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
* [FFI][REFACTOR] Establish tvm_ffi as a standalone python module
This PR establishes tvm_ffi as a standalone python module.
The ffi is structured as a minimal pip module that can be
directly install by path or url.
examples/get_started provided a minimal example.
This is a major change as we are decoupling tvm_ffi as a
separate package, users need to install tvm_ffi separately.
Thanks to its minimal dependency, tvm_ffi can be easily installed
even just from the source by pip install ./ffi
This change would enable future improvement for library plugins
to have lightweight dependencies by just working on top of
the tvm_ffi, while the main compiler toolchain and runtime
can be layered on top.
* [FFI] Improve traceback setups
This PR improves traceback related setups
This PR formalizes the namespace for all object registered so
we do not have object that sits on root namespace
Also fixes the Visitor style in TensorMapNode
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.
* [Relay] Allow partial virtual device annotations.
Previously CompilationConfig::CanonicalVirtualDevice required
the argument virtual device to contain a device type. However
now that virtual devices may contain memory scopes that's
unnecessarily strict.
With this change it is possible to write virtual device
annotations with just memory scopes, and let PlanDevices
flow those constraints along with the usual device constraints.
* - Make sure CanonicalVirtualDevice reuses FullyUnconstrained
* Add Python representation for VirtualDevice
This adds a Python class to represent the VirtualDevice so that the
behaviour for `device_type()` can be semi-replicated.
These tests were actually not being ran and were broken so I've added
them to the integration script.
* Update other references to make_virtual_device
Tianqi Chen