You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2022/04/21 18:50:50 UTC
[GitHub] [tvm] alnah005 commented on pull request #10216: fixed tuple error
alnah005 commented on PR #10216:
URL: https://github.com/apache/tvm/pull/10216#issuecomment-1105634235
> @alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?
I ran the tests on my end after your message and all the tests in the file are failing. I also ran the tests before my additions and they also failed.
Here's the output I got after running without my additions:
```
tests/python/relay/test_op_qnn_dense.py data types int64 and int32 do not match in BroadcastRel
data types int64 and int32 do not match in BroadcastRel
FThe Relay type checker is unable to show the following types match.
In particular `Tensor[(3), int32]` does not match `Tensor[(3), int64]`
FThe Relay type checker is unable to show the following types match.
In particular `Tensor[(3), int32]` does not match `Tensor[(3), int64]`
FThe Relay type checker is unable to show the following types match.
In particular `Tensor[(3), int32]` does not match `Tensor[(3), int64]`
F
================================================================================================= FAILURES =================================================================================================
_______________________________________________________________________________________ test_qnn_dense_without_bias ________________________________________________________________________________________
def test_qnn_dense_without_bias():
with TempOpAttr("qnn.dense", "FTVMQnnLegalize", legalize_qnn_dense):
int32_output_without_bias_params = make_int_configuration(use_bias=False)
> qnn_dense_driver(int32_output_without_bias_params)
tests/python/relay/test_op_qnn_dense.py:230:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/python/relay/test_op_qnn_dense.py:211: in qnn_dense_driver
mod = relay.qnn.transform.CanonicalizeOps()(mod)
../tvm/python/tvm/ir/transform.py:161: in __call__
return _ffi_transform_api.RunPass(self, mod)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <tvm.runtime.packed_func.PackedFunc object at 0x110a38500>
args = (Run Function pass: Legalize at the optimization level 1, #[version = "0.0.5"]
def @main(%quantized_data: Tensor[(2, 1...=int32 */, 0.5f /* ty=float32 */, 0.5f /* ty=float32 */, units=3, out_dtype="int64") /* ty=Tensor[(2, 3), int64] */
}
)
temp_args = [], values = <tvm._ffi._ctypes.packed_func.TVMValue_Array_2 object at 0x137ceef40>, tcodes = <tvm._ffi._ctypes.packed_func.c_int_Array_2 object at 0x137d1ca40>
def __call__(self, *args):
"""Call the function with positional arguments
args : list
The positional arguments to the function call.
"""
temp_args = []
values, tcodes, num_args = _make_tvm_args(args, temp_args)
ret_val = TVMValue()
ret_tcode = ctypes.c_int()
if (
_LIB.TVMFuncCall(
self.handle,
values,
tcodes,
ctypes.c_int(num_args),
ctypes.byref(ret_val),
ctypes.byref(ret_tcode),
)
!= 0
):
> raise get_last_ffi_error()
E tvm.error.DiagnosticError: Traceback (most recent call last):
E [bt] (8) 9 libtvm.dylib 0x000000012c36f870 tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 256
E [bt] (7) 8 libtvm.dylib 0x000000012d6e7c63 tvm::relay::transform::FunctionPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 2595
E [bt] (6) 7 libtvm.dylib 0x000000012c36f66e tvm::transform::Pass::operator()(tvm::IRModule) const + 158
E [bt] (5) 6 libtvm.dylib 0x000000012c36f870 tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 256
E [bt] (4) 5 libtvm.dylib 0x000000012c36ff13 tvm::transform::ModulePassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 819
E [bt] (3) 4 libtvm.dylib 0x000000012d5551e4 tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<void tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::IRModule, tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::transform::InferType()::$_2>(tvm::relay::transform::InferType()::$_2)::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) + 1844
E [bt] (2) 3 libtvm.dylib 0x000000012c2f73eb tvm::DiagnosticContext::Render() + 459
E [bt] (1) 2 libtvm.dylib 0x000000012c02b969 tvm::runtime::detail::LogFatal::Entry::Finalize() + 89
E [bt] (0) 1 libtvm.dylib 0x000000012d8bb4b8 tvm::runtime::Backtrace() + 24
E File "/Users/suhail/tvm/src/ir/diagnostic.cc", line 105
E DiagnosticError: one or more error diagnostics were emitted, please check diagnostic render for output.
