xidulu opened a new issue #17744: [Numpy] Indexing high-dimensional data raises exception URL: https://github.com/apache/incubator-mxnet/issues/17744 ```python n = 16 W = np.random.rand(16, 16) b = np.random.rand(16,) log_potentials = np.zeros([2]*n) for state in itertools.product([0, 1], repeat=n): state_ind = np.array(state) state_val = 2 * state_ind - 1 log_potentials[state] = state_val.dot(W.dot(state_val)) + b.dot(state_val) print(log_potentials) ``` would raise ```python --------------------------------------------------------------------------- MXNetError Traceback (most recent call last) <ipython-input-318-01383abd1f85> in <module> 6 state_ind = np.array(state) 7 state_val = 2 * state_ind - 1 ----> 8 log_potentials[state] = state_val.dot(W.dot(state_val)) + b.dot(state_val) 9 print(log_potentials) ~/mxnet_master_develop/python/mxnet/numpy/multiarray.py in __setitem__(self, key, value) 818 indexing_dispatch_code = get_indexing_dispatch_code(slc_key) 819 if indexing_dispatch_code == _NDARRAY_BASIC_INDEXING: --> 820 self._set_nd_basic_indexing(key, value) # function is inheritated from NDArray class 821 elif indexing_dispatch_code == _NDARRAY_EMPTY_TUPLE_INDEXING: 822 pass # no action needed ~/mxnet_master_develop/python/mxnet/ndarray/ndarray.py in _set_nd_basic_indexing(self, key, value) 1000 value_nd = self._prepare_value_nd(value, bcast_shape=bcast_shape, squeeze_axes=new_axes) 1001 value_nd = value_nd.reshape(indexed_shape) -> 1002 self.slice_assign(value_nd, begin, end, step) 1003 1004 def _get_nd_basic_indexing(self, key): ~/mxnet_master_develop/python/mxnet/numpy/multiarray.py in slice_assign(self, rhs, begin, end, step) 1643 [1., 1.]]]) 1644 """ -> 1645 return _npi.slice_assign(self, rhs, begin=begin, end=end, step=step, out=self) 1646 1647 def take(self, indices, axis=None, mode='raise'): # pylint: disable=arguments-differ, redefined-outer-name ~/mxnet_master_develop/python/mxnet/ndarray/register.py in slice_assign(lhs, rhs, begin, end, step, out, name, **kwargs) ~/mxnet_master_develop/python/mxnet/_ctypes/ndarray.py in _imperative_invoke(handle, ndargs, keys, vals, out, is_np_op, output_is_list) 89 c_str_array(keys), 90 c_str_array([str(s) for s in vals]), ---> 91 ctypes.byref(out_stypes))) 92 93 create_ndarray_fn = _global_var._np_ndarray_cls if is_np_op else _global_var._ndarray_cls ~/mxnet_master_develop/python/mxnet/base.py in check_call(ret) 244 """ 245 if ret != 0: --> 246 raise get_last_ffi_error() 247 248 MXNetError: Traceback (most recent call last): [bt] (5) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(MXImperativeInvokeEx+0x8b) [0x7f756303e80b] [bt] (4) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(MXImperativeInvokeImpl(void*, int, void**, int*, void***, int, char const**, char const**)+0x652) [0x7f756303e112] [bt] (3) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(mxnet::Imperative::Invoke(mxnet::Context const&, nnvm::NodeAttrs const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&)+0x23a) [0x7f75631daf0a] [bt] (2) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(mxnet::imperative::SetShapeType(mxnet::Context const&, nnvm::NodeAttrs const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, mxnet::DispatchMode*)+0x2c5) [0x7f75631e23a5] [bt] (1) /home/ubuntu/mxnet_master_develop/python/mxnet/../../build/libmxnet.so(mxnet::op::SliceAssignOpShape(nnvm::NodeAttrs const&, std::vector<mxnet::TShape, std::allocator<mxnet::TShape> >*, std::vector<mxnet::TShape, std::allocator<mxnet::TShape> >*)+0x381) [0x7f7566fd5241] [bt] (0) /home/ubuntu/anaconda3/lib/python3.7/site-packages/dgl/libdgl.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x22) [0x7f75a5469f42] File "../src/operator/tensor/./matrix_op-inl.h", line 1100 MXNetError: ndim=16too large ```
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