Cookiee235 opened a new issue, #17269:
URL: https://github.com/apache/tvm/issues/17269
### Actual behavior
```
Traceback (most recent call last):
File "/share_container/optfuzz/res/bugs/assert_lazy.py", line 52, in
<module>
mod = relax.transform.LazyTransformParams()(mod)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm-lunder/python/tvm/ir/transform.py", line 238, in
__call__
return _ffi_transform_api.RunPass(self, mod)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm-lunder/python/tvm/_ffi/_ctypes/packed_func.py", line
240, in __call__
raise_last_ffi_error()
File "/software/tvm-lunder/python/tvm/_ffi/base.py", line 481, in
raise_last_ffi_error
raise py_err
File "/software/tvm-lunder/python/tvm/ir/transform.py", line 307, in
_pass_func
return inst.transform_module(mod, ctx)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/software/tvm-lunder/python/tvm/relax/transform/lazy_transform_params.py",
line 396, in transform_module
func = lazy_mutator.transform(func)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/software/tvm-lunder/python/tvm/relax/transform/lazy_transform_params.py",
line 151, in transform
forward_collector.visit_expr(func)
File "/software/tvm-lunder/python/tvm/relax/expr_functor.py", line 346, in
visit_expr
return _ffi_api.PyExprVisitorVisitExpr(self, expr) # type: ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm-lunder/python/tvm/meta_schedule/utils.py", line 76, in
method
return getattr(inst, name)(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/software/tvm-lunder/python/tvm/relax/transform/lazy_transform_params.py",
line 59, in visit_var_binding_
assert isinstance(binding.value, relax.Tuple)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
AssertionError
```
### Steps to reproduce
```
import tvm
from tvm import relax
from tvm.script import ir as I
from tvm.script import tir as T
from tvm.script import relax as R
@I.ir_module
class Module:
@T.prim_func(private=True)
def add(C: T.Buffer((T.int64(16), T.int64(16)), "float32"), B:
T.Buffer((T.int64(16), T.int64(16)), "float32"), T_add: T.Buffer((T.int64(16),
T.int64(16)), "float32")):
T.func_attr({"tir.noalias": T.bool(True)})
# with T.block("root"):
for ax0, ax1 in T.grid(T.int64(16), T.int64(16)):
with T.block("T_add"):
v_ax0, v_ax1 = T.axis.remap("SS", [ax0, ax1])
T.reads(C[v_ax0, v_ax1], B[v_ax0, v_ax1])
T.writes(T_add[v_ax0, v_ax1])
T_add[v_ax0, v_ax1] = C[v_ax0, v_ax1] + B[v_ax0, v_ax1]
@T.prim_func(private=True)
def multiply(A: T.Buffer((T.int64(16), T.int64(16)), "float32"),
T_multiply: T.Buffer((T.int64(16), T.int64(16)), "float32")):
T.func_attr({"tir.noalias": T.bool(True)})
# with T.block("root"):
for ax0, ax1 in T.grid(T.int64(16), T.int64(16)):
with T.block("T_multiply"):
v_ax0, v_ax1 = T.axis.remap("SS", [ax0, ax1])
T.reads(A[v_ax0, v_ax1])
T.writes(T_multiply[v_ax0, v_ax1])
T_multiply[v_ax0, v_ax1] = A[v_ax0, v_ax1] * T.float32(2)
@R.function
def transform_params(A: R.Tensor((16, 16), dtype="float32"), B:
R.Tensor((16, 16), dtype="float32")) -> R.Tuple(R.Tensor((16, 16),
dtype="float32"), R.Tensor((16, 16), dtype="float32")):
cls = Module
C = R.call_tir(cls.multiply, (A,), out_sinfo=R.Tensor((16, 16),
dtype="float32"))
D = R.call_tir(cls.add, (C, B), out_sinfo=R.Tensor((16, 16),
dtype="float32"))
para0: R.Tensor((16, 16), dtype="float32") = B
para1: R.Tensor((16, 16), dtype="float32") = B
res: R.Tuple(R.Tensor((16, 16), dtype="float32"), R.Tensor((16, 16),
dtype="float32")) = cls.transform_params_7(para0, para1)
return res
@R.function
def transform_params_2(A: R.Tensor((16, 16), dtype="float32"), B:
R.Tensor((16, 16), dtype="float32")) -> R.Tuple(R.Tensor((16, 16),
dtype="float32"), R.Tensor((16, 16), dtype="float32")):
cls = Module
C = R.call_tir(cls.multiply, (A,), out_sinfo=R.Tensor((16, 16),
dtype="float32"))
D = R.call_tir(cls.add, (C, B), out_sinfo=R.Tensor((16, 16),
dtype="float32"))
return (D, D)
mod = Module
mod = relax.transform.LazyTransformParams()(mod) # crash here
```
cc @Lunderberg @junrushao
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