../tvm/python/tvm/_ffi/_ctypes/packed_func.py:237: DiagnosticError
_________________________________________________________________________________________ test_qnn_dense_with_bias _________________________________________________________________________________________
def test_qnn_dense_with_bias():
with TempOpAttr("qnn.dense", "FTVMQnnLegalize", legalize_qnn_dense):
int32_output_with_bias_params = make_int_configuration(use_bias=True)
> qnn_dense_driver(int32_output_with_bias_params)
tests/python/relay/test_op_qnn_dense.py:237:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/python/relay/test_op_qnn_dense.py:210: in qnn_dense_driver
mod = relay.transform.InferType()(mod)
../tvm/python/tvm/ir/transform.py:161: in __call__
return _ffi_transform_api.RunPass(self, mod)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <tvm.runtime.packed_func.PackedFunc object at 0x110a38500>
args = (Run Module pass: InferType at the optimization level 0, #[version = "0.0.5"]
def @main(%quantized_data: Tensor[(2, 10...dense(%quantized_data, %quantized_kernel, -1, -1, 0.5f, 0.5f, units=3, out_dtype="int64");
nn.bias_add(%0, %bias)
}
)
temp_args = [], values = <tvm._ffi._ctypes.packed_func.TVMValue_Array_2 object at 0x137d5b840>, tcodes = <tvm._ffi._ctypes.packed_func.c_int_Array_2 object at 0x137d5b940>
def __call__(self, *args):
"""Call the function with positional arguments
args : list
The positional arguments to the function call.
"""
temp_args = []
values, tcodes, num_args = _make_tvm_args(args, temp_args)
ret_val = TVMValue()
ret_tcode = ctypes.c_int()
if (
_LIB.TVMFuncCall(
self.handle,
values,
tcodes,
ctypes.c_int(num_args),
ctypes.byref(ret_val),
ctypes.byref(ret_tcode),
)
!= 0
):
> raise get_last_ffi_error()
E tvm.error.DiagnosticError: Traceback (most recent call last):
E [bt] (8) 9 libtvm.dylib 0x000000012d8a02ae TVMFuncCall + 62
E [bt] (7) 8 libtvm.dylib 0x000000012c378ff4 tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<void tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::transform::Pass, tvm::IRModule)>::AssignTypedLambda<tvm::transform::$_6>(tvm::transform::$_6, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >)::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) + 948
E [bt] (6) 7 libtvm.dylib 0x000000012c36f66e tvm::transform::Pass::operator()(tvm::IRModule) const + 158
E [bt] (5) 6 libtvm.dylib 0x000000012c36f870 tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 256
E [bt] (4) 5 libtvm.dylib 0x000000012c36ff13 tvm::transform::ModulePassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 819
E [bt] (3) 4 libtvm.dylib 0x000000012d5551e4 tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<void tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::IRModule, tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::transform::InferType()::$_2>(tvm::relay::transform::InferType()::$_2)::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) + 1844
E [bt] (2) 3 libtvm.dylib 0x000000012c2f73eb tvm::DiagnosticContext::Render() + 459
E [bt] (1) 2 libtvm.dylib 0x000000012c02b969 tvm::runtime::detail::LogFatal::Entry::Finalize() + 89
E [bt] (0) 1 libtvm.dylib 0x000000012d8bb4b8 tvm::runtime::Backtrace() + 24
E File "/Users/suhail/tvm/src/ir/diagnostic.cc", line 105
E DiagnosticError: one or more error diagnostics were emitted, please check diagnostic render for output.
