Files
tilelang/testing/python/transform/test_nullable_buffer_params.py
T
Lei Wang 7ab2b2be92 [BugFix] ArgBinder: relax shared-shape binding for unused nullable buffers (#1870)
* [BugFix] tvm_ffi: handle unused nullable buffers with shared symbolic shapes

* [BugFix] ArgBinder: relax shared-shape binding for unused nullable buffers
2026-02-24 11:43:55 +08:00

145 lines
4.3 KiB
Python

import torch
import tilelang
import tilelang.testing
from tilelang import language as T
def test_nullable_shared_shape():
"""Test that buffers sharing a shape variable can be nullable."""
@tilelang.jit
def get_kernel():
m = T.dynamic("m")
@T.prim_func
def test_kernel(
a: T.Tensor[(m,), T.int32],
b: T.Tensor[(m,), T.int32],
c: T.Tensor[(m,), T.int32],
):
with T.Kernel(1, threads=64):
tx = T.get_thread_binding()
if tx == 0:
T.print(m)
return test_kernel
m = 200
kernel = get_kernel()
# Create test tensors
tensor_a = torch.randn((m,), device="cuda", dtype=torch.float32).to(torch.int32)
tensor_b = torch.randn((m,), device="cuda", dtype=torch.float32).to(torch.int32)
tensor_c = torch.randn((m,), device="cuda", dtype=torch.float32).to(torch.int32)
print("Test 1: All tensors provided")
kernel(tensor_a, tensor_b, tensor_c)
print("✓ PASS: All tensors provided")
print("\nTest 2: Only first tensor provided")
kernel(tensor_a, None, None)
print("✓ PASS: Only first tensor provided")
print("\nTest 3: Only middle tensor provided")
kernel(None, tensor_b, None)
print("✓ PASS: Only middle tensor provided")
print("\nTest 4: Only last tensor provided")
kernel(None, None, tensor_c)
print("✓ PASS: Only last tensor provided")
print("\nTest 5: First and last tensors provided")
kernel(tensor_a, None, tensor_c)
print("✓ PASS: First and last tensors provided")
print("\nTest 6: All tensors are None (should fail)")
try:
kernel(None, None, None)
print("✗ FAIL: Should have raised an error")
return False
except RuntimeError as e:
if "at least one non-null buffer" in str(e):
print(f"✓ PASS: Correctly rejected with error: {e}")
else:
print(f"✗ FAIL: Wrong error message: {e}")
return False
print("\n" + "=" * 60)
print("All tests passed!")
return True
def test_nullable_single_source_shape():
"""Test that a single buffer with a symbolic shape var must be non-null.
This guards against the previous segfault when binding m from x.shape[0]
with x == None.
"""
@tilelang.jit
def get_kernel():
m = T.dynamic("m")
@T.prim_func
def sample_kernel(x: T.Tensor[(m,), T.int32]):
with T.Kernel(1, threads=1):
tx = T.get_thread_binding()
if tx == 0:
T.print(m)
return sample_kernel
m = 16
kernel = get_kernel()
# Provide a valid tensor: should run
x = torch.randn((m,), device="cuda", dtype=torch.float32).to(torch.int32)
kernel(x)
# Passing None should not segfault; m binds to 0 and kernel is a no-op
kernel(None)
def test_nullable_shared_shape_with_no_source_buffers_but_other_tensor_present():
"""Test that unused buffers sharing a symbolic shape var can both be None.
Repro for:
- Two (or more) unused buffers have shape (m,)
- All buffers that mention `m` are passed as None
- Another (non-null) tensor argument exists, but does not mention `m`
TVM requires at least one non-null buffer to bind `m` when it appears in multiple
buffers. TileLang should handle this gracefully for truly-unused nullable buffers.
"""
@tilelang.jit(execution_backend="tvm_ffi")
def get_kernel():
m = T.dynamic("m")
@T.prim_func
def test_kernel(
a: T.Tensor[(m,), T.float16],
b: T.Tensor[(m,), T.float16],
out: T.Tensor[(1,), T.float16],
):
with T.Kernel(1, threads=32):
fragment = T.alloc_fragment((1,), T.float32)
T.copy(out[0], fragment)
T.copy(fragment, out[0])
return test_kernel
kernel = get_kernel()
out = torch.randn((1,), device="cuda", dtype=torch.float16)
out_ref = out.clone()
# Both `a` and `b` are None; they also share the symbolic shape var `m`.
# This should run because `a`/`b` are unused by the kernel body.
kernel(None, None, out)
torch.testing.assert_close(out, out_ref)
if __name__ == "__main__":
tilelang.testing.main()