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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/11/28 10:14:07 UTC
[GitHub] [incubator-mxnet] xidulu opened a new issue #16937: [Numpy]
Zero-size tensor add zero-size sum raises exception
xidulu opened a new issue #16937: [Numpy] Zero-size tensor add zero-size sum raises exception
URL: https://github.com/apache/incubator-mxnet/issues/16937
## Description
Very weird problem:
```python
npx.set_np()
a = np.ones((3,4))
b = np.ones((3,3,4))
a[:, :0] += b[:, :0].sum(-1)
print(a)
```
```python
MXNetError Traceback (most recent call last)
<ipython-input-57-ed8f66a38679> in <module>
2 b = np.ones((3,3,4))
3 a[:, :0] += b[:, :0].sum(-1)
----> 4 print(a)
~/mxnet_master_develop/python/mxnet/numpy/multiarray.py in __str__(self)
929 def __str__(self):
930 """Returns a string representation of the array."""
--> 931 array_str = self.asnumpy().__str__()
932 context = self.ctx
933 if context.device_type == 'cpu' or self.ndim == 0:
~/mxnet_master_develop/python/mxnet/ndarray/ndarray.py in asnumpy(self)
2550 self.handle,
2551 data.ctypes.data_as(ctypes.c_void_p),
-> 2552 ctypes.c_size_t(data.size)))
2553 return data
2554
~/mxnet_master_develop/python/mxnet/base.py in check_call(ret)
276 """
277 if ret != 0:
--> 278 raise MXNetError(py_str(_LIB.MXGetLastError()))
279
280
MXNetError: [10:12:44] /home/ubuntu/mxnet_master_develop/include/mxnet/././tensor_blob.h:198: Check failed: this->shape_.Size() == shape.Size() (0 vs. 1) : Shape size mismatch 0 v.s. 1
Stack trace:
[bt] (0) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x32) [0x7fc85352bd52]
[bt] (1) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(mxnet::TBlob::reshape(mxnet::TShape const&) const+0x140) [0x7fc8539d1570]
[bt] (2) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(void mxnet::op::ReduceAxesComputeImpl<mshadow::cpu, mxnet::op::mshadow_op::sum, false, false, mxnet::op::mshadow_op::identity>(mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, mxnet::TShape const&)+0x2255) [0x7fc85695c105]
[bt] (3) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(void mxnet::op::NumpyReduceAxesCompute<mshadow::cpu, mxnet::op::mshadow_op::sum, true, false, mxnet::op::mshadow_op::identity>(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)+0x239) [0x7fc8569af0e9]
[bt] (4) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(mxnet::imperative::PushFCompute(std::function<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)> const&, nnvm::Op const*, nnvm::NodeAttrs const&, mxnet::Context const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::Resource, std::allocator<mxnet::Resource> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<unsigned int, std::allocator<unsigned int> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&)::{lambda(mxnet::RunContext)#1}::operator()(mxnet::RunContext) const+0x2a6) [0x7fc855ff97f6]
[bt] (5) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(std::_Function_handler<void (mxnet::RunContext), mxnet::imperative::PushFCompute(std::function<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)> const&, nnvm::Op const*, nnvm::NodeAttrs const&, mxnet::Context const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::Resource, std::allocator<mxnet::Resource> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<unsigned int, std::allocator<unsigned int> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&)::{lambda(mxnet::RunContext)#1}>::_M_invoke(std::_Any_data const&, mxnet::RunContext&&)+0x17) [0x7fc855ff9a47]
[bt] (6) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(+0x413328e) [0x7fc855f2f28e]
[bt] (7) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(mxnet::engine::ThreadedEngine::ExecuteOprBlock(mxnet::RunContext, mxnet::engine::OprBlock*)+0x5cf) [0x7fc855f3b4cf]
[bt] (8) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(std::_Function_handler<void (std::shared_ptr<dmlc::ManualEvent>), mxnet::engine::ThreadedEnginePerDevice::PushToExecute(mxnet::engine::OprBlock*, bool)::{lambda()#1}::operator()() const::{lambda(std::shared_ptr<dmlc::ManualEvent>)#1}>::_M_invoke(std::_Any_data const&, std::shared_ptr<dmlc::ManualEvent>&&)+0x118) [0x7fc855f3ea98]
```
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