../tvm/python/tvm/_ffi/_ctypes/packed_func.py:237: DiagnosticError
__________________________________________________________________________________ test_qnn_dense_with_requantized_output __________________________________________________________________________________
def test_qnn_dense_with_requantized_output():
with TempOpAttr("qnn.dense", "FTVMQnnLegalize", legalize_qnn_dense):
int8_requantized_output_with_bias_params = make_int_configuration(
use_bias=True, requantize_output=True
)
> qnn_dense_driver(int8_requantized_output_with_bias_params)
tests/python/relay/test_op_qnn_dense.py:246:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/python/relay/test_op_qnn_dense.py:210: in qnn_dense_driver
mod = relay.transform.InferType()(mod)
../tvm/python/tvm/ir/transform.py:161: in __call__
return _ffi_transform_api.RunPass(self, mod)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <tvm.runtime.packed_func.PackedFunc object at 0x110a38500>
args = (Run Module pass: InferType at the optimization level 0, #[version = "0.0.5"]
def @main(%quantized_data: Tensor[(2, 10...nits=3, out_dtype="int64");
%1 = nn.bias_add(%0, %bias);
qnn.requantize(%1, 0.25f, 0, 1f, -1, out_dtype="int8")
}
)
temp_args = [], values = <tvm._ffi._ctypes.packed_func.TVMValue_Array_2 object at 0x137d5bec0>, tcodes = <tvm._ffi._ctypes.packed_func.c_int_Array_2 object at 0x137d607c0>
def __call__(self, *args):
"""Call the function with positional arguments
args : list
The positional arguments to the function call.
"""
temp_args = []
values, tcodes, num_args = _make_tvm_args(args, temp_args)
ret_val = TVMValue()
ret_tcode = ctypes.c_int()
if (
_LIB.TVMFuncCall(
self.handle,
values,
tcodes,
ctypes.c_int(num_args),
ctypes.byref(ret_val),
ctypes.byref(ret_tcode),
)
!= 0
):
> raise get_last_ffi_error()
E tvm.error.DiagnosticError: Traceback (most recent call last):
E [bt] (8) 9 libtvm.dylib 0x000000012d8a02ae TVMFuncCall + 62
E [bt] (7) 8 libtvm.dylib 0x000000012c378ff4 tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<void tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::transform::Pass, tvm::IRModule)>::AssignTypedLambda<tvm::transform::$_6>(tvm::transform::$_6, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >)::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) + 948
E [bt] (6) 7 libtvm.dylib 0x000000012c36f66e tvm::transform::Pass::operator()(tvm::IRModule) const + 158
E [bt] (5) 6 libtvm.dylib 0x000000012c36f870 tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 256
E [bt] (4) 5 libtvm.dylib 0x000000012c36ff13 tvm::transform::ModulePassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 819
E [bt] (3) 4 libtvm.dylib 0x000000012d5551e4 tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<void tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::IRModule, tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::transform::InferType()::$_2>(tvm::relay::transform::InferType()::$_2)::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) + 1844
E [bt] (2) 3 libtvm.dylib 0x000000012c2f73eb tvm::DiagnosticContext::Render() + 459
E [bt] (1) 2 libtvm.dylib 0x000000012c02b969 tvm::runtime::detail::LogFatal::Entry::Finalize() + 89
E [bt] (0) 1 libtvm.dylib 0x000000012d8bb4b8 tvm::runtime::Backtrace() + 24
E File "/Users/suhail/tvm/src/ir/diagnostic.cc", line 105
E DiagnosticError: one or more error diagnostics were emitted, please check diagnostic render for output.
