slyubomirsky commented on code in PR #15026:
URL: https://github.com/apache/tvm/pull/15026#discussion_r1220318486
##########
python/tvm/relax/utils.py:
##########
@@ -455,10 +462,14 @@ def _shape_with_old_tir_var(
# with old set of variables.
tir_var_inverse_map = {v: k for k, v in tir_var_map.items()}
- output_sinfo = [
- TensorStructInfo(_shape_with_old_tir_var(out.shape,
tir_var_inverse_map), out.dtype)
- for out in outs
- ]
+ def te_to_sinfo(arg):
+ return TensorStructInfo(_shape_with_old_tir_var(arg.shape,
tir_var_inverse_map), arg.dtype)
+
+ input_sinfo = [te_to_sinfo(arg) for arg in te_args]
+ output_sinfo = [te_to_sinfo(out) for out in outs]
+
+ primfunc_sinfo = FuncStructInfo([*input_sinfo, *output_sinfo],
PrimStructInfo("void"))
+ _update_struct_info(tir_func, primfunc_sinfo)
Review Comment:
@tqchen Is this consistent with how we want `FuncStructInfo` to work? I
thought `PrimFunc`s would be `ObjectStructInfo` (this is what we wrote in the
Relax spec). Perhaps they use a `derive_func` instead? If we want them to use
ordinary `FuncStructInfo`, does that also mean we'll allow them to be called
outside of `call_tir`?
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