[Feat] Add support for T.serial with step and negative step

testing/python/language/test_tilelang_language_frontend_v2.py

@@ -273,5 +273,37 @@ def foo() -> T.Tensor((128,), T.float32):
     assert isinstance(foo, T.PrimFunc)
 
 
+def test_serial_for_with_step():
+
+    @tilelang.jit(out_idx=-1)
+    @T.prim_func
+    def test_stepped_serial(A: T.Tensor((10,), T.int32)):
+        with T.Kernel(1) as _:
+            for i in range(0, 10, 2):
+                T.device_assert(0 <= i < 10 and i % 2 == 0, "i out of range")
+                A[i] = 1.0
+            for i in range(1, 10, 2):
+                T.device_assert(1 <= i < 10 and i % 2 == 1, "i out of range")
+                A[i] = 2.0
+
+    ker = test_stepped_serial()
+    res = ker()
+    ref = torch.tensor([1, 2, 1, 2, 1, 2, 1, 2, 1, 2], dtype=torch.int32, device='cuda')
+    assert torch.all(res == ref), f"Expected {ref}, but got {res}"
+
+    @tilelang.jit(out_idx=-1)
+    @T.prim_func
+    def test_serial_step_neg(A: T.Tensor((10,), T.int32)):
+        with T.Kernel(1) as _:
+            for i in range(10, 0, -1):
+                T.device_assert(0 < i <= 10, "i out of range")
+                A[10 - i] = i
+
+    ker = test_serial_step_neg()
+    res = ker()
+    ref = torch.tensor([10, 9, 8, 7, 6, 5, 4, 3, 2, 1], dtype=torch.int32, device='cuda')
+    assert torch.all(res == ref), f"Expected {ref}, but got {res}"
+
+
 if __name__ == '__main__':
     tilelang.testing.main()

tilelang/language/__init__.py

@@ -23,9 +23,7 @@
     SharedBuffer,  # noqa: F401
     LocalBuffer,  # noqa: F401
 )
-from .parallel import Parallel  # noqa: F401
-from .pipeline import Pipelined  # noqa: F401
-from .persistent import Persistent  # noqa: F401
+from .loop import serial, Parallel, Persistent, Pipelined  # noqa: F401
 from .frame import has_let_value, get_let_value  # noqa: F401
 from .math_intrinsics import *  # noqa: F401
 from .kernel import (

tilelang/language/loop.py

@@ -0,0 +1,108 @@
+"""The language interface for tl programs."""
+from __future__ import annotations
+
+from typing import Any
+from tvm import tir
+from tvm.tir import IntImm
+import tvm.script.ir_builder.tir as tb_tir
+from .v2.builder import SerialForWithStep
+from tilelang import _ffi_api
+
+
+def Parallel(*extents: tir.PrimExpr, coalesced_width: int | None = None):
+    """Tools to construct nested parallel for loop.
+       This can be used to create element-wise tensor expression.
+
+    Parameters
+    ----------
+    extents : PrimExpr
+        The extents of the iteration.
+
+    coalesced_width : Optional[int]
+        The coalesced width of the parallel loop.
+
+    Returns
+    -------
+    res : frame.ForFrame
+        The ForFrame.
+    """
+    annotations: dict[str, Any] = {}
+    if coalesced_width is not None:
+        annotations.update({"coalesced_width": coalesced_width})
+    return _ffi_api.Parallel(extents, annotations)  # type: ignore[attr-defined] # pylint: disable=no-member
+
+
+def Persistent(
+    domain: list[tir.PrimExpr],
+    wave_size: tir.PrimExpr,
+    index: tir.PrimExpr,
+    group_size: tir.PrimExpr | None = 8,
+):
+    """Tools to construct persistent for loop.
+
+    Parameters
+    ----------
+    domain : List[tir.PrimExpr]
+        The list of dominators.
+    wave_size : int
+        The wave size.
+    index : int
+        The tile index in one wave.
+    group_size : tir.PrimExpr
+        The group size.
+    """
+    return _ffi_api.Persistent(domain, wave_size, index, group_size)
+
+
+def Pipelined(
+    start: tir.PrimExpr,
+    stop: tir.PrimExpr = None,
+    num_stages: int = 0,
+    order: list[int] | None = None,
+    stage: list[int] | None = None,
+    sync: list[list[int]] | None = None,
+    group: list[list[int]] | None = None,
+):
+    """Tools to construct pipelined for loop.
+
+    Parameters
+    ----------
+    start : PrimExpr
+        The minimum value of iteration.
+    stop : PrimExpr
+        The maximum value of iteration.
+    num_stages : int
+        The max number of buffer used between pipeline producers and consumers.
+        if num_stages is 0, pipeline will not be enabled.
+    Returns
+    -------
+    res : frame.ForFrame
+        The ForFrame.
+    """
+    if stop is None:
+        stop = start
+        start = IntImm(start.dtype, 0) if hasattr(start, "dtype") else 0
+    if order is None:
+        order = []
+    if stage is None:
+        stage = []
+    if sync is None:
+        sync = []
+    if group is None:
+        group = []
+    # type: ignore[attr-defined] # pylint: disable=no-member
+    return _ffi_api.Pipelined(start, stop, num_stages, order, stage, sync, group)
+
+
+def serial(start: tir.PrimExpr,
+           stop: tir.PrimExpr | None = None,
+           step: tir.PrimExpr | None = None,
+           *,
+           annotations: dict[str, Any] | None = None):
+    if step is None or step == 1:
+        return tb_tir.serial(start, stop, annotations=annotations)
+    else:
+        if stop is None:
+            stop = start
+            start = IntImm(start.dtype, 0) if hasattr(start, "dtype") else 0
+        return SerialForWithStep(start, stop, step, annotations=annotations)

