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[CUDA] Improve adaptive and global pool schedule #8936

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Merged
comaniac merged 4 commits into from
Sep 6, 2021
Merged

[CUDA] Improve adaptive and global pool schedule #8936

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ab01583
use reduction schedule for adaptive pool
Sep 5, 2021
f81e5bb
improve adaptive pool schedule
Sep 6, 2021
87a10ec
simplify
Sep 6, 2021
5c68288
fixed global pooling with fused ops
Sep 6, 2021
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36 changes: 19 additions & 17 deletions python/tvm/topi/cuda/pooling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,8 @@
from tvm import te
from .. import tag
from ..utils import traverse_inline
from .reduction import _schedule_reduce
from .injective import schedule_injective_from_existing


def schedule_adaptive_pool(outs, layout="NCHW"):
Expand All @@ -39,29 +41,20 @@ def schedule_adaptive_pool(outs, layout="NCHW"):
outs = [outs] if isinstance(outs, te.tensor.Tensor) else outs
s = te.create_schedule([x.op for x in outs])

def _schedule(Pool):
num_thread = 8
block_x = te.thread_axis("blockIdx.x")
block_y = te.thread_axis("blockIdx.y")
thread_x = te.thread_axis((0, num_thread), "threadIdx.x")
thread_y = te.thread_axis((0, num_thread), "threadIdx.y")
def _schedule_non_global(Pool):
if Pool.op in s.outputs:
Out = Pool
OL = s.cache_write(Pool, "local")
else:
Out = outs[0].op.output(0)
s[Pool].set_scope("local")

by, ty = s[Out].split(s[Out].op.axis[0], factor=num_thread)
if layout == "NHWC":
bx, tx = s[Out].split(s[Out].op.axis[3], factor=num_thread)
else:
bx, tx = s[Out].split(s[Out].op.axis[1], factor=num_thread)
s[Out].reorder(by, bx, ty, tx)
s[Out].bind(ty, thread_y)
s[Out].bind(tx, thread_x)
s[Out].bind(by, block_y)
s[Out].bind(bx, block_x)
max_threads = int(tvm.target.Target.current(allow_none=False).max_num_threads)
fused_axis = s[Out].fuse(*s[Out].op.axis)
bx, tx = s[Out].split(fused_axis, factor=max_threads)
s[Out].bind(bx, te.thread_axis("blockIdx.x"))
s[Out].bind(tx, te.thread_axis("threadIdx.x"))

if Pool.op in s.outputs:
s[OL].compute_at(s[Out], tx)
else:
Expand All @@ -81,7 +74,16 @@ def traverse(OP):
# schedule global_pool
elif OP.tag.startswith("adaptive_pool"):
Pool = OP.output(0)
_schedule(Pool)
oshape = Pool.shape
if (layout == "NCHW" and oshape[2] == 1 and oshape[3] == 1) or (
layout == "NHWC" and oshape[1] == 1 and oshape[2] == 1
):
_schedule_reduce(OP, s)
if OP != outs[0].op:
# the final division for adaptive pool or fused elemwise ops
schedule_injective_from_existing(s, outs[0])
else:
_schedule_non_global(Pool)
else:
raise RuntimeError("Unsupported operator: %s" % OP.tag)

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