comaniac commented on a change in pull request #9737:
URL: https://github.com/apache/tvm/pull/9737#discussion_r769071320
##########
File path: python/tvm/contrib/cutlass/gen_conv2d.py
##########
@@ -121,27 +131,67 @@ def get_default(self, out_dtype):
data_type = gemm_profile_result["data_type"]
return create_conv2d_operator([tile_description], data_type,
[alignment])[0]
+ def check_align(self, op_name, C, K):
+ """Filter out kernels that cannot be supported."""
+ aligns = re.findall(r"align[1|2|4|8]", op_name)
+ assert len(aligns) == 1
+ align = int(aligns[0][-1])
+ return all([dim % align == 0 for dim in [C, K]])
+
def profile(
- self, d_shape, w_shape, out_shape, out_dtype, profile_all=True,
use_multiprocessing=False
+ self,
+ d_shape,
+ w_shape,
+ padding,
+ stride,
+ dilation,
+ out_dtype,
+ profile_all=True,
+ use_multiprocessing=False,
):
"""Profile and select the best kernel from candidate kernels.
If profile_all is False, return immediately after the first applicable
kernel is found.
If use_multiprocessing is True, compile all profiler executables in
parallel.
"""
- B, _, _, IC = d_shape
+ N, H, W, IC = d_shape
OC, R, S, _ = w_shape
- _, P, Q, _ = out_shape
+ workload = (
+ N,
+ H,
+ W,
+ IC,
+ OC,
+ R,
+ S,
+ padding[0],
+ padding[1],
+ stride[0],
+ stride[1],
+ dilation[0],
+ dilation[1],
+ )
- M = B * P * Q
- N = OC
- K = R * S * IC
+ if workload in self.cache:
+ return self.cache[workload]
- gemm_profile_result = self.gemm_profiler.profile(
- M, N, K, out_dtype, profile_all=profile_all,
use_multiprocessing=use_multiprocessing
- )
+ ops = GENERATOR_FUNC_TABLE[self.sm](out_dtype,
op_creator=create_conv2d_operator)
+ ops = list(filter(lambda op: self.check_align(op["name"], IC, OC),
ops))
- tile_description = gemm_profile_result["tile_description"]
- alignment = gemm_profile_result["alignment"]
- data_type = gemm_profile_result["data_type"]
+ if profile_all:
+ self.engine.compile_all(ops, use_multiprocessing)
- return create_conv2d_operator([tile_description], data_type,
[alignment])[0]
+ args = (
+ "--n=%d --h=%d --w=%d --c=%d --k=%d --r=%d --s=%d --pad_h=%d
--pad_w=%d "
+ "--stride_h=%d --stride_w=%d --dilation_h=%d --dilation_w=%d"
+ ) % workload
+
+ for op in ops:
+ out = self.engine.evaluate(op, args.split(" "))
+ op["runtime"] = out
+ if out > 0 and not profile_all:
Review comment:
IIUC, now you changed `evaluate` to return `float("inf")` when invalid.
Then the fist invalid kernel will be selected since `float("inf") > 0`, right?
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