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Posted to commits@tvm.apache.org by "MellowArtisan (via GitHub)" <gi...@apache.org> on 2024/07/26 17:23:43 UTC
[I] [Bug] [Relax] cannot remove the hint_on_device [tvm]
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
```
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Re: [I] [Bug] [Relax] cannot remove the hint_on_device [tvm]
Posted by "MellowArtisan (via GitHub)" <gi...@apache.org>.
MellowArtisan commented on issue #17205:
URL: https://github.com/apache/tvm/issues/17205#issuecomment-2253185960
Hi all, I found the `tvm.transform.Sequential([relax.transform.RealizeVDevice()])(mod)` can remove the "R.hint_on_device()", however, using `relax.transform.RealizeVDevice()(mod)` directly cannot remove it.
@Lunderberg @tqchen Why do the different usages for the same pass (i.e., RealizeVDevice) give different optimization results?
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Re: [I] [Bug] [Relax] cannot remove the hint_on_device [tvm]
Posted by "Hzfengsy (via GitHub)" <gi...@apache.org>.
Hzfengsy closed issue #17205: [Bug] [Relax] cannot remove the hint_on_device
URL: https://github.com/apache/tvm/issues/17205
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Re: [I] [Bug] [Relax] cannot remove the hint_on_device [tvm]
Posted by "Lunderberg (via GitHub)" <gi...@apache.org>.
Lunderberg commented on issue #17205:
URL: https://github.com/apache/tvm/issues/17205#issuecomment-2253337351
Aha! The problem is that `HintOnDeviceRemover` (the first step of `RealizeVDevice`) is mutating the relax expression in-place, which is not legal. As a result, expressions that are in the input `Module` are being mutated to have different `StructInfo`. The second time that `RealizeVDevice` is applied, its input has been mutated to already include `vdevice` annotations.
```python
## Running these commands
Module["foo"].show(name="Before")
relax.transform.RealizeVDevice()(Module)
Module["foo"].show(name="OrigAfter")
## Produces the following output
@R.function
def Before(
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"):
R.func_attr({"global_symbol": "foo"})
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
@R.function
def OrigAfter(
x: R.Tensor((2, 3), dtype="float32"),
y: R.Tensor((2, 3), dtype="float32", vdevice="llvm:-1"),
z: R.Tensor((2, 3), dtype="float32"),
) -> R.Tensor((2, 3), dtype="float32"):
R.func_attr({"global_symbol": "foo"})
with R.dataflow():
lv0: R.Tensor((2, 3), dtype="float32", vdevice="llvm:-1") = R.hint_on_device(
y, R.device(dev_type=1, dev_id=0)
)
R.output(lv0)
return lv0
```
The input module should never be modified when running any `IRModule` transform, so this is definitely a bug.
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Re: [I] [Bug] [Relax] cannot remove the hint_on_device [tvm]
Posted by "Cookiee235 (via GitHub)" <gi...@apache.org>.
Cookiee235 commented on issue #17205:
URL: https://github.com/apache/tvm/issues/17205#issuecomment-2256418031
> @Cookiee235 Can you verify the fix implemented in #17213? It removes the in-place mutation from `RealizeVDevice`, and should resolve this issue.
@Lunderberg Yes! This PR fixed the bug. Thanks for your efforts!
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Re: [I] [Bug] [Relax] cannot remove the hint_on_device [tvm]
Posted by "Lunderberg (via GitHub)" <gi...@apache.org>.
Lunderberg commented on issue #17205:
URL: https://github.com/apache/tvm/issues/17205#issuecomment-2256236520
@Cookiee235 Can you verify the fix implemented in #17213? It removes the in-place mutation from `RealizeVDevice`, and should resolve this issue.
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Re: [I] [Bug] [Relax] cannot remove the hint_on_device [tvm]
Posted by "Hzfengsy (via GitHub)" <gi...@apache.org>.
Hzfengsy closed issue #17205: [Bug] [Relax] cannot remove the hint_on_device
URL: https://github.com/apache/tvm/issues/17205
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Re: [I] [Bug] [Relax] cannot remove the hint_on_device [tvm]
Posted by "Lunderberg (via GitHub)" <gi...@apache.org>.
Lunderberg commented on issue #17205:
URL: https://github.com/apache/tvm/issues/17205#issuecomment-2253301281
Hmm. It looks like it's even weirder. It looks like only the first use of `RealizeVDevice` produces the correct output. The first execution correctly removes the `R.hint_on_device`, but the second execution does not.
```python
relax.transform.RealizeVDevice()(Module).show(name='First')
relax.transform.RealizeVDevice()(Module).show(name='Second')
```
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