* Implement the context manager as a context manager class, rather than using @contextlib.contextmanager. It turns out the contextlib contextmanagers are rather slow.
* Fuse the four child context managers into a single context manager. This saves us a bunch of allocations.
* While we are here, also simplify the xla_metadata context manager to avoid its dual representation of the current metadata.
PiperOrigin-RevId: 719918121
* We don't need to keep a separate thread-local stack of objects: the config state already has a thread local.
* We don't need to keep an explicit stack of contexts at all: we can maintain it in the context manager frames.
* When checking for incompatible nested compute_ons, we can just check the current state: no need to look higher in the stack!
PiperOrigin-RevId: 719892989
We use dead code elimination (DCE) throughout JAX core to remove unused computations from Jaxprs. This typically works transparently when we're just using `lax` primitives, but opaque calls to `pallas_call` or `ffi_call` can't be cleaned up this way. For many kernels however, the author will know how to generate a more efficient call for specific patterns of used outputs, so it is useful to provide a mechanism for customizing this behavior.
In https://github.com/jax-ml/jax/pull/22735, I attempted to automatically tackle one specific example of this that comes up frequently, but there have been feature requests for a more general API. This version is bare bones and probably rough around the edges, but it could be a useful starting point for iteration.
PiperOrigin-RevId: 718950828
This will basically drop the gather operation into full auto mode and add a sharding constraint on the output given by the user via `out_spec`.
Co-authored-by: Matthew Johnson <mattjj@google.com>
PiperOrigin-RevId: 716295953
The Python warnings.catch_warnings() functionality is not thread-safe (https://py-free-threading.github.io/porting/#the-warnings-module-is-not-thread-safe), so we cannot use it during tests that use free-threading. This change introduces a private warnings test helper (test_warning_util.py), which hooks the CPython warning infrastructure and uses it to implement thread-safe warnings infrastructure.
This requires a handful of small modifications to tests to remove direct uses of the warnings module. We also sadly have to delete one TPU test that checks for a warning raised on another thread; there's no easy way for us to catch that in a thread-safe way, but that test seems like overkill anyway.
If PartitionSpec is passed, the mesh is read from the context. The primitives though take `NamedSharding` only. The conversion from `PartitionSpec` to `NamedSharding` happens above `.bind`.
We also raise an error if `PartitionSpec` contain mesh axis names that are of type Auto or Collective for the above functions.
PiperOrigin-RevId: 713352542
Also support `Auto` mode fully or mixed in with `User` mode. This works by overriding the sharding of `Auto` axes in the PartitionSpec with `Unconstrained` in `ShapedArray` constructor. The `ShapedArray` constructor is the central place where we can make such substitutions.
During lowering of shardings with auto axes, we mark the auto dims are `unspecifed_dims`. We don't mark all dims as unspecified because that would enable XLA to shard them even further which is not what we want if some of the dims are user sharded.
PiperOrigin-RevId: 704911253
Shardy custom_partitioning.
The parsing of the sharding rule string very closely follows how einops parses
their rules in einops/parsing.py.
When a SdyShardingRule object is constructed, we check the syntax of the Einsum
like notation string and its consistency with the user provided factor_sizes,
and report errors accordingly. This is done during f.def_partition.
When SdyShardingRule.build is called, during JAX to MLIR lowering, we check
the consistency between the Einsum like notation string, the factor_sizes
and the MLIR operation, and report errors accordingly.
PiperOrigin-RevId: 703187962
This change adds a Python binding that makes `ifrt::CustomCallProgram` for a
colocated Python program. This Python binding will be used internally in the
colocated Python API implementation. The API does not yet compile the program
into an executable, which will be added separately.
PiperOrigin-RevId: 700443656
Set the abstract mesh context manager at the jit tracing boundary by looking at the mesh on the avals. In the future, this context manager will be user settable too.
Abstract mesh context manager is a new context manager with a new context variable and new trace_context entry which governs the cache behavior. If the abstract mesh context manager is not set, the default is `None`.
PiperOrigin-RevId: 698493184
This change adds an experimental API `jax.experimental.colocated_python`. The
ultimate goal of this API is to provide a runtime-agnostic way to wrap a Python
code that runs close to (or on) accelerator hosts. Multi-controller JAX can
trivially achieve this colocated Python code execution today, while
single-controller JAX needed its own solution for distributed Python code
execution, which creates fragmentation of the user code for these two runtime
architectures. `colocated_python` is an attempt to define a single device model
and portable API to allow the user to write a single code once that can run on
both runtime architectures.
This change includes an implementation of the function API portion of
`jax.experimental.colocated_python`. A (stateful) object API will be added
separately. Also there will be a separate change that expresses serialized
functions as an IFRT `CustomCallProgram`.
It is currently in an early development stage. Please proceed with a caution
when using the API.
PiperOrigin-RevId: 690705899
I also deprecated `jax.experimental.pallas.gpu` in favor of
`jax.experimental.pallas.triton` to avoid confusion with the Mosaic GPU
backend.
PiperOrigin-RevId: 683119193
This change also uses the new batching dims for gather/scatter batching rules, to avoid concatenating the indices with iota.
See https://github.com/openxla/stablehlo/pull/2259
PiperOrigin-RevId: 678649138
This cl refactors Pallas memref indexers to transforms which can support different ref transforms: indexing, bitcast (added in this cl), reshape (to be added) and others. Like indexer, user can apply multiple transforms to same memref, eg:
```
ref.bitcast(type1).at[slice1].bitcast(type2).bitcast(type3).at[slice2]...
```
Jaxpr Preview (apply multiple transforms to same ref):
```
{ lambda ; a:MemRef<None>{int32[16,256]} b:MemRef<None>{int32[8,128]}. let
c:i32[8,128] <- a[:8,:][bitcast(int16[16,256])][bitcast(float16[16,256])][:,:128][bitcast(int32[8,128])][:,:]
b[:,:] <- c
in () }
```
Tested:
* DMA with bitcasted ref
* Load from bitcasted ref
* Store to bitcasted ref
* Multiple transforms
* Interpret Mode for ref transforms (updated discharge rules)
PiperOrigin-RevId: 674961388
`jax.make_mesh` is the stable API endpoint of `mesh_utils` but without all the extra options. If you want those, you can still use the experimental endpoint in `mesh_utils`.
PiperOrigin-RevId: 670707995
