFI keys is a separate
follow-up.
This PR phases out tvm._ffi redirections in favor of new FFI
new functions are now called via tvm.ffi.
We also enabled limited API support for python 3.12+
so the compiled binary can be forward compatible to future
python versions.
This PR modernizes the FFI foundation of the project and introduce
a new minimal and lightweight module [tvm ffi](https://github.com/apache/tvm/tree/refactor-s3/ffi)
based on our lessons in the past few years. It implements a modern
version of the [Unified Packed and Object RFC](https://github.com/apache/tvm-rfcs/blob/main/rfcs/0097-unify-packed-and-object.md)
that unifies the packed function call and object systems.
Summary of the change:
- A dedicated clean Any/AnyView that can store strong and weak
references of items
- Function(previously PackedFunc) system built on top of the Any/AnyView
- A minimal C API that backs the overall calls. We are stabilizing the
API with a goal to bring clean, stable FFI conventions for both compiled
and registered code
- A rewrite of core python binding and generated code based on the module
- Update existing code and test cases to the new module
- Latest dlpack support
The new module brings many benefits thanks to the cleaner design,
to name a few:
- Any can support both POD types(int) and object types.
- Containers (e.g. Array) can now also contain Any value, e.g. now
`Array<int>` is supported, no need for boxed types
- Error handling now upgrades to object-based, allowing cleaner
traceback across languages
- Map now preserves insertion orders
- Path toward isolated stabilize minimum core ABI/API foundation module
- Type traits based design that cleanly defines how values interact
with Any system
- Automatic conversion of different types based on traits if needed
Because FFI upgrade is at heart of the project, the change touches every
component of the system. Importantly, this is an upgrade of the ABI so the
change is not backward compatible. The code compiled under the old
FFI won't work under the new one. We did provide example ABI translation
(e.g. LegacyTVMArgValueToFFIAny) functions for compatibility.
The PR tries to leave files in their old places while creating redirections.
The goal is to have the first milestone landed and infrastructure in place,
so we can do further refactors to complete features and cleanup legacy code
as trackable PRs. As of now, python binding and compiled code are under the
new convention while RPC and some other bindings still relies on legacy ABI
translation. We will work on upgrades in the coming PRs, including areas such
as reflection, phasing out legacy redirections etc.
This PR adds fail-guard to reduce error messages thrown during
process termination time. Such error won't trigger test error
but will bring extra message during exit time.
* Rename references to 0.0.0.0 to localhost. Also change references to 127.0.0.1 to localhost so that all references are consistent. 0.0.0.0 is not the same as localhost.
Previously the rpc server relies multiprocessing to start a new process and does not work under jupyter.
It also have a popen mode that does ensure the socket start listening before returning the port number.
This PR switches the implementations use PopenWorker. The port number is returned after the socket
get binded, which resolves some of the RPC flaky issues(need sleep to wait the server to start).
It also makes the RPC server jupyter friendly.
This PR introduces WebGPU support to tvm.
The WebGPU runtime is directly built in javascript(as WebGPU uses JS as the first class citizen API)
and exposes back to the tvm's runtime via PackedFuncs.
One important note is that `ctx.sync` is not async.
This is due to the fact that WebGPU is a purely async API and we cannot block in the web environment.
So the current best way to use the js api is to wrap things in an async function.
When copy a GPU array to CPU, `await ctx.sync()` need to be called to wait for copy completion.
We use a AsyncIO rpc server to serve the async functions to the clients.
* Update dmlc-core which was mistakenly overriden
* [REFACTOR][RPC][PROCOTOL-CHANGE] Modularize the RPC infra.
This PR refactors the RPC protocol to make it more modularized.
- RPCSession: represent a set of features that need to be implemented
- RPCEndPont: End point that forwards the RPCSession requests over a communication channel.
- RPCModule: Exposes an RPCSession as an rpc device in the TVM Runtime API.
In the new design, the local machine is presented as a special case of RPCSession.
The remote is just another client session that calls into RPCEndPoint.
The RPC communication path is as follows.
```
client -> ClientSession -> EndPoint[client@n0]
-> networking[between n0 <=> n1]
-> EndPoint[server@n1] -> LocalSession[@n1]
```
Because of the new modular design, we can now chain more sessions together.
For example, we can now run the following proxy setup (testcase in test_runtime_rpc.test_session_constructor).
```
client -> ClientSession -> Endpoint[client@n0]
-> networking[between n0 <=> n1]
-> Endpoint[server@n1] -> ClientSession -> Endpoint[client@n1]
-> networking[between n1 <=> n2]
-> Endpoint[server@n2] -> LocalSession[@n2]
```
We can also implement other types of Sessions.
As an example, We introduced a PopenSession that communicates with
the another process via a pipe.
We also add more comments about the internal of the RPC.
The communication protocol is simplfied using a similar convention as PackedFunc.
This allows us to further reduce the amount of special remote syscalls.
Due to the major improvement and simplification, we are making a non-compatible update to the RPC protocol.
It means that the client and server needs to be upgraded to together in order for it to function correctly.
This PR also introduces a versioning mechanism to the current RPC procotol,
so that future upgrade will be produce more user friendly with error messages.
* Address review comments
* Remove ld library path
Tianqi Chen