tilelang/language/v2/builder.py

@@ -95,6 +95,14 @@ class BreakFrame(Frame):
     ...
 
 
+@dataclass
+class SerialForWithStep:
+    start: PrimExpr
+    stop: PrimExpr
+    step: PrimExpr
+    annotations: dict[str, Any] | None = None
+
+
 ContinueOrBreak = ContinueFrame | BreakFrame
 AnyFrame = tir.frame.IRBuilderFrame | Frame
 
@@ -236,12 +244,27 @@ def eval(self, val: Any):
     def ctx_for(self, it):
         self.check_continue_break()
         it = unwrap_expr(it)
-        if not isinstance(it, tir.frame.ForFrame):
-            raise TypeError(
-                f"Invalid for loop, got {it}({type(it)}), expect one of the following: "
-                "range, T.serial, T.grid, T.parallel, T.vectorized, T.unroll, T.thread_binding")
-        with self.with_frame(it) as v:
-            yield v
+        if isinstance(it, SerialForWithStep):
+            real_stop = tir.ceildiv(it.stop - it.start, it.step)
+            if isinstance(it.step, (int, IntImm)):
+                value = it.step if isinstance(it.step, int) else it.step.value
+                if value < 0:
+                    real_stop = tir.ceildiv(it.start - it.stop, -it.step)
+            else:
+                logger.warning(
+                    f'Using a non-constant step `{it.step}` in stepped serial may lead to undefined behavior in tilelang'
+                )
+            real_frame = tir.serial(real_stop, annotations=it.annotations)
+            with self.with_frame(real_frame) as v:
+                IRBuilder.name('_tmp', v)
+                yield it.start + v * it.step
+        else:
+            if not isinstance(it, tir.frame.ForFrame):
+                raise TypeError(
+                    f"Invalid for loop, got {it}({type(it)}), expect one of the following: "
+                    "range, T.serial, T.grid, T.parallel, T.vectorized, T.unroll, T.thread_binding")
+            with self.with_frame(it) as v:
+                yield v
 
     def ctx_continue(self):
         self.check_continue_break()
@@ -449,8 +472,9 @@ def arg(self, name, value):
                 f"Unsupported argument type: {value}({type(value)}) for argument `{name}`.")
 
     def override(self, name: str):
+        import tilelang.language as T
         if name == 'range':
-            return tir.serial
+            return T.serial
         raise ValueError(f'Unknown override: {name}')