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fixed tuple error - #10216

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AndrewZhaoLuo merged 1 commit into
apache:mainfrom
alnah005:main
May 27, 2022
Merged

fixed tuple error#10216
AndrewZhaoLuo merged 1 commit into
apache:mainfrom
alnah005:main

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@alnah005

@alnah005alnah005 commented Feb 10, 2022

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tuple cannot be set because it is immutable. I was running a network that had a dense layer with 3D input. Very minimal fix!

@mbrookhart

mbrookhart
mbrookhart reviewed Feb 10, 2022
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LGTM, but would you mind adding a test that hits your usecase?

@alnah005
alnah005force-pushed the main branch 3 times, most recently from c5cd449 to 03462a9CompareFebruary 10, 2022 21:20
@alnah005

alnah005 commented Feb 10, 2022

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LGTM, but would you mind adding a test that hits your usecase?

Added 3d input tests

@mbrookhart

mbrookhart commented Feb 10, 2022

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Looks like you have a lint problem. run make format in the root directory

@alnah005

alnah005 commented Feb 10, 2022•
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Looks like you have a lint problem. run make format in the root directory

It modified files I had nothing to do with. Should I push those as well? Just pushed.

@alnah005
alnah005force-pushed the main branch 2 times, most recently from 71befc1 to 6454e4dCompareFebruary 12, 2022 05:16
@areusch

areusch commented Apr 5, 2022

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@alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?

@alnah005

alnah005 commented Apr 21, 2022

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@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):

AndrewZhaoLuo
AndrewZhaoLuo reviewed May 18, 2022
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Comment threadtests/python/relay/test_op_qnn_dense.py Outdated
@AndrewZhaoLuo

AndrewZhaoLuo commented May 19, 2022

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Appears to be a flaky CI thing. Please push an empty commit to go again

@areusch

areusch commented May 23, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?

@alnah005

alnah005 commented May 24, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?

Just did! Hope it resolves that issue.

areusch
areusch reviewed May 26, 2022
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755

@alnah005

alnah005 commented May 26, 2022

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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755

Done!

@AndrewZhaoLuo

AndrewZhaoLuo commented May 27, 2022

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Thanks! Sorry for the long time to merge :/

@AndrewZhaoLuo
AndrewZhaoLuo merged commit bc492ac into apache:mainMay 27, 2022
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@alnah005@mbrookhart@areusch@AndrewZhaoLuo
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fixed tuple error by alnah005 · Pull Request #10216 · apache/tvm · GitHub
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fixed tuple error - #10216
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AndrewZhaoLuo merged 1 commit into
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alnah005:main
May 27, 2022
Merged
fixed tuple error#10216
AndrewZhaoLuo merged 1 commit into
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alnah005:main
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@alnah005
@alnah005alnah005
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Feb 10, 2022

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tuple cannot be set because it is immutable. I was running a network that had a dense layer with 3D input. Very minimal fix!
@mbrookhart
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LGTM, but would you mind adding a test that hits your usecase?
@alnah005
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@alnah005
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LGTM, but would you mind adding a test that hits your usecase?
Added 3d input tests
@mbrookhart
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Looks like you have a lint problem. run make format in the root directory
@alnah005
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Looks like you have a lint problem. run make format in the root directory
It modified files I had nothing to do with. Should I push those as well? Just pushed.
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@areusch
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@alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?
@alnah005
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@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):

AndrewZhaoLuo
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@AndrewZhaoLuo
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May 19, 2022

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Appears to be a flaky CI thing. Please push an empty commit to go again
@areusch
areusch
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May 23, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
@alnah005
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May 24, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
Just did! Hope it resolves that issue.
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
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May 26, 2022

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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
Done!
@AndrewZhaoLuo
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May 27, 2022

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Thanks! Sorry for the long time to merge :/
@AndrewZhaoLuo
AndrewZhaoLuo
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apache:mainMay 27, 2022
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@alnah005@mbrookhart@areusch@AndrewZhaoLuo

