RuntimeError: simple_bind error. Arguments:

[TimLiujn]

when i train my own dataset in single gpu,the following is the wrong report.: Traceback (most recent call last): File "/home/ljn/ljn_work/simpledet/detection_train.py", line 313, in train_net(parse_args()) File "/home/ljn/ljn_work/simpledet/detection_train.py", line 295, in train_net profile=profile File "/home/ljn/ljn_work/simpledet/core/detection_module.py", line 969, in fit for_training=True, force_rebind=force_rebind) File "/home/ljn/ljn_work/simpledet/core/detection_module.py", line 450, in bind state_names=self._state_names) File "/usr/local/lib/python3.6/site-packages/mxnet-1.6.0-py3.6.egg/mxnet/module/executor_group.py", line 280, in init self.bind_exec(data_shapes, label_shapes, shared_group) File "/usr/local/lib/python3.6/site-packages/mxnet-1.6.0-py3.6.egg/mxnet/module/executor_group.py", line 376, in bind_exec shared_group)) File "/usr/local/lib/python3.6/site-packages/mxnet-1.6.0-py3.6.egg/mxnet/module/executor_group.py", line 670, in _bind_ith_exec shared_buffer=shared_data_arrays, **input_shapes) File "/usr/local/lib/python3.6/site-packages/mxnet-1.6.0-py3.6.egg/mxnet/symbol/symbol.py", line 1782, in simple_bind raise RuntimeError(error_msg) RuntimeError: simple_bind error. Arguments: data: (1, 3, 800, 1200) im_info: (1, 3) gt_bbox: (1, 100, 5) valid_ranges: (1, 3, 2) rpn_cls_label: (1, 3, 56250) rpn_reg_target: (1, 3, 60, 50, 75) rpn_reg_weight: (1, 3, 60, 50, 75) Traceback (most recent call last): File "src/operator/contrib/./../tensor/.././operator_common.h", line 404 MXNetError: Check failed: p->num_inputs() == p->inputs.size() (1 vs. 4) : Number of inputs to operator _backward_ROIAlign_v2 (1) does not match the actual number of inputs provided to operator roi_align_backward (4).

[huangzehao]

Can you train COCO sucessfully?

[TimLiujn]

Can you train COCO sucessfully?

Yes,this error is due to the mxnet version problem