fixed tuple error #10216

alnah005 · 2022-02-10T20:43:38Z

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

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

alnah005 · 2022-02-10T21:22:27Z

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

Added 3d input tests

mbrookhart · 2022-02-10T21:24:14Z

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

alnah005 · 2022-02-10T21:41:55Z

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.

areusch · 2022-04-05T23:10:15Z

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

alnah005 · 2022-04-21T18:50:48Z

@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):

tests/python/relay/test_op_qnn_dense.py

AndrewZhaoLuo · 2022-05-19T16:10:30Z

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

areusch · 2022-05-23T17:49:29Z

@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 · 2022-05-24T18:07:13Z

@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

@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 · 2022-05-26T21:03:52Z

@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 · 2022-05-27T16:22:11Z

Thanks! Sorry for the long time to merge :/

alnah005 requested review from Huyuwei, jwfromm, kazum, mbrookhart, siju-samuel and srkreddy1238 as code owners February 10, 2022 20:43

mbrookhart reviewed Feb 10, 2022

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alnah005 requested review from areusch, comaniac, icemelon, jroesch, junrushao, merrymercy, tqchen and yzhliu as code owners February 10, 2022 21:09

alnah005 force-pushed the main branch 3 times, most recently from c5cd449 to 03462a9 Compare February 10, 2022 21:20

mbrookhart approved these changes Feb 10, 2022

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alnah005 requested review from Hzfengsy, ZihengJiang, kparzysz-quic, liangfu, manupak, masahi, tmoreau89 and vinx13 as code owners February 10, 2022 21:49

alnah005 requested a review from zhiics as a code owner February 10, 2022 21:49

alnah005 force-pushed the main branch 2 times, most recently from 71befc1 to 6454e4d Compare February 12, 2022 05:16

alnah005 force-pushed the main branch from 6454e4d to 2f87c36 Compare March 23, 2022 01:51

AndrewZhaoLuo reviewed May 18, 2022

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tests/python/relay/test_op_qnn_dense.py Outdated Show resolved Hide resolved

alnah005 force-pushed the main branch from 2f87c36 to 217b9f5 Compare May 18, 2022 23:14

alnah005 force-pushed the main branch from 217b9f5 to 47d91dd Compare May 20, 2022 18:28

alnah005 force-pushed the main branch from b4f9bdd to 3512b87 Compare May 24, 2022 18:06

areusch reviewed May 26, 2022

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alnah005 force-pushed the main branch from 3512b87 to 690dcdb Compare May 26, 2022 21:03

fixed tuple error

340af86

alnah005 force-pushed the main branch from 690dcdb to 340af86 Compare May 26, 2022 21:06

AndrewZhaoLuo merged commit bc492ac into apache:main May 27, 2022

fixed tuple error #10216

fixed tuple error #10216

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alnah005 commented Feb 10, 2022

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alnah005 commented Feb 10, 2022

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alnah005 commented May 26, 2022

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alnah005 commented Feb 10, 2022 •

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