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fixed tuple error by alnah005 · Pull Request #10216 · apache/tvm · GitHub
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fixed tuple error - #10216
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fixed tuple error#10216
AndrewZhaoLuo merged 1 commit into
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@alnah005
@alnah005alnah005
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Feb 10, 2022

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tuple cannot be set because it is immutable. I was running a network that had a dense layer with 3D input. Very minimal fix!
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LGTM, but would you mind adding a test that hits your usecase?
@alnah005
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@alnah005
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LGTM, but would you mind adding a test that hits your usecase?
Added 3d input tests
@mbrookhart
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Feb 10, 2022

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Looks like you have a lint problem. run make format in the root directory
@alnah005
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Feb 10, 2022•

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Looks like you have a lint problem. run make format in the root directory
It modified files I had nothing to do with. Should I push those as well? Just pushed.
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@areusch
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@alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?
@alnah005
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Apr 21, 2022

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@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):

AndrewZhaoLuo
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@AndrewZhaoLuo
AndrewZhaoLuo
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May 19, 2022

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Appears to be a flaky CI thing. Please push an empty commit to go again
@areusch
areusch
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May 23, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
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May 24, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
Just did! Hope it resolves that issue.
areusch
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
Done!
@AndrewZhaoLuo
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May 27, 2022

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Thanks! Sorry for the long time to merge :/
@AndrewZhaoLuo
AndrewZhaoLuo
merged commit bc492ac
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apache:mainMay 27, 2022
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@alnah005@mbrookhart@areusch@AndrewZhaoLuo

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fixed tuple error by alnah005 · Pull Request #10216 · apache/tvm · GitHub
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fixed tuple error - #10216
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fixed tuple error#10216
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@alnah005
@alnah005alnah005
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Feb 10, 2022

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tuple cannot be set because it is immutable. I was running a network that had a dense layer with 3D input. Very minimal fix!
@mbrookhart
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LGTM, but would you mind adding a test that hits your usecase?
@alnah005
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@alnah005
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LGTM, but would you mind adding a test that hits your usecase?
Added 3d input tests
@mbrookhart
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Feb 10, 2022

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Looks like you have a lint problem. run make format in the root directory
@alnah005
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Feb 10, 2022•

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Looks like you have a lint problem. run make format in the root directory
It modified files I had nothing to do with. Should I push those as well? Just pushed.
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@areusch
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Apr 5, 2022

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@alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?
@alnah005
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Apr 21, 2022

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@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):

AndrewZhaoLuo
AndrewZhaoLuo
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May 18, 2022
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@AndrewZhaoLuo
AndrewZhaoLuo
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May 19, 2022

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Appears to be a flaky CI thing. Please push an empty commit to go again
@areusch
areusch
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May 23, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
@alnah005
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May 24, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
Just did! Hope it resolves that issue.
areusch
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
@alnah005
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May 26, 2022

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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
Done!
@AndrewZhaoLuo
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May 27, 2022

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Thanks! Sorry for the long time to merge :/
@AndrewZhaoLuo
AndrewZhaoLuo
merged commit bc492ac
into
apache:mainMay 27, 2022
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4 participants

@alnah005@mbrookhart@areusch@AndrewZhaoLuo

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
fixed tuple error by alnah005 · Pull Request #10216 · apache/tvm · GitHub
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fixed tuple error - #10216
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AndrewZhaoLuo merged 1 commit into
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alnah005:main
May 27, 2022
Merged
fixed tuple error#10216
AndrewZhaoLuo merged 1 commit into
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alnah005:main
Conversation
@alnah005
@alnah005alnah005
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Feb 10, 2022

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tuple cannot be set because it is immutable. I was running a network that had a dense layer with 3D input. Very minimal fix!
@mbrookhart
mbrookhart
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LGTM, but would you mind adding a test that hits your usecase?
@alnah005
alnah005force-pushed
the
main
branch
3 times, most recently
from
c5cd449 to
03462a9CompareFebruary 10, 2022 21:20
@alnah005
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Feb 10, 2022

