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31 changes: 28 additions & 3 deletions python/tvm/relax/backend/dispatch_sort_scan.py
Original file line number Diff line number Diff line change
Expand Up @@ -37,9 +37,10 @@ class SortScanDispatcher(BackendDispatcher):

calls_to_update: dict[GlobalVar, Target]

def __init__(self, mod):
def __init__(self, mod, index_bits: int | None = None):
super().__init__(mod)
self.calls_to_update = {}
self.index_bits = index_bits

def apply_dlight_gpu_fallback(
self,
Expand Down Expand Up @@ -172,10 +173,15 @@ def visit_call_(self, call: relax.Call) -> relax.Expr:
if normalized_axis == len(shape) - 1:
outer = reduce(mul, shape_values[:-1], 1)
kernel_shape = relax.ShapeExpr([outer, shape[-1]])
index_bits = self.index_bits
if index_bits is None:
index_bits = 32 if tgt.kind.name == "webgpu" else 64
if tgt.kind.name == "webgpu" and index_bits != 32:
raise ValueError("WebGPU scan kernels require index_bits=32")
kernel = gpu_2d_continuous_cumsum(
in_dtype=in_dtype,
out_dtype=out_dtype,
index_bits=32 if tgt.kind.name == "webgpu" else 64,
index_bits=index_bits,
)
kernel_name = "gpu_2d_continuous_cumsum"
else:
Expand Down Expand Up @@ -263,10 +269,29 @@ def allocate_workspace(self, call: relax.Call) -> relax.Var:
class DispatchSortScan:
"""
Pass to dispatch scan and sort operators to platform dependent implementation.

Parameters
----------
index_bits : Optional[int]
Signed index-width budget for the generated continuous GPU cumsum hierarchy.
Must be 32 or 64. By default, use 32 for WebGPU and 64 for other targets.
WebGPU does not support an explicit 64-bit budget.

Pipelines that subsequently force indices to int32 should request 32 to
avoid generating hierarchy thresholds outside the signed int32 range.
The caller must ensure runtime indices fit the requested width; this
option does not insert runtime bounds checks.
This option does not narrow the generated TIR, change tensor dtypes, or
affect other sort/scan implementations.
"""

def __init__(self, index_bits: int | None = None):
if index_bits not in (None, 32, 64):
raise ValueError("index_bits must be either 32 or 64")
self.index_bits = index_bits

def transform_module(self, mod: IRModule, ctx: PassContext) -> IRModule:
sort_scan_dispater = SortScanDispatcher(mod)
sort_scan_dispater = SortScanDispatcher(mod, self.index_bits)
for gv, func in mod.functions_items():
if isinstance(func, relax.Function):
func = sort_scan_dispater.visit_expr(func)
Expand Down
46 changes: 44 additions & 2 deletions tests/python/relax/test_backend_dispatch_sort_scan.py
Original file line number Diff line number Diff line change
Expand Up @@ -415,10 +415,12 @@ def foo(x: R.Tensor((2, 3), "float32", "vulkan")):
"target",
[
pytest.param("cuda", marks=pytest.mark.gpu),
pytest.param("metal", marks=pytest.mark.gpu),
pytest.param({"kind": "vulkan", "supports_int64": True}, marks=pytest.mark.gpu),
],
)
def test_dispatch_cumsum_gpu(target):
@pytest.mark.parametrize("index_bits", [None, 32, 64])
def test_dispatch_cumsum_gpu(target, index_bits):
"""Test cumsum kernel dispatch and numerical correctness"""
if not tvm.testing.device_enabled(target):
pytest.skip(f"{target} not enabled")
Expand All @@ -436,7 +438,9 @@ def main(x: R.Tensor(("m", "n"), "int32")):
np_data = np.random.randint(0, 10, size).astype("int32")
np_cumsum = np.cumsum(np_data, axis=-1)
with tvm.target.Target(target):
mod = DispatchSortScan()(Module)
mod = DispatchSortScan(index_bits=index_bits)(Module)
if index_bits == 32:
mod = tirx.transform.ForceNarrowIndexToInt32()(mod)
ex = tvm.compile(mod, target)

def run_and_check():
Expand All @@ -449,6 +453,44 @@ def run_and_check():
tvm.testing.run_with_gpu_lock(run_and_check)


@pytest.mark.parametrize("target_kind", ["metal", "webgpu", "cuda"])
@pytest.mark.parametrize("index_bits", [None, 32, 64])
def test_dispatch_cumsum_index_width(target_kind, index_bits):
"""Respect the caller's index budget without restricting Metal's default."""
from tvm.relax.backend.gpu_generic import gpu_2d_continuous_cumsum

@I.ir_module
class Module:
@R.function
def main(x: R.Tensor(("m", "n"), "float32")):
gv = R.cumsum(x, axis=-1)
return gv

with tvm.target.Target(target_kind, host="llvm"):
if target_kind == "webgpu" and index_bits == 64:
with pytest.raises(ValueError, match="WebGPU scan kernels require index_bits=32"):
DispatchSortScan(index_bits=index_bits)(Module)
return
mod = DispatchSortScan(index_bits=index_bits)(Module)

expected_bits = (
index_bits if index_bits is not None else (32 if target_kind == "webgpu" else 64)
)
expected = gpu_2d_continuous_cumsum(
in_dtype="float32", out_dtype="float32", index_bits=expected_bits
)
assert_structural_equal(mod["gpu_2d_continuous_cumsum"], expected)
if expected_bits == 32:
# This previously failed on Metal with a 2**35 IntImm.
tirx.transform.ForceNarrowIndexToInt32()(mod)


@pytest.mark.parametrize("index_bits", [0, 16, 128])
def test_dispatch_cumsum_invalid_index_width(index_bits):
with pytest.raises(ValueError, match="index_bits must be either 32 or 64"):
DispatchSortScan(index_bits=index_bits)


@pytest.mark.gpu
def test_dispatch_cumprod_cuda_large_batch():
"""Test that GPU scan supports more batches than CUDA's grid-y limit."""
Expand Down
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