Traceback (most recent call last):


 "trainval_net.py", line 332, in <module>

roi_labels = FPN(im_data, im_info, gt_boxes, num_boxes)


 "/home/zhuyuhe/.conda/envs/dwzpy/lib/python3.5/site-packages/torch/nn/modules/module.py", line 491, in __call__

result = self.forward(*input, **kwargs)


 "/home/zhuyuhe/duwangzhe/fpn_pytorch/lib/model/fpn/fpn.py", line 246, in forward

roi_pool_feat = self._PyramidRoI_Feat(mrcnn_feature_maps, rois, im_info)


 "/home/zhuyuhe/duwangzhe/fpn_pytorch/lib/model/fpn/fpn.py", line 160, in _PyramidRoI_Feat

feat = self.RCNN_roi_pool(feat_maps[i], rois[idx_l], scale)


 "/home/zhuyuhe/.conda/envs/dwzpy/lib/python3.5/site-packages/torch/nn/modules/module.py", line 491, in __call__

result = self.forward(*input, **kwargs)


 "/home/zhuyuhe/duwangzhe/fpn_pytorch/lib/model/roi_pooling/modules/roi_pool.py", line 14, in forward

return RoIPoolFunction(self.pooled_height, self.pooled_width, scale)(features, rois)


 "/home/zhuyuhe/duwangzhe/fpn_pytorch/lib/model/roi_pooling/functions/roi_pool.py", line 26, in forward

features, rois, output, ctx.argmax)


 "/home/zhuyuhe/.conda/envs/dwzpy/lib/python3.5/site-packages/torch/utils/ffi/__init__.py", line 197, in safe_call

result = torch._C._safe_call(*args, **kwargs)
TypeError: float() not supported on cdata 'void *'

Traceback (most recent call last):


 "/home/stefan/workspaces/kaggle/jigsaw-toxic-comment-classification-challenge/challenge/autoencoder/encoder.py", line 35, in <module>

encoded_a = lstm(a)


 "/usr/local/lib/python3.5/dist-packages/keras/layers/recurrent.py", line 499, in __call__

return super(RNN, self).__call__(inputs, **kwargs)


 "/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py", line 590, in __call__

self.build(input_shapes[0])


 "/usr/local/lib/python3.5/dist-packages/keras/layers/recurrent.py", line 461, in build

self.cell.build(step_input_shape)


 "/usr/local/lib/python3.5/dist-packages/keras/layers/recurrent.py", line 1772, in build

constraint=self.bias_constraint)


 "/usr/local/lib/python3.5/dist-packages/keras/legacy/interfaces.py", line 91, in wrapper

return func(*args, **kwargs)


 "/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py", line 411, in add_weight

weight = K.variable(initializer(shape),


 "/usr/local/lib/python3.5/dist-packages/keras/layers/recurrent.py", line 1764, in bias_initializer

self.bias_initializer((self.units * 2,), *args, **kwargs),


 "/usr/local/lib/python3.5/dist-packages/keras/backend/tensorflow_backend.py", line 1878, in concatenate

return tf.concat([to_dense(x) for x in tensors], axis)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 1075, in concat

dtype=dtypes.int32).get_shape(


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 669, in convert_to_tensor

ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/constant_op.py", line 176, in _constant_tensor_conversion_function

return constant(v, dtype=dtype, name=name)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/constant_op.py", line 165, in constant

tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_util.py", line 367, in make_tensor_proto

_AssertCompatible(values, dtype)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible

(dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int32, got list containing Tensors of type '_Message' instead.