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LGTM, but would you mind adding a test that hits your usecase?
Added 3d input tests
@mbrookhart
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Feb 10, 2022

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Looks like you have a lint problem. run make format in the root directory
@alnah005
alnah005
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Feb 10, 2022•

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Looks like you have a lint problem. run make format in the root directory
It modified files I had nothing to do with. Should I push those as well? Just pushed.
@alnah005
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@areusch
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Apr 5, 2022

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@alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?
@alnah005
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Apr 21, 2022

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@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):

AndrewZhaoLuo
AndrewZhaoLuo
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May 18, 2022
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@AndrewZhaoLuo
AndrewZhaoLuo
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May 19, 2022

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Appears to be a flaky CI thing. Please push an empty commit to go again
@areusch
areusch
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May 23, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
@alnah005
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May 24, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
Just did! Hope it resolves that issue.
areusch
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
@alnah005
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May 26, 2022

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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
Done!
@AndrewZhaoLuo
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May 27, 2022

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Thanks! Sorry for the long time to merge :/
@AndrewZhaoLuo
AndrewZhaoLuo
merged commit bc492ac
into
apache:mainMay 27, 2022
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@mbrookhartmbrookhartmbrookhart approved these changes
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@alnah005@mbrookhart@areusch@AndrewZhaoLuo

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
fixed tuple error by alnah005 · Pull Request #10216 · apache/tvm · GitHub
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fixed tuple error - #10216
Merged
AndrewZhaoLuo merged 1 commit into
apache:mainfrom 
alnah005:main
May 27, 2022
Merged
fixed tuple error#10216
AndrewZhaoLuo merged 1 commit into
apache:mainfrom 
alnah005:main
Conversation
@alnah005
@alnah005alnah005
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Feb 10, 2022

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tuple cannot be set because it is immutable. I was running a network that had a dense layer with 3D input. Very minimal fix!
@mbrookhart
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LGTM, but would you mind adding a test that hits your usecase?
@alnah005
alnah005force-pushed
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from
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@alnah005
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Feb 10, 2022

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LGTM, but would you mind adding a test that hits your usecase?
Added 3d input tests
@mbrookhart
mbrookhart
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Feb 10, 2022

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Looks like you have a lint problem. run make format in the root directory
@alnah005
alnah005
commented
Feb 10, 2022•

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Looks like you have a lint problem. run make format in the root directory
It modified files I had nothing to do with. Should I push those as well? Just pushed.
@alnah005
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@areusch
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Apr 5, 2022

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@alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?
@alnah005
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Apr 21, 2022

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@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):

AndrewZhaoLuo
AndrewZhaoLuo
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@AndrewZhaoLuo
AndrewZhaoLuo
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May 19, 2022

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Appears to be a flaky CI thing. Please push an empty commit to go again
@areusch
areusch
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May 23, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
@alnah005
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May 24, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
Just did! Hope it resolves that issue.
areusch
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
@alnah005
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May 26, 2022

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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
Done!
@AndrewZhaoLuo
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May 27, 2022

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Thanks! Sorry for the long time to merge :/
@AndrewZhaoLuo
AndrewZhaoLuo
merged commit bc492ac
into
apache:mainMay 27, 2022
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@mbrookhartmbrookhartmbrookhart approved these changes
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@alnah005@mbrookhart@areusch@AndrewZhaoLuo

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
fixed tuple error by alnah005 · Pull Request #10216 · apache/tvm · GitHub
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fixed tuple error - #10216
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AndrewZhaoLuo merged 1 commit into
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alnah005:main
May 27, 2022
Merged
fixed tuple error#10216
AndrewZhaoLuo merged 1 commit into
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alnah005:main
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@alnah005
@alnah005alnah005
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Feb 10, 2022

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tuple cannot be set because it is immutable. I was running a network that had a dense layer with 3D input. Very minimal fix!
@mbrookhart
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LGTM, but would you mind adding a test that hits your usecase?
@alnah005
alnah005force-pushed
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@alnah005
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Feb 10, 2022

