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Move jax/_src/interpreters/batching.py into its own BUILD rule #28957

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Merged
merged 1 commit into from
May 23, 2025
Merged

Move jax/_src/interpreters/batching.py into its own BUILD rule #28957

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20 changes: 19 additions & 1 deletion jax/BUILD
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Original file line number Diff line number Diff line change
Expand Up @@ -315,7 +315,6 @@ py_library_providing_imports_info(
"_src/ffi.py",
"_src/flatten_util.py",
"_src/interpreters/__init__.py",
"_src/interpreters/batching.py",
"_src/interpreters/pxla.py",
"_src/pjit.py",
"_src/prng.py",
Expand Down Expand Up @@ -383,6 +382,7 @@ py_library_providing_imports_info(
":ad_util",
":api_util",
":basearray",
":batching",
":cloud_tpu_init",
":compilation_cache_internal",
":compiler",
Expand Down Expand Up @@ -707,6 +707,24 @@ pytype_strict_library(
],
)

pytype_strict_library(
name = "batching",
srcs = ["_src/interpreters/batching.py"],
deps = [
":ad_util",
":config",
":core",
":mesh",
":partial_eval",
":partition_spec",
":sharding_impls",
":source_info_util",
":tree_util",
":typing",
":util",
] + py_deps("numpy"),
)

pytype_strict_library(
name = "mlir",
srcs = ["_src/interpreters/mlir.py"],
Expand Down
28 changes: 19 additions & 9 deletions jax/_src/interpreters/batching.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,6 @@

import numpy as np

import jax
from jax._src import config
from jax._src import core
from jax._src import source_info_util
Expand Down Expand Up @@ -301,11 +300,14 @@ def _cont(axis_size, elt, axis):
from_elt_handlers: dict[type, FromEltHandler] = {}

def make_iota(axis_size: AxisSize) -> Array:
# Callers of this utility, via batch() or vtile(), must be in a context
# where lax is importable.
from jax import lax # pytype: disable=import-error
handler = make_iota_handlers.get(type(axis_size))
if handler:
return handler(axis_size)
else:
return jax.lax.iota('int32', int(axis_size))
return lax.iota('int32', int(axis_size))
make_iota_handlers: dict[type, MakeIotaHandler] = {}

def register_vmappable(data_type: type, spec_type: type, axis_size_type: type,
Expand Down Expand Up @@ -1019,10 +1021,13 @@ def broadcast_batcher(prim, args, dims, **params):
return (out, (0,) * len(out)) if prim.multiple_results else (out, 0)

def _handle_scalar_broadcasting(nd, x, d):
# Callers of this utility, via broadcast_batcher() or defbroadcasting(),
# must be in a context where lax is importable.
from jax import lax # pytype: disable=import-error
if d is not_mapped or nd == np.ndim(x):
return x
else:
return jax.lax.expand_dims(x, tuple(range(np.ndim(x), nd)))
return lax.expand_dims(x, tuple(range(np.ndim(x), nd)))

def defreducer(prim, ident):
primitive_batchers[prim] = partial(reducer_batcher, prim, ident)
Expand Down Expand Up @@ -1078,17 +1083,20 @@ def mask_ragged_axes(operand: Array, ident, axis_spec: RaggedAxis) -> Array:

def _mask_one_ragged_axis(
operand: Array, ident, axis_spec: RaggedAxis) -> Array:
# Callers of this utility, via reducer_batcher() or defreducer(),
# must be in a context where lax is importable.
from jax import lax # pytype: disable=import-error
assert len(axis_spec.ragged_axes) == 1, "Mask just one ragged axis at a time"
ragged_axis, segment_lengths = axis_spec.ragged_axes[0]
value = ident(operand.dtype)
positions = jax.lax.broadcasted_iota('int32', operand.shape, ragged_axis)
positions = lax.broadcasted_iota('int32', operand.shape, ragged_axis)
# TODO(mattjj, axch) can't get ._data, need to convert it
# lengths = jax.lax.convert_element_type(segment_lengths._data, 'int32')
lengths = jax.lax.convert_element_type(segment_lengths, 'int32')
limits = jax.lax.broadcast_in_dim(
# lengths = lax.convert_element_type(segment_lengths._data, 'int32')
lengths = lax.convert_element_type(segment_lengths, 'int32')
limits = lax.broadcast_in_dim(
lengths, operand.shape, [axis_spec.stacked_axis])
mask = positions < limits
return jax.lax.select(mask, operand, jax.lax.broadcast(value, operand.shape))
return lax.select(mask, operand, lax.broadcast(value, operand.shape))

def move_stacked_axis(operand, bdim, dst):
dst = canonicalize_axis(dst, operand.ndim)
Expand All @@ -1103,6 +1111,8 @@ def move_stacked_axis(operand, bdim, dst):
### general utilities for manipulating axes on jaxpr types (not vmappables)

def broadcast(x, sz, axis, mesh_axis=None):
# Callers of this utility must be in a context where lax is importable.
from jax import lax # pytype: disable=import-error
shape = list(np.shape(x))
shape.insert(axis, sz)
broadcast_dims = tuple(np.delete(np.arange(len(shape)), axis))
Expand All @@ -1114,7 +1124,7 @@ def broadcast(x, sz, axis, mesh_axis=None):
# TODO(dougalm, yashkatariya): Delete this context manager once we figure
# out how to ensure jaxpr arguments always have the context mesh.
with mesh_lib.use_abstract_mesh(sharding.mesh):
x = jax.lax.broadcast_in_dim(x, shape, broadcast_dims, out_sharding=sharding)
x = lax.broadcast_in_dim(x, shape, broadcast_dims, out_sharding=sharding)
if config._check_vma.value:
# TODO(yashkatariya,parkers): don't do this, fix during fixit week 2026
spmd_names = core.get_axis_env().spmd_axis_names
Expand Down
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