../tvm/python/tvm/_ffi/_ctypes/packed_func.py:237: DiagnosticError
______________________________________________________________________________________ test_per_channel_weight_scale _______________________________________________________________________________________
def test_per_channel_weight_scale():
with TempOpAttr("qnn.dense", "FTVMQnnLegalize", legalize_qnn_dense):
config = make_int_configuration(use_bias=True, requantize_output=True, per_channel=True)
> qnn_dense_driver(config)
tests/python/relay/test_op_qnn_dense.py:252:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/python/relay/test_op_qnn_dense.py:210: in qnn_dense_driver
mod = relay.transform.InferType()(mod)
../tvm/python/tvm/ir/transform.py:161: in __call__
return _ffi_transform_api.RunPass(self, mod)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <tvm.runtime.packed_func.PackedFunc object at 0x110a38500>
args = (Run Module pass: InferType at the optimization level 0, #[version = "0.0.5"]
def @main(%quantized_data: Tensor[(2, 10...0AAAAAAAAAAAEAAAAAAAAAAQAAAAIgAQADAAAAAAAAAAwAAAAAAAAAAACAPpqZGT7NzEw+"
],
"attrs": {"tvm_version": "0.9.dev0"}
})
temp_args = [], values = <tvm._ffi._ctypes.packed_func.TVMValue_Array_2 object at 0x137d5b040>, tcodes = <tvm._ffi._ctypes.packed_func.c_int_Array_2 object at 0x137d5b2c0>
def __call__(self, *args):
"""Call the function with positional arguments
args : list
The positional arguments to the function call.
"""
temp_args = []
values, tcodes, num_args = _make_tvm_args(args, temp_args)
ret_val = TVMValue()
ret_tcode = ctypes.c_int()
if (
_LIB.TVMFuncCall(
self.handle,
values,
tcodes,
ctypes.c_int(num_args),
ctypes.byref(ret_val),
ctypes.byref(ret_tcode),
)
!= 0
):
> raise get_last_ffi_error()
E tvm.error.DiagnosticError: Traceback (most recent call last):
E [bt] (8) 9 libtvm.dylib 0x000000012d8a02ae TVMFuncCall + 62
E [bt] (7) 8 libtvm.dylib 0x000000012c378ff4 tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<void tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::transform::Pass, tvm::IRModule)>::AssignTypedLambda<tvm::transform::$_6>(tvm::transform::$_6, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >)::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) + 948
E [bt] (6) 7 libtvm.dylib 0x000000012c36f66e tvm::transform::Pass::operator()(tvm::IRModule) const + 158
E [bt] (5) 6 libtvm.dylib 0x000000012c36f870 tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 256
E [bt] (4) 5 libtvm.dylib 0x000000012c36ff13 tvm::transform::ModulePassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const + 819
E [bt] (3) 4 libtvm.dylib 0x000000012d5551e4 tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<void tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::IRModule, tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::transform::InferType()::$_2>(tvm::relay::transform::InferType()::$_2)::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) + 1844
E [bt] (2) 3 libtvm.dylib 0x000000012c2f73eb tvm::DiagnosticContext::Render() + 459
E [bt] (1) 2 libtvm.dylib 0x000000012c02b969 tvm::runtime::detail::LogFatal::Entry::Finalize() + 89
E [bt] (0) 1 libtvm.dylib 0x000000012d8bb4b8 tvm::runtime::Backtrace() + 24
E File "/Users/suhail/tvm/src/ir/diagnostic.cc", line 105
E DiagnosticError: one or more error diagnostics were emitted, please check diagnostic render for output.
../tvm/python/tvm/_ffi/_ctypes/packed_func.py:237: DiagnosticError
========================================================================================= short test summary info ==========================================================================================
FAILED tests/python/relay/test_op_qnn_dense.py::test_qnn_dense_without_bias - tvm.error.DiagnosticError: Traceback (most recent call last):
FAILED tests/python/relay/test_op_qnn_dense.py::test_qnn_dense_with_bias - tvm.error.DiagnosticError: Traceback (most recent call last):
FAILED tests/python/relay/test_op_qnn_dense.py::test_qnn_dense_with_requantized_output - tvm.error.DiagnosticError: Traceback (most recent call last):
FAILED tests/python/relay/test_op_qnn_dense.py::test_per_channel_weight_scale - tvm.error.DiagnosticError: Traceback (most recent call last):
```
--
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: commits-unsubscribe@tvm.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org