MellowArtisan opened a new issue, #17205:
URL: https://github.com/apache/tvm/issues/17205
### Actual behavior
```
Traceback (most recent call last):
File "/share_container/optfuzz/res/bugs/7bug_assert.py", line 25, in
<module>
tvm.ir.assert_structural_equal(mod_seq, mod) # assert failed
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm/python/tvm/ir/base.py", line 256, in
assert_structural_equal
_ffi_node_api.StructuralEqual(lhs, rhs, True, map_free_vars) # type:
ignore # pylint: disable=no-member
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm/python/tvm/_ffi/_ctypes/packed_func.py", line 239, in
__call__
raise_last_ffi_error()
File "/software/tvm/python/tvm/_ffi/base.py", line 481, in
raise_last_ffi_error
raise py_err
ValueError: Traceback (most recent call last):
5: _ZN3tvm7runtime13PackedFuncObj9ExtractorINS0_1
4: tvm::runtime::TypedPackedFunc<bool (tvm::runtime::ObjectRef const&,
tvm::runtime::ObjectRef const&, bool,
bool)>::AssignTypedLambda<tvm::{lambda(tvm::runtime::ObjectRef const&,
tvm::runtime::ObjectRef const&, bool,
bool)#3}>(tvm::{lambda(tvm::runtime::ObjectRef const&, tvm::runtime::ObjectRef
const&, bool, bool)#3}, std::__cxx11::basic_string<char,
std::char_traits<char>, std::allocator<char> >)::{lambda(tvm::runtime::TVMArgs
const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs
const&, tvm::runtime::TVMRetValue*) const
3: _ZN3tvm20SEqualHandlerDefault5EqualERKNS_
2: tvm::SEqualHandlerDefault::Impl::Equal(tvm::runtime::ObjectRef const&,
tvm::runtime::ObjectRef const&, bool)
1: tvm::SEqualHandlerDefault::Impl::RunTasks()
0: tvm::SEqualHandlerDefault::Impl::CheckResult(bool,
tvm::runtime::ObjectRef const&, tvm::runtime::ObjectRef const&,
tvm::runtime::Optional<tvm::ObjectPathPair> const&)
File "/software/tvm/src/node/structural_equal.cc", line 392
ValueError: StructuralEqual check failed, caused by lhs at
<root>.functions[I.GlobalVar("foo")].body.blocks[0].bindings[0].value:
# from tvm.script import ir as I
# from tvm.script import relax as R
@I.ir_module
class Module:
I.module_attrs({"attr": 10})
I.module_global_infos({"vdevice": [I.vdevice({"keys": ["cpu"], "kind":
"llvm", "mtriple": "x86_64-unknown-linux-gnu", "tag": ""}, 0, "global"),
I.vdevice({"arch": "sm_50", "keys": ["cuda", "gpu"], "kind": "cuda",
"max_num_threads": 1024, "tag": "", "thread_warp_size": 32}, 0, "global"),
I.vdevice({"keys": ["metal", "gpu"], "kind": "metal", "max_function_args": 31,
"max_num_threads": 256, "max_shared_memory_per_block": 32768,
"max_threads_per_block": 256, "tag": "", "thread_warp_size": 16}, 0, "global"),
I.vdevice({"arch": "sm_80", "keys": ["cuda", "gpu"], "kind": "cuda",
"max_num_threads": 1024, "tag": "", "thread_warp_size": 32}, 0, "global")]})
@R.function
def foo(x: R.Tensor((2, 3), dtype="float32"), y: R.Tensor((2, 3),
dtype="float32", vdevice="llvm:0"), z: R.Tensor((2, 3), dtype="float32")) ->
R.Tensor((2, 3), dtype="float32", vdevice="llvm:0"):
with R.dataflow():
lv0: R.Tensor((2, 3), dtype="float32", vdevice="llvm:0") = y
^
R.output(lv0)
return lv0
and rhs at
<root>.functions[I.GlobalVar("foo")].body.blocks[0].bindings[0].value:
# from tvm.script import ir as I
# from tvm.script import relax as R
@I.ir_module
class Module:
I.module_attrs({"attr": 10})
I.module_global_infos({"vdevice": [I.vdevice({"keys": ["cpu"], "kind":
"llvm", "mtriple": "x86_64-unknown-linux-gnu", "tag": ""}, 0, "global"),
I.vdevice({"arch": "sm_50", "keys": ["cuda", "gpu"], "kind": "cuda",
"max_num_threads": 1024, "tag": "", "thread_warp_size": 32}, 0, "global"),
I.vdevice({"keys": ["metal", "gpu"], "kind": "metal", "max_function_args": 31,
"max_num_threads": 256, "max_shared_memory_per_block": 32768,
"max_threads_per_block": 256, "tag": "", "thread_warp_size": 16}, 0, "global"),
I.vdevice({"arch": "sm_80", "keys": ["cuda", "gpu"], "kind": "cuda",
"max_num_threads": 1024, "tag": "", "thread_warp_size": 32}, 0, "global")]})
@R.function
def foo(x: R.Tensor((2, 3), dtype="float32"), y: R.Tensor((2, 3),
dtype="float32", vdevice="llvm:0"), z: R.Tensor((2, 3), dtype="float32")) ->
R.Tensor((2, 3), dtype="float32", vdevice="llvm:0"):
with R.dataflow():
lv0: R.Tensor((2, 3), dtype="float32", vdevice="llvm:0") =
R.hint_on_device(y, R.device(dev_type=1, dev_id=0))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
R.output(lv0)
return lv0
```
### Environment
TVM: 0.17.dev0
### 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:
I.module_attrs({"attr": 10})
I.module_global_infos({"vdevice": [I.vdevice({"keys": ["cpu"], "kind":
"llvm", "mtriple": "x86_64-unknown-linux-gnu", "tag": ""}, 0, "global"),
I.vdevice({"arch": "sm_50", "keys": ["cuda", "gpu"], "kind": "cuda",
"max_num_threads": 1024, "tag": "", "thread_warp_size": 32}, 0, "global"),
I.vdevice({"keys": ["metal", "gpu"], "kind": "metal", "max_function_args": 31,
"max_num_threads": 256, "max_shared_memory_per_block": 32768,
"max_threads_per_block": 256, "tag": "", "thread_warp_size": 16}, 0, "global"),
I.vdevice({"arch": "sm_80", "keys": ["cuda", "gpu"], "kind": "cuda",
"max_num_threads": 1024, "tag": "", "thread_warp_size": 32}, 0, "global")]})
@R.function
def foo(x: R.Tensor((2, 3), dtype="float32"), y: R.Tensor((2, 3),
dtype="float32"), z: R.Tensor((2, 3), dtype="float32")) -> R.Tensor((2, 3),
dtype="float32"):
cls = Module
with R.dataflow():
lv0: R.Tensor((2, 3), dtype="float32") = R.hint_on_device(y,
R.device(dev_type=1, dev_id=0))
R.output(lv0)
return lv0
mod = Module
mod_seq = tvm.transform.Sequential([relax.transform.RealizeVDevice()])(mod)
mod = relax.transform.RealizeVDevice()(mod)
mod_seq.show()
mod.show() # cannot remove the 'hint_on_device'
tvm.ir.assert_structural_equal(mod_seq, mod) # assert failed
```
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