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LGTM, but would you mind adding a test that hits your usecase?
Added 3d input tests
@mbrookhart
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Feb 10, 2022

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Looks like you have a lint problem. run make format in the root directory
@alnah005
alnah005
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Feb 10, 2022•

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Looks like you have a lint problem. run make format in the root directory
It modified files I had nothing to do with. Should I push those as well? Just pushed.
@alnah005
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@areusch
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Apr 5, 2022

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@alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?
@alnah005
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Apr 21, 2022

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@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):

AndrewZhaoLuo
AndrewZhaoLuo
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May 18, 2022
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Comment threadtests/python/relay/test_op_qnn_dense.py
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@AndrewZhaoLuo
AndrewZhaoLuo
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May 19, 2022

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Appears to be a flaky CI thing. Please push an empty commit to go again
@areusch
areusch
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May 23, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
@alnah005
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May 24, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
Just did! Hope it resolves that issue.
areusch
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
@alnah005
alnah005
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May 26, 2022

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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
Done!
@AndrewZhaoLuo
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May 27, 2022

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Thanks! Sorry for the long time to merge :/
@AndrewZhaoLuo
AndrewZhaoLuo
merged commit bc492ac
into
apache:mainMay 27, 2022
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@alnah005@mbrookhart@areusch@AndrewZhaoLuo

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
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var enabled = true;
function applyDarkMode() {
if (!enabled) return;
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if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
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filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
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[data-theme="light"], [data-theme="light"],
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pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
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// Apply on load
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// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
fixed tuple error by alnah005 · Pull Request #10216 · apache/tvm · GitHub
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fixed tuple error - #10216
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AndrewZhaoLuo merged 1 commit into
apache:mainfrom 
alnah005:main
May 27, 2022
Merged
fixed tuple error#10216
AndrewZhaoLuo merged 1 commit into
apache:mainfrom 
alnah005:main
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@alnah005
@alnah005alnah005
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Feb 10, 2022

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tuple cannot be set because it is immutable. I was running a network that had a dense layer with 3D input. Very minimal fix!
@mbrookhart
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LGTM, but would you mind adding a test that hits your usecase?
@alnah005
alnah005force-pushed
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branch
3 times, most recently
from
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@alnah005
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Feb 10, 2022

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LGTM, but would you mind adding a test that hits your usecase?
Added 3d input tests
@mbrookhart
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Feb 10, 2022

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Looks like you have a lint problem. run make format in the root directory
@alnah005
alnah005
commented
Feb 10, 2022•

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Looks like you have a lint problem. run make format in the root directory
It modified files I had nothing to do with. Should I push those as well? Just pushed.
@alnah005
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@areusch
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Apr 5, 2022

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@alnah005 it looks like your test failed in CI. do you mind taking a look? could you also clarify the PR title?
@alnah005
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Apr 21, 2022

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@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):

AndrewZhaoLuo
AndrewZhaoLuo
reviewed
May 18, 2022
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Comment threadtests/python/relay/test_op_qnn_dense.py
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@AndrewZhaoLuo
AndrewZhaoLuo
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May 19, 2022

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Appears to be a flaky CI thing. Please push an empty commit to go again
@areusch
areusch
commented
May 23, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
@alnah005
alnah005
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May 24, 2022

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@alnah005 acutally sorry it looks like this is a not-flaky CI thing, but i think it was fixed in #11339 -- can you rebase and then CI should like this PR?
Just did! Hope it resolves that issue.
areusch
areusch
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May 26, 2022
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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
@alnah005
alnah005
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May 26, 2022

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@alnah005 i retriggered CI to see if this is another CI flake. can you also revert your changes to the python file permissions? looks like both files changed to 0755
Done!
@AndrewZhaoLuo
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May 27, 2022

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Thanks! Sorry for the long time to merge :/
@AndrewZhaoLuo
AndrewZhaoLuo
merged commit bc492ac
into
apache:mainMay 27, 2022
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@alnah005@mbrookhart@areusch@AndrewZhaoLuo